| Previous changeset 11:254ab97c6a2c (2022-03-15) Next changeset 13:b41a077af3aa (2022-03-22) |
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Commit message:
"planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit e87d28ea433cc26db7fe44768685d08c06f7a0d0" |
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modified:
macros.xml mqppep_anova.xml mqppep_anova_script.Rmd |
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removed:
MaxQuantProcessingScript.R PhosphoPeptide_Upstream_Kinase_Mapping.pl mqppep_mrgfltr.py repository_dependencies.xml search_ppep.py test-data/pSTY_motifs.tabular test-data/test_input_for_preproc.tabular test-data/test_kinase_substrate.tabular test-data/test_networkin.tabular test-data/test_regulatory_sites.tabular test-data/test_swissprot.fasta workflow/ppenrich_suite_wf.ga |
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| diff -r 254ab97c6a2c -r 4deacfee76ef MaxQuantProcessingScript.R --- a/MaxQuantProcessingScript.R Tue Mar 15 12:44:40 2022 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
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| b'@@ -1,705 +0,0 @@\n-#!/usr/bin/env Rscript\n-\n-# This is the implementation for the\n-# "MaxQuant Phosphopeptide Localization Probability Cutoff"\n-# Galaxy tool (mqppep_lclztn_filter)\n-# It is adapted from the MaxQuant Processing Script written by Larry Cheng.\n-\n-# libraries\n-library(optparse)\n-library(data.table)\n-library(stringr)\n-library(ggplot2)\n-\n-# title: "MaxQuant Processing Script"\n-# author: "Larry Cheng"\n-# date: "February 19, 2018"\n-#\n-# # MaxQuant Processing Script\n-# Takes MaxQuant Phospho (STY)sites.txt file as input\n-# and performs the following (in order):\n-# 1) Runs the Proteomics Quality Control software\n-# 2) Remove contaminant and reverse sequence rows\n-# 3) Filters rows based on localization probability\n-# 4) Extract the quantitative data\n-# 5) Sequences phosphopeptides\n-# 6) Merges multiply phosphorylated peptides\n-# 7) Filters out phosphopeptides based on enrichment\n-# The output file contains the phosphopeptide (first column)\n-# and the quantitative values for each sample.\n-#\n-# ## Revision History\n-# Rev. 2022-02-10 :wrap for inclusion in Galaxy\n-# Rev. 2018-02-19 :break up analysis script into "MaxQuant Processing Script"\n-# and "Phosphopeptide Processing Script"\n-# Rev. 2017-12-12 :added PTXQC\n-# added additional plots and table outputs for quality control\n-# allowed for more than 2 samples to be grouped together\n-# (up to 26 (eg, 1A, 1B, 1C, etc))\n-# converted from .r to .rmd file to knit report\n-# for quality control\n-# Rev. 2016-09-11 :automated the FDR cutoffs; removed the option to data\n-# impute multiple times\n-# Rev. 2016-09-09 :added filter to eliminate contaminant & reverse sequence rows\n-# Rev. 2016-09-01 :moved the collapse step from after ANOVA filter to prior to\n-# preANOVA file output\n-# Rev. 2016-08-22 :use regexSampleNames <- "\\\\.(\\\\d + )[AB]$"\n-# so that it looks at the end of string\n-# Rev. 2016-08-05 :Removed vestigial line (ppeptides <- ....)\n-# Rev. 2016-07-03 :Removed row names from the write.table() output for\n-# ANOVA and PreANOVA\n-# Rev. 2016-06-25 :Set default Localization Probability cutoff to 0.75\n-# Rev. 2016-06-23 :fixed a bug in filtering for pY enrichment by resetting\n-# the row numbers afterwards\n-# Rev. 2016-06-21 :test18 + standardized the regexpression in protocol\n-\n-\n-### FUNCTION DECLARATIONS begin ----------------------------------------------\n-\n-# Read first line of file at filePath\n-# adapted from: https://stackoverflow.com/a/35761217/15509512\n-read_first_line <- function(filepath) {\n- con <- file(filepath, "r")\n- line <- readLines(con, n = 1)\n- close(con)\n- return(line)\n-}\n-\n-# Move columns to the end of dataframe\n-# - data: the dataframe\n-# - move: a vector of column names, each of which is an element of names(data)\n-movetolast <- function(data, move) {\n- data[c(setdiff(names(data), move), move)]\n-}\n-\n-# Generate phosphopeptide and build list when applied\n-phosphopeptide_func <- function(df) {\n- # generate peptide sequence and list of phosphopositions\n- phosphoprobsequence <-\n- strsplit(as.character(df["Phospho (STY) Score diffs"]), "")[[1]]\n- output <- vector()\n- phosphopeptide <- ""\n- counter <- 0 # keep track of position in peptide\n- phosphopositions <-\n- vector() # keep track of phosphorylation positions in peptide\n- score_diff <- ""\n- for (chara in phosphoprobsequence) {\n- # build peptide sequence\n- if (!(\n- chara == " " |\n- chara == "(" |\n- chara == ")" |\n- chara == "." |\n- chara == "-" |\n- chara == "0" |\n- chara == "1" |\n- chara == "2" |\n- chara == "3" |\n- chara == "4" |\n- chara == "5" |\n- chara == "6" |\n- chara == "7" |\n- chara == "8" |\n- chara == "9")\n- ) {\n- phosphopeptide <- paste(phosphopeptide, chara, sep = "")\n- counter <- counter + 1\n- }\n- #'..b' column\n-# ...\n-\n-\n-# Collapse multiphosphorylated peptides\n-# ---\n-quant_data_qc_collapsed <-\n- data.table(quant_data_qc, key = "Phosphopeptide")\n-quant_data_qc_collapsed <-\n- aggregate(. ~ Phosphopeptide, quant_data_qc, FUN = collapse_fn)\n-# ...\n-print("quant_data_qc_collapsed")\n-head(quant_data_qc_collapsed)\n-\n-# Compute (as string) % of phosphopeptides that are multiphosphorylated\n-# (for use in next step)\n-# ---\n-pct_multiphos <-\n- (\n- nrow(quant_data_qc) - nrow(quant_data_qc_collapsed)\n- ) / (2 * nrow(quant_data_qc))\n-pct_multiphos <- sprintf("%0.1f%s", 100 * pct_multiphos, "%")\n-# ...\n-\n-\n-# Compute and visualize breakdown of pY, pS, and pT before enrichment filter\n-# ---\n-py_data <-\n- quant_data_qc_collapsed[\n- str_detect(quant_data_qc_collapsed$Phosphopeptide, "pY"),\n- ]\n-ps_data <-\n- quant_data_qc_collapsed[\n- str_detect(quant_data_qc_collapsed$Phosphopeptide, "pS"),\n- ]\n-pt_data <-\n- quant_data_qc_collapsed[\n- str_detect(quant_data_qc_collapsed$Phosphopeptide, "pT"),\n- ]\n-\n-py_num <- nrow(py_data)\n-ps_num <- nrow(ps_data)\n-pt_num <- nrow(pt_data)\n-\n-# Visualize enrichment\n-enrich_graph_data <- data.frame(group = c("pY", "pS", "pT"),\n- value = c(py_num, ps_num, pt_num))\n-\n-enrich_graph_data <-\n- enrich_graph_data[\n- enrich_graph_data$value > 0,\n- ]\n-\n-# Plot pie chart with legend\n-# start: https://stackoverflow.com/a/62522478/15509512\n-# refine: https://www.statology.org/ggplot-pie-chart/\n-# colors: https://colorbrewer2.org/#type=diverging&scheme=BrBG&n=8\n-slices <- enrich_graph_data$value\n-phosphoresidue <- enrich_graph_data$group\n-pct <- round(100 * slices / sum(slices))\n-lbls <-\n- paste(enrich_graph_data$group, "\\n", pct, "%\\n(", slices, ")", sep = "")\n-slc_ctr <- c()\n-run_tot <- 0\n-for (p in pct) {\n- slc_ctr <- c(slc_ctr, run_tot + p / 2.0)\n- run_tot <- run_tot + p\n-}\n-lbl_y <- 100 - slc_ctr\n-df <-\n- data.frame(slices,\n- pct,\n- lbls,\n- phosphoresidue = factor(phosphoresidue, levels = phosphoresidue))\n-gigi <- ggplot(df\n- , aes(x = 1, y = pct, fill = phosphoresidue)) +\n- geom_col(position = "stack", orientation = "x") +\n- geom_text(aes(x = 1, y = lbl_y, label = lbls), col = "black") +\n- coord_polar(theta = "y", direction = -1) +\n- labs(\n- x = NULL\n- ,\n- y = NULL\n- ,\n- title = "Percentages (and counts) of phosphosites, by type of residue"\n- ,\n- caption = sprintf(\n- "Roughly %s of peptides have multiple phosphosites.",\n- pct_multiphos\n- )\n- ) +\n- labs(x = NULL, y = NULL, fill = NULL) +\n- theme_classic() +\n- theme(\n- legend.position = "right"\n- ,\n- axis.line = element_blank()\n- ,\n- axis.text = element_blank()\n- ,\n- axis.ticks = element_blank()\n- ,\n- plot.title = element_text(hjust = 0.5)\n- ,\n- plot.subtitle = element_text(hjust = 0.5)\n- ,\n- plot.caption = element_text(hjust = 0.5)\n- ,\n- plot.title.position = "plot"\n- ) +\n- scale_fill_manual(breaks = phosphoresidue,\n- values = c("#c7eae5", "#f6e8c3", "#dfc27d"))\n-\n-pdf(enrich_graph_filename)\n-print(gigi)\n-dev.off()\n-svg(enrich_graph_filename_svg)\n-print(gigi)\n-dev.off()\n-# ...\n-\n-\n-# Filter phosphopeptides by enrichment\n-# --\n-if (enriched == "Y") {\n- quant_data_qc_enrichment <- quant_data_qc_collapsed[\n- str_detect(quant_data_qc_collapsed$Phosphopeptide, "pY"),\n- ]\n-} else if (enriched == "ST") {\n- quant_data_qc_enrichment <- quant_data_qc_collapsed[\n- str_detect(quant_data_qc_collapsed$Phosphopeptide, "pS") |\n- str_detect(quant_data_qc_collapsed$Phosphopeptide, "pT"),\n- ]\n-} else {\n- print("Error in enriched variable. Set to either \'Y\' or \'ST\'")\n-}\n-# ...\n-\n-print("quant_data_qc_enrichment")\n-head(quant_data_qc_enrichment)\n-\n-# Write phosphopeptides filtered by enrichment\n-# --\n-write.table(\n- quant_data_qc_enrichment,\n- file = output_filename,\n- sep = "\\t",\n- quote = FALSE,\n- row.names = FALSE\n-)\n-# ...\n' |
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| diff -r 254ab97c6a2c -r 4deacfee76ef PhosphoPeptide_Upstream_Kinase_Mapping.pl --- a/PhosphoPeptide_Upstream_Kinase_Mapping.pl Tue Mar 15 12:44:40 2022 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
