Mercurial > repos > iuc > dada2_primercheck

comparison test-data/gentest.R @ 0:40cd037434d9 draft

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/dada2 commit 3dd3145db6ed58efc3bf5f71e96515173967fc72
author iuc
date Sat, 07 Dec 2024 08:41:16 +0000
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-1:000000000000 0:40cd037434d9
1 library(dada2, quietly = TRUE)
2 library(ggplot2, quietly = TRUE)
3
4 sample_names <- c("F3D0_S188_L001", "F3D141_S207_L001")
5 fwd <- c("F3D0_S188_L001_R1_001.fastq.gz", "F3D141_S207_L001_R1_001.fastq.gz")
6 rev <- c("F3D0_S188_L001_R2_001.fastq.gz", "F3D141_S207_L001_R2_001.fastq.gz")
7
8 filt_fwd <- c("filterAndTrim_F3D0_R1.fq.gz", "filterAndTrim_F3D141_R1.fq.gz")
9 filt_rev <- c("filterAndTrim_F3D0_R2.fq.gz", "filterAndTrim_F3D141_R2.fq.gz")
10
11 print("filterAndTrim")
12
13 for (i in seq_len(fwd)) {
14 ftout <- dada2::filterAndTrim(fwd[i], filt_fwd[i], rev[i], filt_rev[i])
15 b <- paste(strsplit(fwd[i], ".", fixed = TRUE)[[1]][1], "tab", sep = ".")
16 write.table(ftout, b, quote = FALSE, sep = "\t", col.names = NA)
17 }
18
19 # In the test only the 1st data set is used
20 t <- data.frame()
21 t <- rbind(t, ftout[1, ])
22 colnames(t) <- colnames(ftout)
23 rownames(t) <- rownames(ftout)[1]
24 write.table(t, "filterAndTrim.tab", quote = FALSE, sep = "\t", col.names = NA)
25
26 names(fwd) <- sample_names
27 names(rev) <- sample_names
28 names(filt_fwd) <- sample_names
29 names(filt_rev) <- sample_names
30
31 # Plot quality profile (just for one file, Galaxy compares with sim_size)
32 print("plots")
33 qp <- dada2::plotQualityProfile(fwd)
34 ggsave("qualityProfile_fwd.pdf", qp, width = 20, height = 15, units = c("cm"))
35 qp <- dada2::plotQualityProfile(rev)
36 ggsave("qualityProfile_rev.pdf", qp, width = 20, height = 15, units = c("cm"))
37 qp <- dada2::plotQualityProfile(fwd[1])
38 ggsave("qualityProfile.pdf", qp, width = 20, height = 15, units = c("cm"))
39
40 # Plot complexity (just for one file, Galaxy compares with sim_size)
41
42 cp <- dada2::plotComplexity(fwd)
43 ggsave("complexity_fwd.pdf", cp, width = 20, height = 15, units = c("cm"))
44 cp <- dada2::plotComplexity(rev)
45 ggsave("complexity_rev.pdf", cp, width = 20, height = 15, units = c("cm"))
46 cp <- dada2::plotComplexity(fwd[1])
47 ggsave("complexity.pdf", cp, width = 20, height = 15, units = c("cm"))
48
49
50 # learn Errors
51 print("learnErrors")
52 err_fwd <- dada2::learnErrors(filt_fwd)
53 saveRDS(err_fwd, file = "learnErrors_R1.Rdata")
54 plot <- dada2::plotErrors(err_fwd)
55 ggsave("learnErrors_R1.pdf", plot, width = 20, height = 15, units = c("cm"))
56
57 err_rev <- dada2::learnErrors(filt_rev)
58 saveRDS(err_rev, file = "learnErrors_R2.Rdata")
59 plot <- dada2::plotErrors(err_rev)
60 ggsave("learnErrors.pdf", plot, width = 20, height = 15, units = c("cm"))
61
62 # dada
63 print("dada")
64 dada_fwd <- dada2::dada(filt_fwd, err_fwd)
65 dada_rev <- dada2::dada(filt_rev, err_rev)
66 for (id in sample_names) {