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| b'@@ -1,2095 +0,0 @@\n-#!/usr/local/bin/perl\r\n-###############################################################################################################################\r\n-# perl Kinase_enrichment_analysis_complete_v0.pl\r\n-#\r\n-# Nick Graham, USC\r\n-# 2016-02-27\r\n-#\r\n-# Built from scripts written by NG at UCLA in Tom Graeber\'s lab:\r\n-# CombinePhosphoSites.pl\r\n-# Retrieve_p_motifs.pl\r\n-# NetworKIN_Motif_Finder_v7.pl\r\n-#\r\n-# Given a list of phospho-peptides, find protein information and upstream kinases.\r\n-# Output file can be used for KS enrichment score calculations using Enrichment_Score4Directory.pl\r\n-#\r\n-# Updated 2022-01-13, Art Eschenlauer, UMN on behalf of Justin Drake\'s lab:\r\n-# Added warnings and used strict;\r\n-# fixed some code paths resulting in more NetworKIN matches;\r\n-# applied Aho-Corasick algorithm (via external Python script because Perl implementation was still too slow)\r\n-# to speed up "Match the non_p_peptides to the @sequences array";\r\n-# added support for SQLite-formatted UniProtKB/Swiss-Prot data as an alternative to FASTA-formatted data;\r\n-# added support for SQLite output in addition to tabular files.\r\n-#\r\n-#\r\n-###############################################################################################################################\r\n-\r\n-use strict;\r\n-use warnings \'FATAL\' => \'all\';\r\n-\r\n-use Getopt::Std;\r\n-use DBD::SQLite::Constants qw/:file_open/;\r\n-use DBI qw(:sql_types);\r\n-use File::Copy;\r\n-use File::Basename;\r\n-use POSIX qw(strftime);\r\n-use Time::HiRes qw(gettimeofday);\r\n-#use Data::Dump qw(dump);\r\n-\r\n-my $USE_SEARCH_PPEP_PY = 1;\r\n-#my $FAILED_MATCH_SEQ = "Failed match";\r\n-my $FAILED_MATCH_SEQ = \'No Sequence\';\r\n-my $FAILED_MATCH_GENE_NAME = \'No_Gene_Name\';\r\n-\r\n-my $dirname = dirname(__FILE__);\r\n-my %opts;\r\n-my ($file_in, $average_or_sum, $db_out, $file_out, $file_melt, $phospho_type);\r\n-my $dbtype;\r\n-my ($fasta_in, $networkin_in, $motifs_in, $PSP_Kinase_Substrate_in, $PSP_Regulatory_Sites_in);\r\n-my (@samples, %sample_id_lut, %ppep_id_lut, %data, @tmp_data, %n);\r\n-my $line = 0;\r\n-my @failed_match = ($FAILED_MATCH_SEQ);\r\n-my @failed_matches;\r\n-my (%all_data);\r\n-my (@p_peptides, @non_p_peptides);\r\n-my @parsed_fasta;\r\n-my (@accessions, @names, @sequences, @databases, $database);\r\n-my ($dbfile, $dbh, $stmth);\r\n-my @col_names;\r\n-my (%matched_sequences, %accessions, %names, %sites, );\r\n-my (@tmp_matches, @tmp_accessions, @tmp_names, @tmp_sites);\r\n-my (%p_residues, @tmp_p_residues, @p_sites, $left, $right, %p_motifs, @tmp_motifs_array, $tmp_motif, $tmp_site, %residues);\r\n-my (@kinases_observed, $kinases);\r\n-my (@kinases_observed_lbl, @phosphosites_observed_lbl);\r\n-my ($p_sequence_kinase, $p_sequence, $kinase);\r\n-my (@motif_sequence, %motif_type, %motif_count);\r\n-my (@kinases_PhosphoSite, $kinases_PhosphoSite);\r\n-my ($p_sequence_kinase_PhosphoSite, $p_sequence_PhosphoSite, $kinase_PhosphoSite);\r\n-my (%regulatory_sites_PhosphoSite_hash);\r\n-my (%domain, %ON_FUNCTION, %ON_PROCESS, %ON_PROT_INTERACT, %ON_OTHER_INTERACT, %notes, %organism);\r\n-my (%unique_motifs);\r\n-my ($kinase_substrate_NetworKIN_matches, $kinase_motif_matches, $kinase_substrate_PhosphoSite_matches);\r\n-my %psp_regsite_protein_2;\r\n-my (%domain_2, %ON_FUNCTION_2, %ON_PROCESS_2, %ON_PROT_INTERACT_2, %N_PROT_INTERACT, %ON_OTHER_INTERACT_2, %notes_2, %organism_2);\r\n-my @timeData;\r\n-my $PhosphoSitePlusCitation;\r\n-my %site_description;\r\n-\r\n-my %kinase_substrate_NetworKIN_matches;\r\n-my %kinase_motif_matches;\r\n-my $regulatory_sites_PhosphoSite;\r\n-my ($seq_plus5aa, $seq_plus7aa, %seq_plus7aa_2);\r\n-my %kinase_substrate_PhosphoSite_matches;\r\n-my @formatted_sequence;\r\n-my $pSTY_sequence;\r\n-my $i;\r\n-my @a;\r\n-my $use_sqlite;\r\n-my $verbose;\r\n-\r\n-##########\r\n-## opts ##\r\n-##########\r\n- ## input files\r\n- # i : path to input file, e.g., \'outputfile_STEP2.txt\'\r\n- # f : path to UniProtKB/SwissProt FASTA\r\n- # s : optional species argument\r\n- # n : path '..b'mes\r\n- $ppep_gene_site_stmth->bind_param(3, $NetworKIN_label); # ppep_gene_site.kinase_map\r\n- $ppep_gene_site_stmth->bind_param(4, $SITE_KINASE_SUBSTRATE); # ppep_gene_site.site_type_id\r\n- if (not $ppep_gene_site_stmth->execute()) {\r\n- print "Error writing tuple ($peptide,$gene_names,$kinases_observed[$i]): $ppep_gene_site_stmth->errstr\\n";\r\n- }\r\n- # ...\r\n- # end store-to-SQLite "ppep_gene_site" table\r\n- }\r\n- else { print OUT "\\t";}\r\n- }\r\n- my %wrote_motif;\r\n- my $motif_parts_0;\r\n- for my $i (0 .. $#motif_sequence) {\r\n- if (exists($kinase_motif_matches{$peptide}{$motif_sequence[$i]})) {\r\n- print OUT "X\\t";\r\n- $motif_parts_0 = $motif_type{$motif_sequence[$i]}." ".$motif_sequence[$i];\r\n- my $key = "$peptide\\t$gene_names\\t$motif_parts_0";\r\n- if (!exists($wrote_motif{$key})) {\r\n- $wrote_motif{$key} = $key;\r\n- print MELT "$peptide\\t$gene_names\\t$site_description{$SITE_MOTIF}\\t$motif_parts_0\\n";\r\n- # print "Line 657: i is $i\\t$kinase_motif_matches{$peptide}{$motif_sequence[$i]}\\n"; #debug\r\n- # begin store-to-SQLite "ppep_gene_site" table\r\n- # ---\r\n- $ppep_gene_site_stmth->bind_param(1, $ppep_id); # ppep_gene_site.ppep_id\r\n- $ppep_gene_site_stmth->bind_param(2, $gene_names); # ppep_gene_site.gene_names\r\n- $ppep_gene_site_stmth->bind_param(3, $motif_parts_0); # ppep_gene_site.kinase_map\r\n- $ppep_gene_site_stmth->bind_param(4, $SITE_MOTIF); # ppep_gene_site.site_type_id\r\n- if (not $ppep_gene_site_stmth->execute()) {\r\n- print "Error writing tuple ($peptide,$gene_names,$motif_parts_0): $ppep_gene_site_stmth->errstr\\n";\r\n- }\r\n- # ...\r\n- # end store-to-SQLite "ppep_gene_site" table\r\n- }\r\n- }\r\n- else { print OUT "\\t";}\r\n- }\r\n- for my $i (0 .. $#kinases_PhosphoSite) {\r\n- if (exists($kinase_substrate_PhosphoSite_matches{$peptide}{$kinases_PhosphoSite[$i]})) {\r\n- print MELT "$peptide\\t$gene_names\\t$site_description{$SITE_PHOSPHOSITE}\\t$phosphosites_observed_lbl[$i]\\n";\r\n- if ($i < $#kinases_PhosphoSite) {\r\n- print OUT "X\\t";\r\n- }\r\n- else {\r\n- print OUT "X\\n";\r\n- }\r\n- # begin store-to-SQLite "ppep_gene_site" table\r\n- # ---\r\n- $ppep_gene_site_stmth->bind_param(1, $ppep_id); # ppep_gene_site.ppep_id\r\n- $ppep_gene_site_stmth->bind_param(2, $gene_names); # ppep_gene_site.gene_names\r\n- $ppep_gene_site_stmth->bind_param(3, $phosphosites_observed_lbl[$i]); # ppep_gene_site.kinase_map\r\n- $ppep_gene_site_stmth->bind_param(4, $SITE_PHOSPHOSITE); # ppep_gene_site.site_type_id\r\n- if (not $ppep_gene_site_stmth->execute()) {\r\n- print "Error writing tuple ($peptide,$gene_names,$phosphosites_observed_lbl[$i]): $ppep_gene_site_stmth->errstr\\n";\r\n- }\r\n- # ...\r\n- # end store-to-SQLite "ppep_gene_site" table\r\n- }\r\n- else {\r\n- if ($i < $#kinases_PhosphoSite) {\r\n- print OUT "\\t";\r\n- }\r\n- elsif ($i == $#kinases_PhosphoSite) {\r\n- print OUT "\\n";\r\n- }\r\n- }\r\n- }\r\n-}\r\n-\r\n-close OUT;\r\n-close MELT;\r\n-$ppep_gene_site_stmth->finish;\r\n-print "begin DB commit at " . format_localtime_iso8601() . "\\n";\r\n-$dbh->{AutoCommit} = $auto_commit;\r\n-$dbh->disconnect if ( defined $dbh );\r\n-\r\n-print "\\nFinished writing output at " . format_localtime_iso8601() ."\\n\\n";\r\n-\r\n-###############################################################################################################################\r\n' |
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| diff -r 254ab97c6a2c -r 4deacfee76ef macros.xml --- a/macros.xml Tue Mar 15 12:44:40 2022 +0000 +++ b/macros.xml Tue Mar 15 18:17:55 2022 +0000 |
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| @@ -1,5 +1,5 @@ <macros> - <token name="@TOOL_VERSION@">0.1.2</token> + <token name="@TOOL_VERSION@">0.1.3</token> <token name="@VERSION_SUFFIX@">0</token> <xml name="requirements"> <requirements> |
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| diff -r 254ab97c6a2c -r 4deacfee76ef mqppep_anova.xml --- a/mqppep_anova.xml Tue Mar 15 12:44:40 2022 +0000 +++ b/mqppep_anova.xml Tue Mar 15 18:17:55 2022 +0000 |
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| @@ -78,7 +78,7 @@ /> </when> </conditional> - <param name="sample_names_regex" type="text" value="\.(\d+)[A-Z]$" + <param name="sample_names_regex" type="text" value="\.\d+[A-Z]$" help="[sample_names_regex] PERL-compatible regular expression extracting sample-names from the the name of a spectrum file (without extension)" label="Sample-extraction regex"> <sanitizer> @@ -87,7 +87,7 @@ </valid> </sanitizer> </param> - <param name="sample_grouping_regex" type="text" value="(\d+)" + <param name="sample_grouping_regex" type="text" value="\d+" help="[sample_grouping_regex] PERL-compatible regular expression extracting sample-group from each sample-name (i.e., extracted by previous regex pattern)" label="Group-extraction regex"> <sanitizer> |
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| diff -r 254ab97c6a2c -r 4deacfee76ef mqppep_anova_script.Rmd --- a/mqppep_anova_script.Rmd Tue Mar 15 12:44:40 2022 +0000 +++ b/mqppep_anova_script.Rmd Tue Mar 15 18:17:55 2022 +0000 |
| [ |
| @@ -11,8 +11,8 @@ imputationMethod: !r c("group-median", "median", "mean", "random")[1] meanPercentile: 1 sdPercentile: 0.2 - regexSampleNames: "\\.(\\d+)[A-Z]$" - regexSampleGrouping: "(\\d+)" + regexSampleNames: "\\.\\d+[A-Z]$" + regexSampleGrouping: "\\d+" imputedDataFilename: "Upstream_Map_pST_outputfile_STEP4_QN_LT.txt" --- ```{r setup, include = FALSE} @@ -570,23 +570,62 @@ sample_factor_levels <- as.factor(regmatches(temp_matches, m2)) - if (length(levels(sample_factor_levels)) < 2) { + nuke_control_sequences <- + function(s) { + s <- gsub("[\\]", "xyzzy_plugh", s) + s <- gsub("[$]", "\\\\$", s) + s <- gsub("xyzzy_plugh", "$\\\\backslash$", s) + return(s) + } cat( "ERROR!!!! Cannot perform ANOVA analysis", - "because it requires two or more factor levels\n" + "(see next page)\\newpage\n" + ) + cat( + "ERROR: ANOVA analysis", + "requires two or more factor levels!\\newline\n" ) - cat("Unparsed sample names are:\n") - print(names(quant_data_imp_qn_log)) - cat(sprintf("Parsing rule for SampleNames is '%s'\n", regex_sample_names)) - cat("Parsed names are:\n") - print(temp_matches) - cat(sprintf( - "Parsing rule for SampleGrouping is '%s'\n", - regex_sample_grouping - )) - cat("Sample group assignments are:\n") - print(regmatches(temp_matches, m2)) + + cat("\\newline\\newline\n") + cat("Unparsed sample names are:\\newline\n", + "\\begin{quote}\n", + paste(names(quant_data_imp_qn_log), collapse = "\\newline\n"), + "\n\\end{quote}\n\n") + + regex_sample_names <- nuke_control_sequences(regex_sample_names) + + cat("\\leavevmode\\newline\n") + cat("Parsing rule for SampleNames is", + "\\newline\n", + "\\text{'", + regex_sample_names, + "'}\\newline\n", + sep = "" + ) + + cat("\nParsed sample names are:\n", + "\\begin{quote}\n", + paste(temp_matches, collapse = "\\newline\n"), + "\n\\end{quote}\n\n") + + regex_sample_grouping <- nuke_control_sequences(regex_sample_grouping) + + cat("\\leavevmode\\newline\n") + cat("Parsing rule for SampleGrouping is", + "\\newline\n", + "\\text{'", + regex_sample_grouping, + "'}\\newline\n", + sep = "" + ) + + cat("\\newline\n") + cat("Sample group assignments are:\n", + "\\begin{quote}\n", + paste(regmatches(temp_matches, m2), collapse = "\\newline\n"), + "\n\\end{quote}\n\n") + } else { p_value_data_anova_ps <- apply( @@ -707,8 +746,6 @@ } ) - - anova_filtered <- data.table( anova_filtered_merge$Phosphopeptide , @@ -719,7 +756,7 @@ colnames(anova_filtered) <- c("Phosphopeptide", colnames(filtered_data_filtered)) - # merge qualitative columns into the ANOVA data + # Merge qualitative columns into the ANOVA data output_table <- data.frame(anova_filtered$Phosphopeptide) output_table <- merge( x = output_table @@ -731,9 +768,16 @@ by.y = "Phosphopeptide" ) - #Produce heatmap to visualize significance and the effect of imputation + # Produce heatmap to visualize significance and the effect of imputation m <- as.matrix(unimputed_quant_data_log[anova_filtered_merge_order, ]) + m_nan_rows <- rowSums( + matrix( + as.integer(is.na(m)), + nrow = nrow(m) + ) + ) + m <- m[!m_nan_rows, ] if (nrow(m) > 0) { rownames_m <- rownames(m) rownames(m) <- sapply( @@ -741,53 +785,53 @@ , FUN = function(i) { sprintf( - anova_filtered_merge_format[i] - , - filtered_p$fdr_adjusted_anova_p[i] - , + anova_filtered_merge_format[i], + filtered_p$fdr_adjusted_anova_p[i], rownames_m[i] ) } ) - margins <- c(max(nchar(colnames(m))) * 10 / 16 # col - , max(nchar(rownames(m))) * 5 / 16 # row - ) - how_many_peptides <- min(50, nrow(m)) + margins <- + c(max(nchar(colnames(m))) * 10 / 16 # col + , max(nchar(rownames(m))) * 5 / 16 # row + ) + how_many_peptides <- min(50, nrow(m)) - cat("\\newpage\n") - if (nrow(m) > 50) { - cat("Heatmap for the 50 most-significant peptides", - sprintf( - "whose adjusted p-value < %0.2f\n", - cutoff) - ) - } else { - cat("Heatmap for peptides whose", - sprintf("adjusted p-value < %0.2f\n", - cutoff) - ) - } - cat("\\newline\n") - cat("\\newline\n") - op <- par("cex.main") - try( - if (nrow(m) > 1) { - par(cex.main = 0.6) - heatmap( - m[how_many_peptides:1, ], - Rowv = NA, - Colv = NA, - cexRow = 0.7, - cexCol = 0.8, - scale = "row", - margins = margins, - main = - "Heatmap of unimputed, unnormalized intensities", - xlab = "" - ) - } - ) - par(op) + cat("\\newpage\n") + if (nrow(m) > 50) { + cat("Heatmap for the 50 most-significant peptides", + sprintf( + "whose adjusted p-value < %0.2f\n", + cutoff) + ) + } else { + cat("Heatmap for peptides whose", + sprintf("adjusted p-value < %0.2f\n", + cutoff) + ) + } + cat("\\newline\n") + cat("\\newline\n") + op <- par("cex.main") + try( + if (nrow(m) > 1) { + par(cex.main = 0.6) + heatmap( + m[how_many_peptides:1, ], + Rowv = NA, + Colv = NA, + cexRow = 0.7, + cexCol = 0.8, + scale = "row", + #ACE scale = "none", + margins = margins, + main = + "Heatmap of unimputed, unnormalized intensities", + xlab = "" + ) + } + ) + par(op) } } } |
| b |
| diff -r 254ab97c6a2c -r 4deacfee76ef mqppep_mrgfltr.py --- a/mqppep_mrgfltr.py Tue Mar 15 12:44:40 2022 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| [ |
| b'@@ -1,1519 +0,0 @@\n-#!/usr/bin/env python\n-\n-# Import the packages needed\n-import argparse\n-import operator # for operator.itemgetter\n-import os.path\n-import re\n-import shutil # for shutil.copyfile(src, dest)\n-import sqlite3 as sql\n-import sys # import the sys module for exc_info\n-import time\n-import traceback # for formatting stack-trace\n-from codecs import getreader as cx_getreader\n-\n-import numpy as np\n-import pandas\n-\n-# global constants\n-N_A = "N/A"\n-\n-\n-# ref: https://stackoverflow.com/a/8915613/15509512\n-# answers: "How to handle exceptions in a list comprehensions"\n-# usage:\n-# from math import log\n-# eggs = [1,3,0,3,2]\n-# print([x for x in [catch(log, egg) for egg in eggs] if x is not None])\n-# producing:\n-# for <built-in function log>\n-# with args (0,)\n-# exception: math domain error\n-# [0.0, 1.0986122886681098, 1.0986122886681098, 0.6931471805599453]\n-def catch(func, *args, handle=lambda e: e, **kwargs):\n-\n- try:\n- return func(*args, **kwargs)\n- except Exception as e:\n- print("For %s" % str(func))\n- print(" with args %s" % str(args))\n- print(" caught exception: %s" % str(e))\n- (ty, va, tb) = sys.exc_info()\n- print(" stack trace: " + str(traceback.format_exception(ty, va, tb)))\n- exit(-1)\n- return None\n-\n-\n-def whine(func, *args, handle=lambda e: e, **kwargs):\n-\n- try:\n- return func(*args, **kwargs)\n- except Exception as e:\n- print("Warning: For %s" % str(func))\n- print(" with args %s" % str(args))\n- print(" caught exception: %s" % str(e))\n- (ty, va, tb) = sys.exc_info()\n- print(" stack trace: " + str(traceback.format_exception(ty, va, tb)))\n- return None\n-\n-\n-def ppep_join(x):\n- x = [i for i in x if N_A != i]\n- result = "%s" % " | ".join(x)\n- if result != "":\n- return result\n- else:\n- return N_A\n-\n-\n-def melt_join(x):\n- tmp = {key.lower(): key for key in x}\n- result = "%s" % " | ".join([tmp[key] for key in tmp])\n- return result\n-\n-\n-def __main__():\n- # Parse Command Line\n- parser = argparse.ArgumentParser(\n- description="Phopsphoproteomic Enrichment Pipeline Merge and Filter."\n- )\n-\n- # inputs:\n- # Phosphopeptide data for experimental results, including the intensities\n- # and the mapping to kinase domains, in tabular format.\n- parser.add_argument(\n- "--phosphopeptides",\n- "-p",\n- nargs=1,\n- required=True,\n- dest="phosphopeptides",\n- help="Phosphopeptide data for experimental results, including the intensities and the mapping to kinase domains, in tabular format",\n- )\n- # UniProtKB/SwissProt DB input, SQLite\n- parser.add_argument(\n- "--ppep_mapping_db",\n- "-d",\n- nargs=1,\n- required=True,\n- dest="ppep_mapping_db",\n- help="UniProtKB/SwissProt SQLite Database",\n- )\n- # species to limit records chosed from PhosPhositesPlus\n- parser.add_argument(\n- "--species",\n- "-x",\n- nargs=1,\n- required=False,\n- default=[],\n- dest="species",\n- help="limit PhosphoSitePlus records to indicated species (field may be empty)",\n- )\n-\n- # outputs:\n- # tabular output\n- parser.add_argument(\n- "--mrgfltr_tab",\n- "-o",\n- nargs=1,\n- required=True,\n- dest="mrgfltr_tab",\n- help="Tabular output file for results",\n- )\n- # CSV output\n- parser.add_argument(\n- "--mrgfltr_csv",\n- "-c",\n- nargs=1,\n- required=True,\n- dest="mrgfltr_csv",\n- help="CSV output file for results",\n- )\n- # SQLite output\n- parser.add_argument(\n- "--mrgfltr_sqlite",\n- "-S",\n- nargs=1,\n- required=True,\n- dest="mrgfltr_sqlite",\n- help="SQLite output file for results",\n- )\n-\n- # "Make it so!" (parse the arguments)\n- optio'..b'cur.execute(\n- CITATION_INSERT_STMT,\n- ("mrgfltr_metadata_view", CITATION_INSERT_PSP_REF),\n- )\n- cur.execute(\n- CITATION_INSERT_STMT, ("mrgfltr_metadata", CITATION_INSERT_PSP_REF)\n- )\n-\n- # Read ppep-to-sequence LUT\n- ppep_lut_df = pandas.read_sql_query(PPEP_ID_SQL, conn)\n- # write only metadata for merged/filtered records to SQLite\n- mrgfltr_metadata_df = output_df.copy()\n- # replace phosphopeptide seq with ppep.id\n- mrgfltr_metadata_df = ppep_lut_df.merge(\n- mrgfltr_metadata_df,\n- left_on="ppep_seq",\n- right_on=PHOSPHOPEPTIDE,\n- how="inner",\n- )\n- mrgfltr_metadata_df.drop(\n- columns=[PHOSPHOPEPTIDE, "ppep_seq"], inplace=True\n- )\n- # rename columns\n- mrgfltr_metadata_df.columns = MRGFLTR_METADATA_COLUMNS\n- mrgfltr_metadata_df.to_sql(\n- "mrgfltr_metadata",\n- con=conn,\n- if_exists="append",\n- index=False,\n- method="multi",\n- )\n-\n- # Close SwissProt SQLite database\n- conn.close()\n- # ----------- Write merge/filter metadata to SQLite database (finish) -----------\n-\n- output_df = output_df.merge(\n- quant_data,\n- how="right",\n- left_on=PHOSPHOPEPTIDE,\n- right_on=PHOSPHOPEPTIDE_MATCH,\n- )\n- output_cols = output_df.columns.tolist()\n- output_cols = output_cols[:-1]\n- output_df = output_df[output_cols]\n-\n- # cosmetic changes to Upstream column\n- output_df[PUTATIVE_UPSTREAM_DOMAINS] = output_df[\n- PUTATIVE_UPSTREAM_DOMAINS\n- ].fillna(\n- ""\n- ) # fill the NaN with "" for those Phosphopeptides that got a "WARNING: Failed match for " in the upstream mapping\n- us_series = pandas.Series(output_df[PUTATIVE_UPSTREAM_DOMAINS])\n- i = 0\n- while i < len(us_series):\n- # turn blanks into N_A to signify the info was searched for but cannot be found\n- if us_series[i] == "":\n- us_series[i] = N_A\n- i += 1\n- output_df[PUTATIVE_UPSTREAM_DOMAINS] = us_series\n-\n- end_time = time.process_time() # timer\n- print(\n- "%0.6f establisheed output [3]" % (end_time - start_time,),\n- file=sys.stderr,\n- ) # timer\n-\n- (output_rows, output_cols) = output_df.shape\n-\n- output_df = output_df.convert_dtypes(convert_integer=True)\n-\n- # Output onto Final CSV file\n- output_df.to_csv(output_filename_csv, index=False)\n- output_df.to_csv(\n- output_filename_tab, quoting=None, sep="\\t", index=False\n- )\n-\n- end_time = time.process_time() # timer\n- print(\n- "%0.6f wrote output [4]" % (end_time - start_time,),\n- file=sys.stderr,\n- ) # timer\n-\n- print(\n- "{:>10} phosphopeptides written to output".format(str(output_rows))\n- )\n-\n- end_time = time.process_time() # timer\n- print(\n- "%0.6f seconds of non-system CPU time were consumed"\n- % (end_time - start_time,),\n- file=sys.stderr,\n- ) # timer\n-\n- # Rev. 7/1/2016\n- # Rev. 7/3/2016 : fill NaN in Upstream column to replace to N/A\'s\n- # Rev. 7/3/2016: renamed Upstream column to PUTATIVE_UPSTREAM_DOMAINS\n- # Rev. 12/2/2021: Converted to Python from ipynb; use fast Aho-Corasick searching; \\\n- # read from SwissProt SQLite database\n- # Rev. 12/9/2021: Transfer code to Galaxy tool wrapper\n-\n- #\n- # copied from Excel Output Script.ipynb END #\n- #\n-\n- try:\n- catch(\n- mqpep_getswissprot,\n- )\n- exit(0)\n- except Exception as e:\n- exit("Internal error running mqpep_getswissprot(): %s" % (e))\n-\n-\n-if __name__ == "__main__":\n- __main__()\n' |