67 saveRDS(dada_fwd[[id]], file = paste("dada_", id, "_R1.Rdata", sep = ""))
68 saveRDS(dada_rev[[id]], file = paste("dada_", id, "_R2.Rdata", sep = ""))
69 }
70
71 # merge pairs
72 print("mergePairs")
73 merged <- dada2::mergePairs(dada_fwd, filt_fwd, dada_rev, filt_rev)
74 for (id in sample_names) {
75 saveRDS(merged[[id]], file = paste("mergePairs_", id, ".Rdata", sep = ""))
76 }
77
78
79 # make sequence table
80 print("makeSequenceTable")
81 seqtab <- makeSequenceTable(merged)
82 write.table(t(seqtab), file = "makeSequenceTable.tab", quote = FALSE, sep = "\t", row.names = TRUE, col.names = NA)
83
84 reads_per_seqlen <- tapply(colSums(seqtab), factor(nchar(getSequences(seqtab))), sum)
85 df <- data.frame(length = as.numeric(names(reads_per_seqlen)), count = reads_per_seqlen)
86 pdf("makeSequenceTable.pdf")
87 ggplot(data = df, aes(x = length, y = count)) +
88 geom_col() +
89 theme_bw()
90 bequiet <- dev.off()
91
92 # remove bimera
93 print("removeBimera")
94 seqtab_nochim <- dada2::removeBimeraDenovo(seqtab)
95 write.table(t(seqtab), file = "removeBimeraDenovo.tab", quote = FALSE, sep = "\t", row.names = TRUE, col.names = NA)
96
97 # assign taxonomy/species
98 tl <- "Level1,Level2,Level3,Level4,Level5"
99 tl <- strsplit(tl, ",")[[1]]
100
101 set.seed(42)
102 print("assignTaxonomyAndSpecies")
103 taxa <- dada2::assignTaxonomy(seqtab_nochim, "reference.fa.gz", outputBootstraps = TRUE, taxLevels = tl, multithread = 1)
104
105 taxa$tax <- dada2::addSpecies(taxa$tax, "reference_species.fa.gz")
106 write.table(taxa$tax, file = "assignTaxonomyAddspecies.tab", quote = FALSE, sep = "\t", row.names = TRUE, col.names = NA)
107
108 write.table(taxa$boot, file = "assignTaxonomyAddspecies_boot.tab", quote = FALSE, sep = "\t", row.names = TRUE, col.names = NA)
109
110
111 ## Generate extra test data for parameter testing
112 print("alternatives")
113 dada2::filterAndTrim(fwd, c("filterAndTrim_single_F3D0_R1.fq.gz", "filterAndTrim_single_F3D141_R1.fq.gz"), rm.phix = TRUE, orient.fwd = "TACGG")
114
115 dada2::filterAndTrim(fwd, c("filterAndTrim_single_trimmers_F3D0_R1.fq.gz", "filterAndTrim_single_trimmers_F3D141_R1.fq.gz"), truncQ = 30, truncLen = 2, trimLeft = 150, trimRight = 2)
116
117 dada2::filterAndTrim(fwd, c("filterAndTrim_single_filters_F3D0_R1.fq.gz", "filterAndTrim_single_filters_F3D141_R1.fq.gz"), maxLen = 255, minLen = 60, maxN = 100, minQ = 13, maxEE = 1)
118
119
120 merged_nondef <- dada2::mergePairs(dada_fwd, filt_fwd, dada_rev, filt_rev, minOverlap = 8, maxMismatch = 1, justConcatenate = TRUE, trimOverhang = TRUE)
121 for (id in sample_names) {
122 saveRDS(merged_nondef[[id]], file = paste("mergePairs_", id, "_nondefault.Rdata", sep = ""))
123 }
124 rb_dada_fwd <- dada2::removeBimeraDenovo(dada_fwd[["F3D0_S188_L001"]])
125 write.table(rb_dada_fwd, file = "removeBimeraDenovo_F3D0_dada_uniques.tab", quote = FALSE, sep = "\t", row.names = TRUE, col.names = FALSE)
126
127 rb_merged <- dada2::removeBimeraDenovo(merged, method = "pooled")