| b |
| diff -r 254ab97c6a2c -r 4deacfee76ef repository_dependencies.xml --- a/repository_dependencies.xml Tue Mar 15 12:44:40 2022 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| b |
| @@ -1,5 +0,0 @@ -<?xml version="1.0" ?> -<repositories description="Suite for preprocessing and ANOVA of MaxQuant results using LC-MS proteomics data from phosphoproteomic enrichment."> - <repository name="mqppep_preproc" owner="eschen42" toolshed="https://testtoolshed.g2.bx.psu.edu" changeset_revision="302918bd77e0"/> - <repository name="mqppep_anova" owner="eschen42" toolshed="https://testtoolshed.g2.bx.psu.edu" changeset_revision="6c22e8563a93"/> -</repositories> \ No newline at end of file |
| b |
| diff -r 254ab97c6a2c -r 4deacfee76ef search_ppep.py --- a/search_ppep.py Tue Mar 15 12:44:40 2022 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| [ |
| b'@@ -1,545 +0,0 @@\n-#!/usr/bin/env python\n-# Search and memoize phosphopeptides in Swiss-Prot SQLite table UniProtKB\n-\n-import argparse\n-import os.path\n-import re\n-import sqlite3\n-import sys # import the sys module for exc_info\n-import time\n-import traceback # import the traceback module for format_exception\n-from codecs import getreader as cx_getreader\n-\n-# For Aho-Corasick search for fixed set of substrings\n-# - add_word\n-# - make_automaton\n-# - iter\n-import ahocorasick\n-\n-\n-# ref: https://stackoverflow.com/a/8915613/15509512\n-# answers: "How to handle exceptions in a list comprehensions"\n-# usage:\n-# from math import log\n-# eggs = [1,3,0,3,2]\n-# print([x for x in [catch(log, egg) for egg in eggs] if x is not None])\n-# producing:\n-# for <built-in function log>\n-# with args (0,)\n-# exception: math domain error\n-# [0.0, 1.0986122886681098, 1.0986122886681098, 0.6931471805599453]\n-def catch(func, *args, handle=lambda e: e, **kwargs):\n-\n- try:\n- return func(*args, **kwargs)\n- except Exception as e:\n- print("For %s" % str(func))\n- print(" with args %s" % str(args))\n- print(" caught exception: %s" % str(e))\n- (ty, va, tb) = sys.exc_info()\n- print(" stack trace: " + str(traceback.format_exception(ty, va, tb)))\n- # exit(-1)\n- return None # was handle(e)\n-\n-\n-def __main__():\n-\n- DROP_TABLES_SQL = """\n- DROP VIEW IF EXISTS ppep_gene_site_view;\n- DROP VIEW IF EXISTS uniprot_view;\n- DROP VIEW IF EXISTS uniprotkb_pep_ppep_view;\n- DROP VIEW IF EXISTS ppep_intensity_view;\n- DROP VIEW IF EXISTS ppep_metadata_view;\n-\n- DROP TABLE IF EXISTS sample;\n- DROP TABLE IF EXISTS ppep;\n- DROP TABLE IF EXISTS site_type;\n- DROP TABLE IF EXISTS deppep_UniProtKB;\n- DROP TABLE IF EXISTS deppep;\n- DROP TABLE IF EXISTS ppep_gene_site;\n- DROP TABLE IF EXISTS ppep_metadata;\n- DROP TABLE IF EXISTS ppep_intensity;\n- """\n-\n- CREATE_TABLES_SQL = """\n- CREATE TABLE deppep\n- ( id INTEGER PRIMARY KEY\n- , seq TEXT UNIQUE ON CONFLICT IGNORE\n- )\n- ;\n- CREATE TABLE deppep_UniProtKB\n- ( deppep_id INTEGER REFERENCES deppep(id) ON DELETE CASCADE\n- , UniProtKB_id TEXT REFERENCES UniProtKB(id) ON DELETE CASCADE\n- , pos_start INTEGER\n- , pos_end INTEGER\n- , PRIMARY KEY (deppep_id, UniProtKB_id, pos_start, pos_end)\n- ON CONFLICT IGNORE\n- )\n- ;\n- CREATE TABLE ppep\n- ( id INTEGER PRIMARY KEY\n- , deppep_id INTEGER REFERENCES deppep(id) ON DELETE CASCADE\n- , seq TEXT UNIQUE ON CONFLICT IGNORE\n- , scrubbed TEXT\n- );\n- CREATE TABLE site_type\n- ( id INTEGER PRIMARY KEY\n- , type_name TEXT UNIQUE ON CONFLICT IGNORE\n- );\n- CREATE INDEX idx_ppep_scrubbed on ppep(scrubbed)\n- ;\n- CREATE TABLE sample\n- ( id INTEGER PRIMARY KEY\n- , name TEXT UNIQUE ON CONFLICT IGNORE\n- )\n- ;\n- CREATE VIEW uniprot_view AS\n- SELECT DISTINCT\n- Uniprot_ID\n- , Description\n- , Organism_Name\n- , Organism_ID\n- , Gene_Name\n- , PE\n- , SV\n- , Sequence\n- , Description || \' OS=\' ||\n- Organism_Name || \' OX=\' || Organism_ID ||\n- CASE WHEN Gene_Name = \'N/A\' THEN \'\' ELSE \' GN=\'|| Gene_Name END ||\n- CASE WHEN PE = \'N/A\' THEN \'\' ELSE \' PE=\'|| PE END ||\n- CASE WHEN SV = \'N/A\' THEN \'\' ELSE \' SV=\'|| SV END\n- AS long_description\n- , '..b' "\\nEach of the following sequences is associated with several accession IDs (which are listed in the first column) but the same gene ID (which is listed in the second column)."\n- )\n- if row[2] != old_seq:\n- old_seq = row[2]\n- duplicate_count += 1\n- if options.warn_duplicates:\n- print("\\n%s\\t%s\\t%s" % row)\n- else:\n- if options.warn_duplicates:\n- print("%s\\t%s" % (row[0], row[1]))\n- if duplicate_count > 0:\n- print(\n- "\\n%d sequences have duplicated accession IDs\\n" % duplicate_count\n- )\n-\n- print("%s accession sequences will be searched\\n" % sequence_count)\n-\n- # print(auto.dump())\n-\n- # Convert the trie to an automaton (a finite-state machine)\n- auto.make_automaton()\n-\n- # Execute query for seqs and metadata without fetching the results yet\n- uniprot_seq_and_id = cur.execute(UNIPROT_SEQ_AND_ID_SQL)\n- while 1:\n- batch = uniprot_seq_and_id.fetchmany(size=50)\n- if not batch:\n- break\n- for Sequence, UniProtKB_id in batch:\n- if Sequence is not None:\n- for end_index, (insert_order, original_value) in auto.iter(\n- Sequence\n- ):\n- ker.execute(\n- """\n- INSERT INTO deppep_UniProtKB\n- (deppep_id,UniProtKB_id,pos_start,pos_end)\n- VALUES (?,?,?,?)\n- """,\n- (\n- insert_order,\n- UniProtKB_id,\n- 1 + end_index - len(original_value),\n- end_index,\n- ),\n- )\n- else:\n- raise ValueError(\n- "UniProtKB_id %s, but Sequence is None: Check whether SwissProt file is missing sequence for this ID"\n- % (UniProtKB_id,)\n- )\n- ker.execute(\n- """\n- SELECT count(*) || \' accession-peptide-phosphopeptide combinations were found\'\n- FROM uniprotkb_pep_ppep_view\n- """\n- )\n- for row in ker.fetchall():\n- print(row[0])\n-\n- ker.execute(\n- """\n- SELECT count(*) || \' accession matches were found\', count(*) AS accession_count\n- FROM (\n- SELECT accession\n- FROM uniprotkb_pep_ppep_view\n- GROUP BY accession\n- )\n- """\n- )\n- for row in ker.fetchall():\n- print(row[0])\n-\n- ker.execute(\n- """\n- SELECT count(*) || \' peptide matches were found\'\n- FROM (\n- SELECT peptide\n- FROM uniprotkb_pep_ppep_view\n- GROUP BY peptide\n- )\n- """\n- )\n- for row in ker.fetchall():\n- print(row[0])\n-\n- ker.execute(\n- """\n- SELECT count(*) || \' phosphopeptide matches were found\', count(*) AS phosphopeptide_count\n- FROM (\n- SELECT phosphopeptide\n- FROM uniprotkb_pep_ppep_view\n- GROUP BY phosphopeptide\n- )\n- """\n- )\n- for row in ker.fetchall():\n- print(row[0])\n-\n- # link peptides not found in sequence database to a dummy sequence-record\n- ker.execute(\n- """\n- INSERT INTO deppep_UniProtKB(deppep_id,UniProtKB_id,pos_start,pos_end)\n- SELECT id, \'No Uniprot_ID\', 0, 0\n- FROM deppep\n- WHERE id NOT IN (SELECT deppep_id FROM deppep_UniProtKB)\n- """\n- )\n-\n- con.commit()\n- ker.execute("vacuum")\n- con.close()\n-\n-\n-if __name__ == "__main__":\n- wrap_start_time = time.perf_counter()\n- __main__()\n- wrap_stop_time = time.perf_counter()\n- # print(wrap_start_time)\n- # print(wrap_stop_time)\n- print(\n- "\\nThe matching process took %d milliseconds to run.\\n"\n- % ((wrap_stop_time - wrap_start_time) * 1000),\n- )\n-\n-# vim: sw=4 ts=4 et ai :\n' |
| b |
| diff -r 254ab97c6a2c -r 4deacfee76ef test-data/pSTY_motifs.tabular --- a/test-data/pSTY_motifs.tabular Tue Mar 15 12:44:40 2022 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| b |
| b'@@ -1,196 +0,0 @@\n-1\t((E|D|A)(D|E)(E|D)(E|D)pS(E|D|A)(D|E|A)(E|D)(E|D))|(pS.(E|pS|pT))|(pS..(E|pS|pT))|((pS|pT)..(E|D))|(pS(D|E).(D|E).(D|E))|((D|E)pS(D|E).(D|E))|(pS(D|E)(D|E)(D|E))|((pS|pT)..(D|E))|((pS|pT)..(E|D|pS|pY))|((S|E|P|G)(D|S|N|E|P)(E|D|G|Q|W)(Y|E|D|S|W|T)(W|E|D)pS(D|E)(D|E|W|N)(E|D)(E|D|N|Q))\tCasein Kinase II substrate motif (HPRD)\n-2\t((L|F|I)...R(Q|S|T)L(pS|pT)(M|L|I|V))|(..B.R..pS..)|(pS...(pS|pT))\tMAPKAPK2 kinase substrate motif (HPRD)\n-3\t((M|V|L|I|F)(R|K|H)...(pS|pT)...(M|V|L|I|F))|((M|V|L|I)..(R|K|H).(pS|pT)...(M|V|L|I))|((M|V|L|I|F)(R|K|H)..(pS|pT)...(M|V|L|I|F))\tAMP-activated protein kinase substrate motif (HPRD)\n-4\t((P|L|I|M).(L|I|D|E)pSQ)|(LpSQE)|(pSQ)\tATM kinase substrate motif (HPRD)\n-5\t((R|K).R..(pS|pT)(M|L|V|I))|(VFLGFpTYVAP)\tp70 Ribosomal S6 kinase substrate motif (HPRD)\n-6\t((R|K).R..pS)|(RRR.pS)\tMAPKAPK1 kinase substrate motif (HPRD)\n-7\t((R|K)pSP(R|P)(R|K|H))|((pS|pT)P.(R|K))|(HHH(R|K)pSPR(R|K)R)\tCdc2 kinase substrate motif (HPRD)\n-8\t((R|N)(F|L|M)(R|K)(R|K)pS(R|I|V|M)(R|I|M|V)(M|I|F|V)(I|F|M))|(FR.(pS|pT))|(RF(R|K)(R|K)pS(R|I)(R|I)MI)\tNIMA kinase substrate motif (HPRD)\n-9\t((pS|pT)P.(K|R))|((K|R)(pS|pT)P)|((pS|pT)P(K|R))\tGrowth associated histone HI kinase substrate motif (HPRD)\n-10\t(..(pS|pT)E)|(.(pS|pT)...(A|P|S|T))\tG protein-coupled receptor kinase 1 substrate motif (HPRD)\n-11\t(.R..(pS|pT).R.)|((pS|pT).(R|K))|((R|K)..(pS|pT))|((R|K)..(pS|pT).(R|K))|((K|R).(pS|pT))|((R|K).(pS|pT).(R|K))\tPKC kinase substrate motif (HPRD)\n-12\t(.pSQ)|(P(pS|pT).)\tDNA dependent Protein kinase substrate motif (HPRD)\n-13\t(AKRRRLSpSLRA)|(VRKRpTLRRL)\tPAK1 kinase substrate motif (HPRD)\n-14\t(ARKGpSLRQ)|(R(R|F)RR(R|K)GpSF(R|K)(R|K))\tPKC alpha kinase substrate motif (HPRD)\n-15\t(HpSTSDD)|(YRpSVDE)\tBranched chain alpha-ketoacid dehydrogenase kinase substrate motif (HPRD)\n-16\t(KCSpTWP)|(R..pS)|(R.R..pS.P)|(YpTV)|(RS.(pS|pT).P)|(R.(Y|F).pS.P)|(RPVSSAApSVY)\t14-3-3 domain binding motif (HPRD)\n-17\t(KK.RRpT(L|V).)|(KKR.RpT(L|V).)|((R|K).RR.(pS|pT)(L|V).)\tDMPK1 kinase substrate motif (HPRD)\n-18\t(KKKKKK(pS|pT)...)|((R|K|Q|N)(M|C|W)(R|T|S|N)(E|D|S|N)(R|K|E|D|N)pS(S|D|E)(S|GC|D)(SM|R|N)(N|H|S|R|C))\tTGF beta receptor kinase substrate motif (HPRD)\n-19\t(KRKQIpSVR)|((F|M|K)(R|K)(M|R|Q|F)(M|F|L|I)pS(F|I|M|L)(F|R|K)(L|I)(F|L|I))|((K|R)..pS(V|I))\tPhosphorylase kinase substrate motif (HPRD)\n-20\t(KRQGpSVRR)|(R(K|E|R).pS)\tPKC epsilon kinase substrate motif (HPRD)\n-21\t(P.(pS|pT)P)|(pSP)\tERK1, ERK2 Kinase substrate motif (HPRD)\n-22\t(P.(pS|pT)PP)|(..P.(pS|pT)PPP.)\tERK1,2 kinase substrate motif (HPRD)\n-23\t(PL(pS|pT)PIP(K|R|H))|(PL(pS|pT)P.(K|R|H))\tCDK4 kinase substrate motif (HPRD)\n-24\t(PLpTLP)|(PLLpTP)|(PLpTP)|(PpTLP)|(PLpTLP)|(PpTLP)|(LpTP)\tRAF1 kinase substrate motif (HPRD)\n-25\t(R..(pS|pT))|((K|F)(R|K)(Q|M)(Q|M|K|L|F)pS(F|I|M|L|V)(D|E|I)(L|M|K|I)(F|K))|((M|V|L|I|F).(R|K)..(pS|pT)..)|(R..pS)\tCalmodulin-dependent protein kinase II substrate motif (HPRD)\n-26\t(R..pSPV)|(K(pS|pT)P.K)|(KpSP...K)|(KpSP..K)|(KpSP....K)|(KpTPAKEE)|(P.pSP)|(.(pS|pT)P)|(..pSP)\tGSK-3, ERK1, ERK2, CDK5 substrate motif (HPRD)\n-27\t(R.R..(pS|pT)(F|L))|(R.R..(pS|pT))|(GRART(S|T)pSFAE)|((R|Q|K)(R|K|N|Q|P|H)(R|K)(R|S|T)(N|K|Q|H|D|P)pS(F|W|I|M|N|S)(S|T|H)(R|S|K)(S|T|P|Q))|((R|K).(R|K)(S|T).pS)\tAkt kinase substrate motif (HPRD)\n-28\t(RR..pS)|(KR.RpS)|(KRR.pT)\tZIP kinase substrate motif (HPRD)\n-29\t(RR.pS(M|I|L|V|F|Y))|(R.pS)|(KR..pS)|(R..pS)|((R|K).(pS|pT))|(K..(pS|pT))|((R|K)(R|K).(pS|pT))|(K...(pS|pT))|((pS|pT).(R|K))|(RRRRpSIIFI)|(RR.pS)|(R(R|K).(pS|pT)(I|L|V|F|Y)(D|C|.).D)|(RR.pS)|(RRR(R|N)pSII(F|D))|((R|C|P|K)(R|A|P)(R|K)(R|K|S)(N|L|S|M|P)Ps(I|L|V|C)(S|P|H|Q)(S|W|Q)(S|L|G))\tPKA kinase substrate motif (HPRD)\n-30\t(RRFGpSBRRF)|(RRFGpS(M|L|V|I|F)RR(M|L|V|I|F))\tMEKK kinase substrate motif (HPRD)\n-31\t(VPGKARKKpSSCQLL)|(PLARTLpSVAGLP)|((M|I|L|V|F|Y).R..(pS|pT))\tCalmodulin-dependent protein kinase IV substrate motif (HPRD)\n-32\t(pSD.E)|(pS..(E|D))\tCasein kinase II substrate motif (HPRD)\n-33\t(pSP..(pS|pT))|((D|E)..(pS|pT))|((pS|pT)..(S|T))|((pS|pT)...(S|T)(M|L|V|I|F))\tCasein Kinase I substrate'..b'-140\t(pY..P)|(pYDHP)\tCrk SH2 domain binding motif (HPRD)\n-141\t(pY..Q)|(pY(M|L|V|I|F)(P|R|K|H)Q)\tSTAT3 SH2 domain binding motif (HPRD)\n-142\t(pY..YY)|(pY(D|E).(I|L|V|M))|((D|E)..pY)|(pY....(F|Y))\tALK kinase substrate motif (HPRD)\n-143\t(pYIDL)|(pYASI)|(EFpYA.(V|I)G(R|K|H)S)\tSHP2 phosphatase substrate motif (HPRD)\n-144\t(pYM.M)|(EDAIpY)|(.VIpYAAPF)|(EAIpYAAPF)|(EEIpYEEpY)|(E.IpY..P.)|(EEIpYYYVH)|(ERIpYARTK)|(AEV(I|V|L|F)pYAA(P|F)F)\tAbl kinase substrate motif (HPRD)\n-145\t(pYM.M)|(EE(E|N|D)pY(M|F)(M|F)(M|F|I|E)(M|F))|(.EEEpYMMMM)|(KKSRGDpYMTMQIG)|(KKKLPATGDpYMNMSPVGD)\tInsulin receptor kinase substrate motif (HPRD)\n-146\t(pYM.M)|(YIpYGSFK)|(EEEIpY(G|E)EFD)|(D(D|E)(E|D|G)(I|V|L)pY(G|E)E(F|I)F)|((D|E).......(D|E)..pY..L.......Y..(L|I))|((D|E)(D|E)(E|D|G)(I|V|L)pY(G|E|D)E(F|I|L|V)(D|E))|(pY(A|G|S|T|D|E))\tSrc kinase substrate motif (HPRD)\n-147\t(pYM.M)|(pY..M)|(pYMPMS)\tPI3 Kinase p85 SH2 domain binding motif (HPRD)\n-148\tME(E|N)(I|V)pY(G|E)IFF\tFgr kinase substrate motif (HPRD)\n-149\tKKKSPGEpYVNIEFG\tIGF1 receptor kinase substrate motif (HPRD)\n-150\tpY..(L|I|V)\tJAK2 kinase substrate motif (HPRD)\n-151\tpTPpY\tJNK kinase substrate motif (HPRD)\n-152\t(E|D|pT|pY).pYEE\tSyk kinase substrate motif (HPRD)\n-153\tDpYpYR\tPTP1B, TC-PTP phosphatase substrate motif (HPRD)\n-154\t(D|E)FpY(G|A)(F|Y)(A|G)\tPTPRH phosphatase substrate motif (HPRD)\n-155\tF(M|L|V|I)pY\tPTPRJ phosphatase substrate motif (HPRD)\n-156\tpY(E|M|V)(N|V|I)\t3BP2 SH2 domain binding motif (HPRD)\n-157\tpYENP\tAbl SH2 domain binding motif (HPRD)\n-158\tpY(T|A|S)(K|R|Q|N)(M|I|V|R)\tCsk SH2 domain binding motif (HPRD)\n-159\tpYE.(V|I)\tFes SH2 domain binding motif (HPRD)\n-160\tpYEE(I|V)\tFgr SH2 domain binding motif (HPRD)\n-161\tpYEDP\tFyn SH2 domain binding motif (HPRD)\n-162\tpY(M|I|L|V).(M|I|L|V)\tGRB2, 3BP2, Csk, Fes, Syk C-terminal SH2 domain binding motif (HPRD)\n-163\t(F|Y)pY(E|T|Y|S)N(I|L|V|P|T|Y|S)\tGRB7, GRB10 SH2 domain binding motif (HPRD)\n-164\tpYF.(F|P|L|Y)\tHCP SH2 domain binding motif (HPRD)\n-165\tpY(A|E|V)(Y|F|E|S|N|V)(P|F|I|H)\tItk SH2 domain binding motif (HPRD)\n-166\tpYDYV\tLck and Src SH2 domain binding motif (HPRD)\n-167\tpYDEP\tNck SH2 domain binding motif (HPRD)\n-168\tpY(L|I|V)E(L|I|V)\tPLCgamma C and N-terminal SH2 domain binding motif (HPRD)\n-169\tpY..P\tRasGAP C-terminal SH2 domain binding motif (HPRD)\n-170\tpYILV.(M|L|I|V|P)\tRasGAP N-terminal SH2 domain binding motif (HPRD)\n-171\tTIpY..(V|I)\tSAP and EAT2 SH2 domain binding motif (HPRD)\n-172\tpY(L|V)N(V|P)\tSem5 SH2 domain binding motif (HPRD)\n-173\tpY(T|V|I).L\tShb SH2 domain binding motif (HPRD)\n-174\tpY(I|E|Y|L).(I|L|M)\tSHC SH2 domain binding motif (HPRD)\n-175\t(I|V|L|S).pY..(L|I)\tSHIP2 SH2 domain binding motif (HPRD)\n-176\t(I|V).pY..(L|V)\tSHP1 SH2 domain binding motif (HPRD)\n-177\t(V|I|L).pY(M|L|F).P\tSHP1, SHP2 SH2 domain binding motif (HPRD)\n-178\t(T|V|I|Y).pY(A|S|T|V).(I|V|L)\tSHP2 CSH2 domain binding motif (HPRD)\n-179\t(I|L|V)(I|L|V)(I|L|V|F|T|Y)pY(T|I|L|V)(I|L)(I|L|V|P)\tSHP2 C-terminal SH2 domain binding motif (HPRD)\n-180\tpYIPP\tSHP2, PLCgamma SH2 domain binding motif (HPRD)\n-181\tpYM.M\tSrc and Abl SH2 domain binding motif (HPRD)\n-182\tpY(R|K|H|Q|E|D)(R|K|H|Q|E|D)(I|P)\tSrc, Fyn, Lck, Fgr, Abl, Crk, Nck SH2 domain binding motif (HPRD)\n-183\tPP.pY\tSrc, Fyn,Csk, Nck and SHC SH2 domain binding motif (HPRD)\n-184\tpYEEI\tSrc,Lck and Fyn SH2 domains binding motif (HPRD)\n-185\tpY(D|E)(P|R)(R|P|Q)\tSTAT1 SH2 domain binding motif (HPRD)\n-186\tpY(Q|T|E)(E|Q)(L|I)\tSyk C-terminal SH2 domain binding motif (HPRD)\n-187\tpYTT(I|L|M)\tSyk N-terminal SH2 domain binding motif (HPRD)\n-188\t(D|E).......(D|E)..pY..L.......Y..(L|I)\tSyk, ZAP-70, Shc, Lyn SH2 domain binding motif (HPRD)\n-189\tpYEN(F|I|V)\tTensin SH2 domain binding motif (HPRD)\n-190\tD(N|D).pY\tCbl PTB domain binding motif (HPRD)\n-191\tN.LpY\tDok1 PTB domain binding motif (HPRD)\n-192\tN..pY\tFRIP PTB domain binding motif (HPRD)\n-193\tNP.pY\tShc PTB domain binding motif (HPRD)\n-194\tDD.pY\tShb PTB domain binding motif (HPRD)\n-195\tNP.pYF.R\tShcA PTB domain binding motif (HPRD)\n-196\tHN(M|L|V|I)(M|L|V|I|N)NP(S|T)pY\tShcC PTB domain binding motif (HPRD)\n' |
| b |
| diff -r 254ab97c6a2c -r 4deacfee76ef test-data/test_input_for_preproc.tabular --- a/test-data/test_input_for_preproc.tabular Tue Mar 15 12:44:40 2022 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| [ |
| b'@@ -1,38 +0,0 @@\n-Proteins\tPositions within proteins\tLeading proteins\tProtein\tFasta headers\tLocalization prob\tScore diff\tPEP\tScore\tDelta score\tScore for localization\tLocalization prob shL.1A\tScore diff shL.1A\tPEP shL.1A\tScore shL.1A\tLocalization prob shL.1B\tScore diff shL.1B\tPEP shL.1B\tScore shL.1B\tLocalization prob shL.1C\tScore diff shL.1C\tPEP shL.1C\tScore shL.1C\tLocalization prob shR.2A\tScore diff shR.2A\tPEP shR.2A\tScore shR.2A\tLocalization prob shR.2B\tScore diff shR.2B\tPEP shR.2B\tScore shR.2B\tLocalization prob shR.2C\tScore diff shR.2C\tPEP shR.2C\tScore shR.2C\tDiagnostic peak\tNumber of Phospho (STY)\tAmino acid\tSequence window\tModification window\tPeptide window coverage\tPhospho (STY) Probabilities\tPhospho (STY) Score diffs\tPosition in peptide\tCharge\tMass error [ppm]\tIdentification type shL.1A\tIdentification type shL.1B\tIdentification type shL.1C\tIdentification type shR.2A\tIdentification type shR.2B\tIdentification type shR.2C\tIntensity\tIntensity___1\tIntensity___2\tIntensity___3\tRatio mod/base\tIntensity shL.1A\tIntensity shL.1B\tIntensity shL.1C\tIntensity shR.2A\tIntensity shR.2B\tIntensity shR.2C\tRatio mod/base shL.1A\tRatio mod/base shL.1B\tRatio mod/base shL.1C\tRatio mod/base shR.2A\tRatio mod/base shR.2B\tRatio mod/base shR.2C\tIntensity shL.1A___1\tIntensity shL.1A___2\tIntensity shL.1A___3\tIntensity shL.1B___1\tIntensity shL.1B___2\tIntensity shL.1B___3\tIntensity shL.1C___1\tIntensity shL.1C___2\tIntensity shL.1C___3\tIntensity shR.2A___1\tIntensity shR.2A___2\tIntensity shR.2A___3\tIntensity shR.2B___1\tIntensity shR.2B___2\tIntensity shR.2B___3\tIntensity shR.2C___1\tIntensity shR.2C___2\tIntensity shR.2C___3\tOccupancy shL.1A\tOccupancy ratioshL.1A\tOccupancy error scale shL.1A\tOccupancy shL.1B\tOccupancy ratioshL.1B\tOccupancy error scale shL.1B\tOccupancy shL.1C\tOccupancy ratioshL.1C\tOccupancy error scale shL.1C\tOccupancy shR.2A\tOccupancy ratioshR.2A\tOccupancy error scale shR.2A\tOccupancy shR.2B\tOccupancy ratioshR.2B\tOccupancy error scale shR.2B\tOccupancy shR.2C\tOccupancy ratioshR.2C\tOccupancy