128 saveRDS(rb_merged, file = "removeBimeraDenovo_F3D0_mergepairs.Rdata")
129
130 # SeqCounts
131 get_n <- function(x) {
132 sum(dada2::getUniques(x))
133 }
134
135 print("seqCounts ft")
136 samples <- list()
137 samples[["F3D0_S188_L001_R1_001.tab"]] <- read.table("F3D0_S188_L001_R1_001.tab", header = TRUE, sep = "\t", row.names = 1)
138 dname <- "filter"
139 tdf <- samples[["F3D0_S188_L001_R1_001.tab"]]
140 names(tdf) <- paste(dname, names(tdf))
141 tdf <- cbind(data.frame(samples = names(samples)), tdf)
142 write.table(tdf, "seqCounts_filter.tab", quote = FALSE, sep = "\t", row.names = FALSE, col.names = TRUE)
143
144 samples <- list()
145 samples[["F3D0_S188_L001_R1_001.tab"]] <- read.table("F3D0_S188_L001_R1_001.tab", header = TRUE, sep = "\t", row.names = 1)
146 samples[["F3D141_S207_L001_R1_001.tab"]] <- read.table("F3D141_S207_L001_R1_001.tab", header = TRUE, sep = "\t", row.names = 1)
147 dname <- "filter"
148 tdf <- samples[["F3D0_S188_L001_R1_001.tab"]]
149 tdf <- rbind(tdf, samples[["F3D141_S207_L001_R1_001.tab"]])
150 names(tdf) <- paste(dname, names(tdf))
151 tdf <- cbind(data.frame(samples = names(samples)), tdf)
152 write.table(tdf, "seqCounts_filter_both.tab", quote = FALSE, sep = "\t", row.names = FALSE, col.names = TRUE)
153
154 print("seqCounts dada")
155 samples <- list()
156 samples[["dada_F3D0_S188_L001_R1.Rdata"]] <- readRDS("dada_F3D0_S188_L001_R1.Rdata")
157 samples[["dada_F3D141_S207_L001_R1.Rdata"]] <- readRDS("dada_F3D141_S207_L001_R1.Rdata")
158 dname <- "dadaF"
159 tdf <- data.frame(samples = names(samples))
160 tdf[[dname]] <- sapply(samples, get_n)
161 write.table(tdf, "seqCounts_dadaF.tab", quote = FALSE, sep = "\t", row.names = FALSE, col.names = TRUE)
162
163 print("seqCounts mp")
164 samples <- list()
165 samples[["mergePairs_F3D0_S188_L001.Rdata"]] <- readRDS("mergePairs_F3D0_S188_L001.Rdata")
166 samples[["mergePairs_F3D141_S207_L001.Rdata"]] <- readRDS("mergePairs_F3D141_S207_L001.Rdata")
167 dname <- "merge"
168 tdf <- data.frame(samples = names(samples))
169 tdf[[dname]] <- sapply(samples, get_n)
170 write.table(tdf, "seqCounts_merge.tab", quote = FALSE, sep = "\t", row.names = FALSE, col.names = TRUE)
171
172 print("seqCounts st")
173 samples <- list()
174 samples <- t(as.matrix(read.table("makeSequenceTable.tab", header = TRUE, sep = "\t", row.names = 1)))
175 dname <- "seqtab"
176 tdf <- data.frame(samples = row.names(samples))
177 tdf[[dname]] <- rowSums(samples)
178 write.table(tdf, "seqCounts_seqtab.tab", quote = FALSE, sep = "\t", row.names = FALSE, col.names = TRUE)
179
180 print("seqCounts rb")
181 samples <- list()
182 samples <- t(as.matrix(read.table("removeBimeraDenovo.tab", header = TRUE, sep = "\t", row.names = 1)))
183 dname <- "nochim"
184 tdf <- data.frame(samples = row.names(samples))
185 tdf[[dname]] <- rowSums(samples)
186 write.table(tdf, "seqCounts_nochim.tab", quote = FALSE, sep = "\t", row.names = FALSE, col.names = TRUE)