error scale shR.2C\tReverse\tPotential contaminant\tid\tProtein group IDs\tPositions\tPosition\tPeptide IDs\tMod. peptide IDs\tEvidence IDs\tMS/MS IDs\tBest localization evidence ID\tBest localization MS/MS ID\tBest localization raw file\tBest localization scan number\tBest score evidence ID\tBest score MS/MS ID\tBest score raw file\tBest score scan number\tBest PEP evidence ID\tBest PEP MS/MS ID\tBest PEP raw file\tBest PEP scan number\n-sp|O43768-2|ENSA_HUMAN;sp|O43768|ENSA_HUMAN;sp|O43768-9|ENSA_HUMAN;sp|O43768-3|ENSA_HUMAN;sp|O43768-4|ENSA_HUMAN;sp|O43768-6|ENSA_HUMAN;sp|O43768-5|ENSA_HUMAN;sp|O43768-7|ENSA_HUMAN\t108;108;124;124;131;104;104;120\tsp|O43768-2|ENSA_HUMAN\tsp|O43768-2|ENSA_HUMAN\t\t0.877317\t8.54376\t0.001041\t110.11\t55.028\t110.11\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t1\tS\tTGDHIPTPQDLPQRKSSLVTSKLAG______\tX;X;X;X;X;X;X;X;X;X;X;X;X;X;X;Phospho (STY);X;X;X;X;X;X;X;X;X;X;X;X;X;X;X\tXXXXXXXXXXXXXXPPPPPPPPXXXXXXXXX\tKS(0.877)S(0.123)LVTSK\tKS(8.54)S(-8.54)LVT(-58.58)S(-72.01)K\t2\t2\t0.022801\t\t\tBy MS/MS\t\t\t\t18629000\t18629000\t0\t0\t\t0\t0\t18629000\t0\t0\t0\t\t\t\t\t\t\t0\t0\t0\t0\t0\t0\t18629000\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t700\t529\t108\t108\t12310;20039\t13742;22688\t99166\t91729\t99166\t91729\tQE05099\t5593\t99166\t91729\tQE05099\t5593\t99166\t91729\tQE05099\t5593\n-sp|O43768-2|ENSA_HUMAN;sp|O43768|ENSA_HUMAN;sp|O43768-9|ENSA_HUMAN;sp|O43768-3|ENSA_HUMAN;sp|O43768-4|ENSA_HUMAN;sp|O43768-6|ENSA_HUMAN;sp|O43768-5|ENSA_HUMAN;sp|O43768-7|ENSA_HUMAN\t109;109;125;125;132;105;105;121\tsp|O43768-2|ENSA_HUMAN\tsp|O43768-2|ENSA_HUMAN\t\t0.877764\t9.23011\t0.00135208\t98.182\t25.939\t55.754\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t1\tS\tGDHIPTPQDLPQRKSSLVTSKLAG_______\tX;X;X;X;X;X;X;X;X;X;X;X;X;X;X;Phospho (STY);X;X;X;X;X;X;X;X;X;X;X;X;X;X;X\tXXXXXXXXXXXXXPPPPPPPPXXXXXXXXXX\tKS(0.105)S(0.878)LVT(0.015)S(0.002)K\tKS(-9.23)S(9.23)LVT(-17.65)S(-25.69)K\t3\t2\t-0.061619\tBy MS/MS\tBy MS/MS\tBy matching\tBy matching\tBy matching\tBy MS/MS\t81973000\t81973000\t0\t0\t\t7090300\t8341200\t9691500\t10030000\t1675200\t9952100\t\t\t\t\t\t\t7090300\t0\t0\t8341200\t0\t0\t9691500\t0\t0\t10030000\t0\t0\t1675200\t0\t0\t99'..b'tching\tBy matching\t86590000\t86590000\t0\t0\t0.032027\t17447000\t15753000\t20219000\t14001000\t6284700\t12885000\t0.028348\t0.025719\t0.032895\t0.033925\t0.083789\t0.034516\t17447000\t0\t0\t15753000\t0\t0\t20219000\t0\t0\t14001000\t0\t0\t6284700\t0\t0\t12885000\t0\t0\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\t\t\t1189\t809\t48\t48\t17891\t20149\t142427;142428;142429;142430;142431;142432\t127454\t142427\t127454\tQE05099\t48504\t142427\t127454\tQE05099\t48504\t142427\t127454\tQE05099\t48504\n-sp|Q15836|VAMP3_HUMAN;sp|P63027|VAMP2_HUMAN\t63;80\tsp|Q15836|VAMP3_HUMAN\tsp|Q15836|VAMP3_HUMAN\t\t0.920811\t10.6555\t1.81E-09\t124.1\t98.278\t107.25\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t1\tS\tDRADALQAGASQFETSAAKLKRKYWWKNCKM\tX;X;X;X;X;X;X;X;X;X;X;X;X;X;X;Phospho (STY);X;X;X;X;X;X;X;X;X;X;X;X;X;X;X\tXXPPPPPPPPPPPPPPPPPXXXXXXXXXXXX\tADALQAGASQFET(0.079)S(0.921)AAK\tADALQAGAS(-49.99)QFET(-10.66)S(10.66)AAK\t14\t2\t0.23449\tBy MS/MS\tBy MS/MS\tBy MS/MS\tBy MS/MS\tBy matching\tBy MS/MS\t265240000\t265240000\t0\t0\t0.036151\t44627000\t41445000\t69094000\t42521000\t5738000\t61819000\t0.03226\t0.028442\t0.039791\t0.036967\t0.030963\t0.043392\t44627000\t0\t0\t41445000\t0\t0\t69094000\t0\t0\t42521000\t0\t0\t5738000\t0\t0\t61819000\t0\t0\t0.47624\t0.90925\t12.188\t0.51677\t1.0694\t7.2217\tNaN\tNaN\tNaN\t0.81588\t4.4311\t19.209\tNaN\tNaN\tNaN\t0.4388\t0.78189\t5.9861\t\t\t4442\t2836\t63\t63\t279\t319\t2297;2298;2299;2300;2301;2302\t1992;1993;1994;1995;1996\t2300\t1995\tQE05100\t30086\t2301\t1996\tQE05102\t30007\t2301\t1996\tQE05102\t30007\n-sp|Q15836|VAMP3_HUMAN;sp|P63027|VAMP2_HUMAN;sp|P23763-2|VAMP1_HUMAN;sp|P23763-3|VAMP1_HUMAN;sp|P23763|VAMP1_HUMAN\t44;61;63;63;63\tsp|Q15836|VAMP3_HUMAN\tsp|Q15836|VAMP3_HUMAN\t\t1\t65.4951\t2.36E-06\t126.19\t98.602\t65.495\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t1\tS\tMRVNVDKVLERDQKLSELDDRADALQAGASQ\tX;X;X;X;X;X;X;X;X;X;X;X;X;X;X;Phospho (STY);X;X;X;X;X;X;X;X;X;X;X;X;X;X;X\tXXXXXXXXXXXPPPPPPPPPPXXXXXXXXXX\tDQKLS(1)ELDDR\tDQKLS(65.5)ELDDR\t5\t3\t-0.72518\tBy MS/MS\tBy MS/MS\tBy MS/MS\tBy MS/MS\tBy matching\tBy MS/MS\t412950000\t412950000\t0\t0\tNaN\t75542000\t44814000\t32924000\t35016000\t11023000\t4669900\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\t75542000\t0\t0\t44814000\t0\t0\t32924000\t0\t0\t35016000\t0\t0\t11023000\t0\t0\t4669900\t0\t0\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\t\t\t4443\t2836\t44\t44\t4530\t5083\t37093;37094;37095;37096;37097;37098;37099;37100;37101;37102;37103;37104\t34712;34713;34714;34715;34716;34717;34718;34719\t37100\t34719\tQE05102\t18436\t37093\t34712\tQE05097\t18245\t37093\t34712\tQE05097\t18245\n-sp|Q15836|VAMP3_HUMAN\t11\tsp|Q15836|VAMP3_HUMAN\tsp|Q15836|VAMP3_HUMAN\t\t0.97018\t15.1316\t0.000117365\t79.652\t72.041\t79.652\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t1\tS\t_____MSTGPTAATGSNRRLQQTQNQVDEVV\tX;X;X;X;X;X;X;X;X;X;X;X;X;X;X;Phospho (STY);X;X;X;X;X;X;X;X;X;X;X;X;X;X;X\tXXXXXXPPPPPPPPPPPPPXXXXXXXXXXXX\tSTGPTAAT(0.03)GS(0.97)NRR\tS(-66.94)T(-63.48)GPT(-42.47)AAT(-15.13)GS(15.13)NRR\t10\t2\t-0.15791\tBy matching\tBy matching\tBy MS/MS\tBy matching\tBy matching\tBy MS/MS\t34280000\t34280000\t0\t0\tNaN\t3057100\t4718800\t12052000\t5047700\t1070900\t8333500\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\t3057100\t0\t0\t4718800\t0\t0\t12052000\t0\t0\t5047700\t0\t0\t1070900\t0\t0\t8333500\t0\t0\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\t\t\t4444\t2836\t11\t11\t20280\t22978\t162490;162491;162492;162493;162494;162495\t144222;144223\t162490\t144222\tQE05099\t7582\t162490\t144222\tQE05099\t7582\t162490\t144222\tQE05099\t7582\n-sp|Q9BV40|VAMP8_HUMAN\t55\tsp|Q9BV40|VAMP8_HUMAN\tsp|Q9BV40|VAMP8_HUMAN\t\t0.959784\t13.7778\t3.78E-05\t91.969\t27.98\t91.969\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t1\tS\tNLEHLRNKTEDLEATSEHFKTTSQKVARKFW\tX;X;X;X;X;X;X;X;X;X;X;X;X;X;X;Phospho (STY);X;X;X;X;X;X;X;X;X;X;X;X;X;X;X\tXXXXXXXXPPPPPPPPPPPPXXXXXXXXXXX\tTEDLEAT(0.04)S(0.96)EHFK\tT(-83.18)EDLEAT(-13.78)S(13.78)EHFK\t8\t2\t0.40785\tBy matching\tBy matching\tBy matching\t\t\tBy MS/MS\t114520000\t114520000\t0\t0\tNaN\t20400000\t9738500\t7862300\t0\t0\t76518000\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\t20400000\t0\t0\t9738500\t0\t0\t7862300\t0\t0\t0\t0\t0\t0\t0\t0\t76518000\t0\t0\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\tNaN\t\t\t7902\t4687\t55\t55\t21013\t23827\t168874;168875;168876;168877\t150433\t168874\t150433\tQE05102\t19524\t168874\t150433\tQE05102\t19524\t168874\t150433\tQE05102\t19524\n' |
| b |
| diff -r 254ab97c6a2c -r 4deacfee76ef test-data/test_kinase_substrate.tabular --- a/test-data/test_kinase_substrate.tabular Tue Mar 15 12:44:40 2022 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| b |
| @@ -1,2 +0,0 @@ -GENE KINASE KIN_ACC_ID KIN_ORGANISM SUBSTRATE SUB_GENE_ID SUB_ACC_ID SUB_GENE SUB_ORGANISM SUB_MOD_RSD SITE_GRP_ID SITE_+/-7_AA DOMAIN IN_VIVO_RXN IN_VITRO_RXN CST_CAT# -Csnk2a1 CK2A1 Q60737 human VAMP4 53330 O70480 Vamp4 human S30 454285 RNLLEDDsDEEEDFF X |
| b |
| diff -r 254ab97c6a2c -r 4deacfee76ef test-data/test_networkin.tabular --- a/test-data/test_networkin.tabular Tue Mar 15 12:44:40 2022 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| b |
| @@ -1,33 +0,0 @@ -#substrate position id networkin_score tree netphorest_group netphorest_score string_identifier string_score substrate_name sequence string_path -VAMP4 (ENSP00000236192) 30 CK2alpha 35.6396 KIN CK2_group 0.5228 ENSP00000236192 0.85 VAMP4 LLEDDsDEEED "ENSP00000217244, 0.68 ENSP00000236192" -SSRP1 (ENSP00000278412) 444 CK2alpha 28.6345 KIN CK2_group 0.3768 ENSP00000278412 0.874 SSRP1 DEYADsDEDQH "ENSP00000217244, 0.6992 ENSP00000278412" -SSRP1 (ENSP00000278412) 667 CK2alpha 22.2088 KIN CK2_group 0.3168 ENSP00000278412 0.874 SSRP1 SKEFVsSDESS "ENSP00000217244, 0.6992 ENSP00000278412" -HERC2 (ENSP00000261609) 1577 CK2alpha 10.7686 KIN CK2_group 0.5253 ENSP00000261609 0.4514 HERC2 IGNEEsDLEEA "ENSP00000217244, 0.764 ENSP00000346659, 0.76 ENSP00000261609" -HERC2 (ENSP00000261609) 2928 CK2alpha 10.7686 KIN CK2_group 0.4698 ENSP00000261609 0.4514 HERC2 VPFLAsDNEEE "ENSP00000217244, 0.764 ENSP00000346659, 0.76 ENSP00000261609" -RRP15 (ENSP00000355899) 11 CK2alpha 8.5484 KIN CK2_group 0.3566 ENSP00000355899 0.461 RRP15 PDSRVsEEENL "ENSP00000217244, 0.3688 ENSP00000355899" -SSRP1 (ENSP00000278412) 444 CK2a2 7.8435 KIN CK2_group 0.3768 ENSP00000278412 0.615 SSRP1 DEYADsDEDQH "ENSP00000262506, 0.492 ENSP00000278412" -SSRP1 (ENSP00000278412) 667 CK2a2 7.7757 KIN CK2_group 0.3168 ENSP00000278412 0.615 SSRP1 SKEFVsSDESS "ENSP00000262506, 0.492 ENSP00000278412" -VAMP2 (ENSP00000314214) 80 PKD3 6.9217 KIN PKD_group 0.0744 ENSP00000314214 0.949 VAMP2 SQFETsAAKLK "ENSP00000234179, 0.7592 ENSP00000314214" -VAMP2 (ENSP00000314214) 61 CK2alpha 6.3122 KIN CK2_group 0.3338 ENSP00000314214 0.4391 VAMP2 RDQKLsELDDR "ENSP00000217244, 0.7992 ENSP00000222812, 0.7544 ENSP00000314214" -VAMP1 (ENSP00000380148) 63 CK2alpha 6.1363 KIN CK2_group 0.3338 ENSP00000380148 0.4364 VAMP1 RDQKLsELDDR "ENSP00000217244, 0.7944 ENSP00000222812, 0.7544 ENSP00000380148" -ERC1 (ENSP00000354158) 191 IKKalpha 5.3194 KIN IKKalpha_IKKbeta_group 0.031 ENSP00000354158 0.96 ERC1 IKTFWsPELKK "ENSP00000359424, 0.768 ENSP00000354158" -ERC1 (ENSP00000354158) 191 IKKalpha 5.3194 KIN IKKalpha_IKKbeta_group 0.031 ENSP00000354158 0.96 ERC1 IKTFWsPELKK "ENSP00000359424, 0.768 ENSP00000354158" -VAMP2 (ENSP00000314214) 61 PKAbeta 4.9293 KIN PKA_group 0.1153 ENSP00000314214 0.8 VAMP2 RDQKLsELDDR "ENSP00000359719, 0.64 ENSP00000314214" -VAMP2 (ENSP00000314214) 61 PKAgamma 4.9293 KIN PKA_group 0.1153 ENSP00000314214 0.8 VAMP2 RDQKLsELDDR "ENSP00000366488, 0.64 ENSP00000314214" -VAMP3 (ENSP00000054666) 44 CK2alpha 4.2842 KIN CK2_group 0.3338 ENSP00000054666 0.4201 VAMP3 RDQKLsELDDR "ENSP00000217244, 0.7992 ENSP00000317714, 0.6792 ENSP00000054666" -VAMP2 (ENSP00000314214) 80 PKCiota 3.8971 KIN PKC_group 0.0928 ENSP00000314214 0.899 VAMP2 SQFETsAAKLK "ENSP00000295797, 0.7192 ENSP00000314214" -SSRP1 (ENSP00000278412) 444 CDK7 3.6159 KIN CDK7 0.0186 ENSP00000278412 0.903 SSRP1 DEYADsDEDQH "ENSP00000256443, 0.7224 ENSP00000278412" -SSRP1 (ENSP00000278412) 444 CK1alpha 3.3573 KIN CK1_group 0.1264 ENSP00000278412 0.404 SSRP1 DEYADsDEDQH "ENSP00000261798, 0.3232 ENSP00000278412" -VAMP3 (ENSP00000054666) 11 PKCalpha 3.0633 KIN PKC_group 0.4633 ENSP00000054666 0.3277 VAMP3 TAATGsNRRLQ "ENSP00000284384, 0.6232 ENSP00000359025, 0.6352 ENSP00000054666" -SSRP1 (ENSP00000278412) 659 PKCalpha 3.0524 KIN PKC_group 0.4345 ENSP00000278412 0.237 SSRP1 RQLSEsFKSKE "ENSP00000284384, 0.4552 ENSP00000351885, 0.76 ENSP00000278412" -VAMP2 (ENSP00000314214) 61 PKCiota 2.7785 KIN PKC_group 0.0463 ENSP00000314214 0.899 VAMP2 RDQKLsELDDR "ENSP00000295797, 0.7192 ENSP00000314214" -SSRP1 (ENSP00000278412) 659 CDK7 2.5961 KIN CDK7 0.0104 ENSP00000278412 0.903 SSRP1 RQLSEsFKSKE "ENSP00000256443, 0.7224 ENSP00000278412" -SSRP1 (ENSP00000278412) 667 CDK7 2.5961 KIN CDK7 0.0124 ENSP00000278412 0.903 SSRP1 SKEFVsSDESS "ENSP00000256443, 0.7224 ENSP00000278412" -ERC1 (ENSP00000354158) 191 IKKbeta 2.571 KIN IKKalpha_IKKbeta_group 0.031 ENSP00000354158 0.946 ERC1 IKTFWsPELKK "ENSP00000339151, 0.7568 ENSP00000354158" -ERC1 (ENSP00000354158) 191 IKKbeta 2.571 KIN IKKalpha_IKKbeta_group 0.031 ENSP00000354158 0.946 ERC1 IKTFWsPELKK "ENSP00000339151, 0.7568 ENSP00000354158" -SSRP1 (ENSP00000278412) 659 PKCbeta 2.4948 KIN PKC_group 0.4345 ENSP00000278412 0.1743 SSRP1 RQLSEsFKSKE "ENSP00000305355, 0.7976 ENSP00000366013, 0.7192 ENSP00000284811, 0.7448 ENSP00000278412" -VAMP3 (ENSP00000054666) 11 PKCbeta 2.4948 KIN PKC_group 0.4633 ENSP00000054666 0.2393 VAMP3 TAATGsNRRLQ "ENSP00000305355, 0.512 ENSP00000348986, 0.7616 ENSP00000054666" -SSRP1 (ENSP00000278412) 659 CK2a2 2.4345 KIN CK2_group 0.0356 ENSP00000278412 0.615 SSRP1 RQLSEsFKSKE "ENSP00000262506, 0.492 ENSP00000278412" -ERC1 (ENSP00000354158) 191 HIPK2 2.2748 KIN HIPK1_HIPK2_group 0.0463 ENSP00000354158 0.4159 ERC1 IKTFWsPELKK "ENSP00000263551, 0.7696 ENSP00000286332, 0.7192 ENSP00000354158" -VAMP3 (ENSP00000054666) 11 PKCzeta 2.0773 KIN PKC_group 0.4633 ENSP00000054666 0.4263 VAMP3 TAATGsNRRLQ "ENSP00000367830, 0.7688 ENSP00000320935, 0.796 ENSP00000054666" -SSRP1 (ENSP00000278412) 659 DNAPK 2.0042 KIN DNAPK 0.0584 ENSP00000278412 0.56 SSRP1 RQLSEsFKSKE "ENSP00000313420, 0.448 ENSP00000278412" |
| b |
| diff -r 254ab97c6a2c -r 4deacfee76ef test-data/test_regulatory_sites.tabular --- a/test-data/test_regulatory_sites.tabular Tue Mar 15 12:44:40 2022 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| b |
| @@ -1,8 +0,0 @@ -32017 -"PhosphoSitePlus(R) (PSP) was created by Cell Signaling Technology Inc. It is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. When using PSP data or analyses in printed publications or in online resources, the following acknowledgements must be included: (a) the words ""PhosphoSitePlus(R), www.phosphosite.org"" must be included at appropriate places in the text or webpage, and (b) the following citation must be included in the bibliography: ""Hornbeck PV, Zhang B, Murray B, Kornhauser JM, Latham V, Skrzypek E PhosphoSitePlus, 2014: mutations, PTMs and recalibrations. Nucleic Acids Res. 2015 43:D512-20. PMID: 25514926.""" - -GENE PROTEIN PROT_TYPE ACC_ID GENE_ID HU_CHR_LOC ORGANISM MOD_RSD SITE_GRP_ID SITE_+/-7_AA DOMAIN ON_FUNCTION ON_PROCESS ON_PROT_INTERACT ON_OTHER_INTERACT PMIDs LT_LIT MS_LIT MS_CST NOTES -ENSA ENSA "Inhibitor; Protein phosphatase, regulatory subunit" O43768 2029 1q21.3 human S109-p 477819 DLPQRKSsLVTSKLA Endosulfine "molecular association, regulation; protein conformation" SNCA(DISRUPTS) 18973346 1 34 50 -VAMP8 VAMP8 "Membrane protein, integral; Vesicle" Q9BV40 8673 2p11.2 human S55-p 12738929 TEDLEATsEHFKTTS Synaptobrevin "activity, inhibited" 27402227 1 8 0 "abolish function in SNARE complex during mast cell secretion, reduces in vitro ensemble vesicle fusion" -ENSA ENSA "Inhibitor; Protein phosphatase, regulatory subunit" O43768 2029 1q21.3 human S67-p 455934 KGQKYFDsGDYNMAK Endosulfine "molecular association, regulation" cell cycle regulation PPP2CA(INDUCES) 27889260 3 56 47 -Vamp4 VAMP4 "Membrane protein, integral; Vesicle" O70480 53330 1 H2.1|1 70.29 cM mouse S30-p 454285 RNLLEDDsDEEEDFF "molecular association, regulation; intracellular localization" PACS-1(INDUCES) 14608369 1 64 10 |
| b |
| diff -r 254ab97c6a2c -r 4deacfee76ef test-data/test_swissprot.fasta --- a/test-data/test_swissprot.fasta Tue Mar 15 12:44:40 2022 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| b |
| b'@@ -1,68 +0,0 @@\n->sp|Q9Y3B9|RRP15_HUMAN RRP15-like protein OS=Homo sapiens OX=9606 GN=RRP15 PE=1 SV=2\n-MAAAAPDSRVSEEENLKKTPKKKMKMVTGAVASVLEDEATDTSDSEGSCGSEKDHFYSDDDAIEADSEGDAEPCDKENENDGESSVGTNMGWADAMAKVLNKKTPESKPTILVKNKKLEKEKEKLKQERLEKIKQRDKRLEWEMMCRVKPDVVQDKETERNLQRIATRGVVQLFNAVQKHQKNVDEKVKEAGSSMRKRAKLISTVSKKDFISVLRGMDGSTNETASSRKKPKAKQTEVKSEEGPGWTILRDDFMMGASMKDWDKESDGPDDSRPESASDSDT\n->sp|Q08945|SSRP1_HUMAN FACT complex subunit SSRP1 OS=Homo sapiens OX=9606 GN=SSRP1 PE=1 SV=1\n-MAETLEFNDVYQEVKGSMNDGRLRLSRQGIIFKNSKTGKVDNIQAGELTEGIWRRVALGHGLKLLTKNGHVYKYDGFRESEFEKLSDFFKTHYRLELMEKDLCVKGWNWGTVKFGGQLLSFDIGDQPVFEIPLSNVSQCTTGKNEVTLEFHQNDDAEVSLMEVRFYVPPTQEDGVDPVEAFAQNVLSKADVIQATGDAICIFRELQCLTPRGRYDIRIYPTFLHLHGKTFDYKIPYTTVLRLFLLPHKDQRQMFFVISLDPPIKQGQTRYHFLILLFSKDEDISLTLNMNEEEVEKRFEGRLTKNMSGSLYEMVSRVMKALVNRKITVPGNFQGHSGAQCITCSYKASSGLLYPLERGFIYVHKPPVHIRFDEISFVNFARGTTTTRSFDFEIETKQGTQYTFSSIEREEYGKLFDFVNAKKLNIKNRGLKEGMNPSYDEYADSDEDQHDAYLERMKEEGKIREENANDSSDDSGEETDESFNPGEEEEDVAEEFDSNASASSSSNEGDSDRDEKKRKQLKKAKMAKDRKSRKKPVEVKKGKDPNAPKRPMSAYMLWLNASREKIKSDHPGISITDLSKKAGEIWKGMSKEKKEEWDRKAEDARRDYEKAMKEYEGGRGESSKRDKSKKKKKVKVKMEKKSTPSRGSSSKSSSRQLSESFKSKEFVSSDESSSGENKSKKKRRRSEDSEEEELASTPPSSEDSASGSDE\n->sp|Q96SA4|SERC2_HUMAN Serine incorporator 2 OS=Homo sapiens OX=9606 GN=SERINC2 PE=2 SV=3\n-MGACLGACSLLSCASCLCGSAPCILCSCCPASRNSTVSRLIFTFFLFLGVLVSIIMLSPGVESQLYKLPWVCEEGAGIPTVLQGHIDCGSLLGYRAVYRMCFATAAFFFFFTLLMLCVSSSRDPRAAIQNGFWFFKFLILVGLTVGAFYIPDGSFTNIWFYFGVVGSFLFILIQLVLLIDFAHSWNQRWLGKAEECDSRAWYAGLFFFTLLFYLLSIAAVALMFMYYTEPSGCHEGKVFISLNLTFCVCVSIAAVLPKVQDAQPNSGLLQASVITLYTMFVTWSALSSIPEQKCNPHLPTQLGNETVVAGPEGYETQWWDAPSIVGLIIFLLCTLFISLRSSDHRQVNSLMQTEECPPMLDATQQQQQVAACEGRAFDNEQDGVTYSYSFFHFCLVLASLHVMMTLTNWYKPGETRKMISTWTAVWVKICASWAGLLLYLWTLVAPLLLRNRDFS\n->sp|Q96SA4-2|SERC2_HUMAN Isoform 2 of Serine incorporator 2 OS=Homo sapiens OX=9606 GN=SERINC2\n-MGAEGAPDFLSCPRVRRASCLCGSAPCILCSCCPASRNSTVSRLIFTFFLFLGVLVSIIMLSPGVESQLYKLPWVCEEGAGIPTVLQGHIDCGSLLGYRAVYRMCFATAAFFFFFTLLMLCVSSSRDPRAAIQNGFWFFKFLILVGLTVGAFYIPDGSFTNIWFYFGVVGSFLFILIQLVLLIDFAHSWNQRWLGKAEECDSRAWYAGLFFFTLLFYLLSIAAVALMFMYYTEPSGCHEGKVFISLNLTFCVCVSIAAVLPKVQDAQPNSGLLQASVITLYTMFVTWSALSSIPEQKCNPHLPTQLGNETVVAGPEGYETQWWDAPSIVGLIIFLLCTLFISLRSSDHRQVNSLMQTEECPPMLDATQQQQQVAACEGRAFDNEQDGVTYSYSFFHFCLVLASLHVMMTLTNWYKPGETRKMISTWTAVWVKICASWAGLLLYLWTLVAPLLLRNRDFS\n->sp|Q96SA4-3|SERC2_HUMAN Isoform 3 of Serine incorporator 2 OS=Homo sapiens OX=9606 GN=SERINC2\n-MRSMRLREEESPGPSHTASCLCGSAPCILCSCCPASRNSTVSRLIFTFFLFLGVLVSIIMLSPGVESQLYKLPWVCEEGAGIPTVLQGHIDCGSLLGYRAVYRMCFATAAFFFFFTLLMLCVSSSRDPRAAIQNGFWFFKFLILVGLTVGAFYIPDGSFTNIWFYFGVVGSFLFILIQLVLLIDFAHSWNQRWLGKAEECDSRAWYAGLFFFTLLFYLLSIAAVALMFMYYTEPSGCHEGKVFISLNLTFCVCVSIAAVLPKVQDAQPNSGLLQASVITLYTMFVTWSALSSIPEQKCNPHLPTQLGNETVVAGPEGYETQWWDAPSIVGLIIFLLCTLFISLRSSDHRQVNSLMQTEECPPMLDATQQQQQVAACEGRAFDNEQDGVTYSYSFFHFCLVLASLHVMMTLTNWYKPGETRKMISTWTAVWVKICASWAGLLLYLWTLVAPLLLRNRDFS\n->sp|Q96SA4-4|SERC2_HUMAN Isoform 4 of Serine incorporator 2 OS=Homo sapiens OX=9606 GN=SERINC2\n-MDGRMMRSMRLREEESPGPSHTASCLCGSAPCILCSCCPASRNSTVSRLIFTFFLFLGVLVSIIMLSPGVESQLYKLPWVCEEGAGIPTVLQGHIDCGSLLGYRAVYRMCFATAAFFFFFTLLMLCVSSSRDPRAAIQNGFWFFKFLILVGLTVGAFYIPDGSFTNIWFYFGVVGSFLFILIQLVLLIDFAHSWNQRWLGKAEECDSRAWYAGLFFFTLLFYLLSIAAVALMFMYYTEPSGCHEGKVFISLNLTFCVCVSIAAVLPKVQDAQPNSGLLQASVITLYTMFVTWSALSSIPEQKCNPHLPTQLGNETVVAGPEGYETQWWDAPSIVGLIIFLLCTLFISLRSSDHRQVNSLMQTEECPPMLDATQQQQQVAACEGRAFDNEQDGVTYSYSFFHFCLVLASLHVMMTLTNWYKPGETRKMISTWTAVWVKICASWAGLLLYLWTLVAPLLLRNRDFS\n->sp|Q9NRX5|SERC1_HUMAN Serine incorporator 1 OS=Homo sapiens OX=9606 GN=SERINC1 PE=1 SV=1\n-MGSVLGLCSMASWIPCLCGSAPCLLCRCCPSGNNSTVTRLIYALFLLVGVCVACVMLIPGMEEQLNKIPGFCENEKGVVPCNILVGYKAVYRLCFGLAMFYLLLSLLMIKVKSSSDPRAAVHNGFWFFKFAAAIAIIIGAFFIPEGTFTTVWFYVGMAGAFCFILIQLVLLIDFAHSWNESWVEKMEEGNSRCWYAALLSATALNYLLSLVAIVLFFVYYTHPASCSENKAFISVNMLLCVGASVMSILPKIQESQPRSGLLQSSVITVYTMYLTWSAMTNEPETNCNPSLLSIIGYNTTSTVPKEGQSVQWWHAQGIIGLILFLLCVFYSSIRTSNNSQVNKLTLTSDESTLIEDGGARSDGSLEDGDDVHRAVDNERDGVTYSYSFFHFMLFLASLYIMMTLTNWYRYEPSREMKSQWTAVWVKISSSWIGIVLYVWTLVAPLVLTNRDFD\n->sp|O43768|ENSA_HUMAN Alpha-endosulf'..b'=1 SV=3\n-MYGSARTITNLEGSPSRSPRLPRSPRLGHRRTSSGGGGGTGKTLSMENIQSLNAAYATSGPMYLSDHEGVASTTYPKGTMTLGRATNRAVYGGRVTAMGSSPNIASAGLSHTDVLSYTDQHGGLTGSSHHHHHQVPSMLRQVRDSTMLDLQAQLKELQRENDLLRKELDIKDSKLGSSMNSIKTFWSPELKKERVLRKEEAARMSVLKEQMRVSHEENQHLQLTIQALQDELRTQRDLNHLLQQESGNRGAEHFTIELTEENFRRLQAEHDRQAKELFLLRKTLEEMELRIETQKQTLNARDESIKKLLEMLQSKGLPSKSLEDDNERTRRMAEAESQVSHLEVILDQKEKENIHLREELHRRSQLQPEPAKTKALQTVIEMKDTKIASLERNIRDLEDEIQMLKANGVLNTEDREEEIKQIEVYKSHSKFMKTKIDQLKQELSKKESELLALQTKLETLSNQNSDCKQHIEVLKESLTAKEQRAAILQTEVDALRLRLEEKESFLNKKTKQLQDLTEEKGTLAGEIRDMKDMLEVKERKINVLQKKIENLQEQLRDKDKQLTNLKDRVKSLQTDSSNTDTALATLEEALSEKERIIERLKEQRERDDRERLEEIESFRKENKDLKEKVNALQAELTEKESSLIDLKEHASSLASAGLKRDSKLKSLEIAIEQKKEECSKLEAQLKKAHNIEDDSRMNPEFADQIKQLDKEASYYRDECGKAQAEVDRLLEILKEVENEKNDKDKKIAELESLTLRHMKDQNKKVANLKHNQQLEKKKNAQLLEEVRRREDSMADNSQHLQIEELMNALEKTRQELDATKARLASTQQSLAEKEAHLANLRIERRKQLEEILEMKQEALLAAISEKDANIALLELSASKKKKTQEEVMALKREKDRLVHQLKQQTQNRMKLMADNYDDDHHHYHHHHHHHHHRSPGRSQHSNHRPSPDQDDEEGIWA\n->sp|P23763|VAMP1_HUMAN_Vesicle-associated membrane protein 1 OS=Homo sapiens OX=9606 GN=VAMP1 PE=1 SV=1\n-MSAPAQPPAEGTEGTAPGGGPPGPPPNMTSNRRLQQTQAQVEEVVDIIRVNVDKVLERDQKLSELDDRADALQAGASQFESSAAKLKRKYWWKNCKMMIMLGAICAIIVVVIVIYFFT\n->sp|P23763-3|VAMP1_HUMAN_Isoform 2 of Vesicle-associated membrane protein 1 OS=Homo sapiens OX=9606 GN=VAMP1\n-MSAPAQPPAEGTEGTAPGGGPPGPPPNMTSNRRLQQTQAQVEEVVDIIRVNVDKVLERDQKLSELDDRADALQAGASQFESSAAKLKRKYWWKNCKMMIMLGAICAIIVVVIVSKYR\n->sp|P23763-2|VAMP1_HUMAN_Isoform 3 of Vesicle-associated membrane protein 1 OS=Homo sapiens OX=9606 GN=VAMP1\n-MSAPAQPPAEGTEGTAPGGGPPGPPPNMTSNRRLQQTQAQVEEVVDIIRVNVDKVLERDQKLSELDDRADALQAGASQFESSAAKLKRKYWWKNCKMMIMLGAICAIIVVVIVRRD\n->sp|Q15836|VAMP3_HUMAN_Vesicle-associated membrane protein 3 OS=Homo sapiens OX=9606 GN=VAMP3 PE=1 SV=3\n-MSTGPTAATGSNRRLQQTQNQVDEVVDIMRVNVDKVLERDQKLSELDDRADALQAGASQFETSAAKLKRKYWWKNCKMWAIGITVLVIFIIIIIVWVVSS\n->sp|P63027|VAMP2_HUMAN_Vesicle-associated membrane protein 2 OS=Homo sapiens OX=9606 GN=VAMP2 PE=1 SV=3\n-MSATAATAPPAAPAGEGGPPAPPPNLTSNRRLQQTQAQVDEVVDIMRVNVDKVLERDQKLSELDDRADALQAGASQFETSAAKLKRKYWWKNLKMMIILGVICAIILIIIIVYFST\n->sp|O75379|VAMP4_HUMAN_Vesicle-associated membrane protein 4 OS=Homo sapiens OX=9606 GN=VAMP4 PE=1 SV=2\n-MPPKFKRHLNDDDVTGSVKSERRNLLEDDSDEEEDFFLRGPSGPRFGPRNDKIKHVQNQVDEVIDVMQENITKVIERGERLDELQDKSESLSDNATAFSNRSKQLRRQMWWRGCKIKAIMALVAAILLLVIIILIVMKYRT\n->sp|O75379-2|VAMP4_HUMAN_Isoform 2 of Vesicle-associated membrane protein 4 OS=Homo sapiens OX=9606 GN=VAMP4\n-MPPKFKRHLNDDDVTGSVKSERRNLLEDDSDEEEDFFLGPSGPRFGPRNDKIKHVQNQVDEVIDVMQENITKVIERGERLDELQDKSESLSDNATAFSNRSKQLRRQMWWRGCKIKAIMALVAAILLLVIIILIVMKYRT\n->sp|O95183|VAMP5_HUMAN_Vesicle-associated membrane protein 5 OS=Homo sapiens OX=9606 GN=VAMP5 PE=1 SV=1\n-MAGIELERCQQQANEVTEIMRNNFGKVLERGVKLAELQQRSDQLLDMSSTFNKTTQNLAQKKCWENIRYRICVGLVVVGVLLIILIVLLVVFLPQSSDSSSAPRTQDAGIASGPGN\n->sp|P51809|VAMP7_HUMAN_Vesicle-associated membrane protein 7 OS=Homo sapiens OX=9606 GN=VAMP7 PE=1 SV=3\n-MAILFAVVARGTTILAKHAWCGGNFLEVTEQILAKIPSENNKLTYSHGNYLFHYICQDRIVYLCITDDDFERSRAFNFLNEIKKRFQTTYGSRAQTALPYAMNSEFSSVLAAQLKHHSENKGLDKVMETQAQVDELKGIMVRNIDLVAQRGERLELLIDKTENLVDSSVTFKTTSRNLARAMCMKNLKLTIIIIIVSIVFIYIIVSPLCGGFTWPSCVKK\n->sp|P51809-2|VAMP7_HUMAN_Isoform 2 of Vesicle-associated membrane protein 7 OS=Homo sapiens OX=9606 GN=VAMP7\n-MAILFAVVARGTTILAKHAWCGGNFLEVTEQILAKIPSENNKLTYSHGNYLFHYICQDRIVYLCITDDDFERSRAFNFLNEIKKRFQTTYGSRAQTALPYAMNSEFSSVLAAQLKHHSENKGLDKVMETQAQVDELKGIMVRNIVCHLQNYQQKSCSSHVYEEPQAHYYHHHRINCVHLYHCFTSLWWIYMAKLCEEIGKKKLPLTKDMREQGVKSNPCDSSLSHTDRWYLPVSSTLFSLFKILFHASRFIFVLSTSLFL\n->sp|P51809-3|VAMP7_HUMAN_Isoform 3 of Vesicle-associated membrane protein 7 OS=Homo sapiens OX=9606 GN=VAMP7\n-MAILFAVVARGTTILAKHAWCGGNFLEDFERSRAFNFLNEIKKRFQTTYGSRAQTALPYAMNSEFSSVLAAQLKHHSENKGLDKVMETQAQVDELKGIMVRNIDLVAQRGERLELLIDKTENLVDSSVTFKTTSRNLARAMCMKNLKLTIIIIIVSIVFIYIIVSPLCGGFTWPSCVKK\n->sp|Q9BV40|VAMP8_HUMAN_Vesicle-associated membrane protein 8 OS=Homo sapiens OX=9606 GN=VAMP8 PE=1 SV=1\n-MEEASEGGGNDRVRNLQSEVEGVKNIMTQNVERILARGENLEHLRNKTEDLEATSEHFKTTSQKVARKFWWKNVKMIVLICVIVFIIILFIVLFATGAFS\n' |
| b |
| diff -r 254ab97c6a2c -r 4deacfee76ef workflow/ppenrich_suite_wf.ga --- a/workflow/ppenrich_suite_wf.ga Tue Mar 15 12:44:40 2022 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| [ |
| b'@@ -1,678 +0,0 @@\n-{\n- "a_galaxy_workflow": "true",\n- "annotation": "phoshpoproteomic enrichment data pre-processing and ANOVA",\n- "creator": [\n- {\n- "class": "Person",\n- "identifier": "0000-0002-2882-0508",\n- "name": "Art Eschenlauer"\n- }\n- ],\n- "format-version": "0.1",\n- "license": "MIT",\n- "name": "ppenrich_suite_wf",\n- "steps": {\n- "0": {\n- "annotation": "The Phospho (STY)Sites.txt file produced by MaxQuant (found in the txt folder).",\n- "content_id": null,\n- "errors": null,\n- "id": 0,\n- "input_connections": {},\n- "inputs": [\n- {\n- "description": "The Phospho (STY)Sites.txt file produced by MaxQuant (found in the txt folder).",\n- "name": "Phospho (STY)Sites.txt"\n- }\n- ],\n- "label": "Phospho (STY)Sites.txt",\n- "name": "Input dataset",\n- "outputs": [],\n- "position": {\n- "bottom": -36.30000305175781,\n- "height": 82.19999694824219,\n- "left": 150,\n- "right": 350,\n- "top": -118.5,\n- "width": 200,\n- "x": 150,\n- "y": -118.5\n- },\n- "tool_id": null,\n- "tool_state": "{\\"optional\\": false, \\"format\\": [\\"tabular\\"]}",\n- "tool_version": null,\n- "type": "data_input",\n- "uuid": "f4273d40-f2b8-4ad0-8bcc-91e72bd25fe1",\n- "workflow_outputs": []\n- },\n- "1": {\n- "annotation": "FASTA file of all human canonical isoforms, derived from Swiss-Prot (e.g., merge of https://ftp.uniprot.org/pub/databases/uniprot/current_release/knowledgebase/complete/uniprot_sprot_varsplic.fasta.gz and https://ftp.uniprot.org/pub/databases/uniprot/current_release/knowledgebase/complete/uniprot_sprot.fasta.gz)",\n- "content_id": null,\n- "errors": null,\n- "id": 1,\n- "input_connections": {},\n- "inputs": [\n- {\n- "description": "FASTA file of all human canonical isoforms, derived from Swiss-Prot (e.g., merge of https://ftp.uniprot.org/pub/databases/uniprot/current_release/knowledgebase/complete/uniprot_sprot_varsplic.fasta.gz and https://ftp.uniprot.org/pub/databases/uniprot/current_release/knowledgebase/complete/uniprot_sprot.fasta.gz)",\n- "name": "SwissProt_Human_Canonical_Isoform.fasta"\n- }\n- ],\n- "label": "SwissProt_Human_Canonical_Isoform.fasta",\n- "name": "Input dataset",\n- "outputs": [],\n- "position": {\n- "bottom": 278.1000061035156,\n- "height": 102.60000610351562,\n- "left": 376,\n- "right": 576,\n- "top": 175.5,\n- "width": 200,\n- "x": 376,\n- "y": 175.5\n- },\n- "tool_id": null,\n- "tool_state": "{\\"optional\\": false, \\"format\\": [\\"fasta\\"]}",\n- "tool_version": null,\n- "type": "data_input",\n- "uuid": "cb31b0ac-cacc-42ee-bd42-f42d0bdae128",\n- "workflow_outputs": []\n- },\n- "2": {\n- "annotation": "Derived from https://networkin.info/download/networkin_human_predictions_3.1.tsv.xz (which is free for non-commercial use - for required citation, see https://networkin.info/)",\n- "content_id": null,\n- "errors": null,\n- "id": 2,\n- "input_connections": {},\n- "inputs": [\n- {\n- "description": "Derived from https://networkin.info/download/networkin_human_predictions_3.1.tsv.xz (which is free for non-commercial use - for required citation, see https://networkin.info/)",\n- "name": "NetworKIN_cutoffscore2.0.'..b', \\"__page__\\": null, \\"__rerun_remap_job_id__\\": null}",\n- "tool_version": null,\n- "type": "tool",\n- "uuid": "a3cb902d-8ef6-4f84-bed3-80b2b20d1916",\n- "workflow_outputs": [\n- {\n- "label": "intensities_group-mean-imputed_QN_LT",\n- "output_name": "imputed_data_file",\n- "uuid": "ef19dcd3-8f3e-4fc4-829e-dae6719ff1cc"\n- },\n- {\n- "label": "intensities_group-mean-imputed_report",\n- "output_name": "report_file",\n- "uuid": "26bb93b0-bc11-4455-a280-241253b21981"\n- }\n- ]\n- },\n- "9": {\n- "annotation": "Perform ANOVA. For imputing missing values, create random values.",\n- "content_id": "mqppep_anova",\n- "errors": null,\n- "id": 9,\n- "input_connections": {\n- "alpha_file": {\n- "id": 6,\n- "output_name": "output"\n- },\n- "input_file": {\n- "id": 7,\n- "output_name": "preproc_tab"\n- }\n- },\n- "inputs": [],\n- "label": "MaxQuant Phosphopeptide ANOVA randomly imputed",\n- "name": "MaxQuant Phosphopeptide ANOVA",\n- "outputs": [\n- {\n- "name": "imputed_data_file",\n- "type": "tabular"\n- },\n- {\n- "name": "report_file",\n- "type": "html"\n- }\n- ],\n- "position": {\n- "bottom": 1186,\n- "height": 256,\n- "left": 1308,\n- "right": 1508,\n- "top": 930,\n- "width": 200,\n- "x": 1308,\n- "y": 930\n- },\n- "post_job_actions": {\n- "RenameDatasetActionimputed_data_file": {\n- "action_arguments": {\n- "newname": "#{input_file}.intensities_randomly-imputed_QN_LT"\n- },\n- "action_type": "RenameDatasetAction",\n- "output_name": "imputed_data_file"\n- },\n- "RenameDatasetActionreport_file": {\n- "action_arguments": {\n- "newname": "#{input_file}.intensities_randomly-imputed_report (download/unzip to view)"\n- },\n- "action_type": "RenameDatasetAction",\n- "output_name": "report_file"\n- }\n- },\n- "tool_id": "mqppep_anova",\n- "tool_state": "{\\"alpha_file\\": {\\"__class__\\": \\"ConnectedValue\\"}, \\"first_data_column\\": \\"Intensity\\", \\"imputation\\": {\\"imputation_method\\": \\"random\\", \\"__current_case__\\": 3, \\"meanPercentile\\": \\"1\\", \\"sdPercentile\\": \\"0.2\\"}, \\"input_file\\": {\\"__class__\\": \\"ConnectedValue\\"}, \\"sample_grouping_regex\\": \\"(\\\\\\\\d+)\\", \\"sample_names_regex\\": \\"\\\\\\\\.(\\\\\\\\d+)[A-Z]$\\", \\"__page__\\": null, \\"__rerun_remap_job_id__\\": null}",\n- "tool_version": null,\n- "type": "tool",\n- "uuid": "217d92af-f6d6-4fd3-a78a-090d8afd3ae0",\n- "workflow_outputs": [\n- {\n- "label": "intensities_randomly-imputed_QN_LT",\n- "output_name": "imputed_data_file",\n- "uuid": "925d734f-f9d8-49e8-aebb-c8d7598d45b2"\n- },\n- {\n- "label": "intensities_randomly-imputed_report",\n- "output_name": "report_file",\n- "uuid": "4ab5f1b1-d04e-4634-8765-265122bc1064"\n- }\n- ]\n- }\n- },\n- "tags": [\n- "ppenrich"\n- ],\n- "uuid": "c54c2b2e-8080-445c-bc3e-43950c89d4e4",\n- "version": 3\n-}\n\\ No newline at end of file\n' |