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annotate calisp.xml @ 0:d158a7909193 draft default tip

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planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tools/calisp commit 060699366b6dd19ad6c3ef3f332f63cc55d75dce
author galaxyp
date Thu, 01 Jun 2023 08:33:58 +0000
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d158a7909193 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tools/calisp commit 060699366b6dd19ad6c3ef3f332f63cc55d75dce
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1 <tool id="calisp" name="calisp" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="21.05">
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2 <description>Estimate isotopic composition of peptides from proteomics mass spectrometry data</description>
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3 <macros>
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4 <token name="@TOOL_VERSION@">3.0.10</token>
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5 <token name="@VERSION_SUFFIX@">0</token>
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6 <token name="@CALISP_REPO@">https://raw.githubusercontent.com/kinestetika/Calisp/208d495674e2b52fe56cf23457c833d1c2527242</token>
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7 <xml name="input_macro" tokens="multiple">
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8 <!-- According to readme mzid input is not yet implented -->
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9 </xml>
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10 </macros>
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11 <requirements>
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12 <requirement type="package" version="@TOOL_VERSION@">calisp</requirement>
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13 </requirements>
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14 <command detect_errors="aggressive"><![CDATA[
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15 #import re
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16
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17 mkdir -p spectra &&
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18 #set escaped_specs = re.sub('[^\w\-\.,:]', '_', str($spectrum_file.element_identifier))
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19 ln -s '$spectrum_file' spectra/'$escaped_specs' &&
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20
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21 mkdir -p psms &&
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22 #set escaped_peps = re.sub('[^\w\-\.,:]', '_', str($peptide_file.element_identifier))
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23 ln -s '$peptide_file' psms/'$escaped_peps' &&
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24
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25 calisp
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26 --spectrum_file spectra/
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27 --peptide_file psms/
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28 --output_file calisp-output/
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29 --mass_accuracy $mass_accuracy
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30 --bin_delimiter '$bin_delimiter'
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31 --threads "\${GALAXY_SLOTS:-1}"
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32 --isotope $isotope
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33 $compute_clumps &&
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34 '$__tool_directory__/feather2tsv.py' --calisp_output calisp-output/
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35 ]]></command>
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36 <inputs>
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37 <param argument="--spectrum_file" type="data" multiple="false" format="mzml" label="Spectrum file"/>
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38 <param argument="--peptide_file" type="data" multiple="false" format="tabular" label="Peptide file" help="Psm file" />
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39 <param argument="--mass_accuracy" type="float" value="10" label="Mass accuracy" help="The maximum mass difference between theoretical mass and experimental mass of a peptide" />
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40 <param argument="--bin_delimiter" type="text" value="_" label="Bin delimiter" help="For metagenomic data, the delimiter that separates the bin ID from the protein ID (default: &quot;_&quot;). Use &quot;-&quot; to ignore bins ID entirely.">
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41 <sanitizer invalid_char="">
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42 <valid initial="string.ascii_letters,string.digits">
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43 <add value="_" />
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44 <add value="-" />
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45 <add value=":" />
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46 </valid>
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47 </sanitizer>
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48 </param>
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49 <param argument="--isotope" type="select" label="Target isotope">
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50 <option value="13C" selected="true">13C</option>
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51 <option value="14C">14C</option>
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52 <option value="15N">15N</option>
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53 <option value="17O">17O</option>
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54 <option value="18O">18O</option>
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55 <option value="2H">2H</option>
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56 <option value="3H">3H</option>
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57 <option value="33S">33S</option>
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58 <option value="34S">34S</option>
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59 <option value="36S">36S</option>
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60 </param>
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61 <param argument="--compute_clumps" type="boolean" truevalue="--compute_clumps" falsevalue="" checked="false" label="Compute clumps" help="To compute clumpiness of carbon assimilation. Only use when samples are labeled tosaturation. Estimation of clumpiness takes much additional time." />
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62 </inputs>
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63 <outputs>
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64 <collection name="output" type="list">
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65 <discover_datasets pattern="(?P&lt;designation&gt;.*)\.tsv" format="tabular" directory="calisp-output"/>
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66 </collection>
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67 </outputs>
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68 <tests>
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69 <!-- TODO test data to large, avilable from here: https://github.com/kinestetika/Calisp/tree/master/test
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70 if possible inlcude via location in the future
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71 <test expect_num_outputs="1">
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72 <param name="spectrum_file" value="calisp_test_data.mzML" ftype="mzml"/>
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73 <param name="peptide_file" value="calisp_test_data_TargetPeptideSpectrumMatch.txt" ftype="tabular"/>
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74 <output_collection name="output" count="1">
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75 <element name="calisp_test_data">
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76 <assert_contents>
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77 <has_text text="experiment"/>
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78 <has_text text="MKH_260min_1800ng"/>
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79 <has_text text="HOMO"/>
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80 <has_text text="P13645"/>
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81 <has_text text="NHEEEMKDLR"/>
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82 <has_text text="Oxidation"/>
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83 <has_n_columns n="85"/>
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84 <has_n_lines n="24"/>
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85 </assert_contents>
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86 </element>
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87 </output_collection>
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88 </test>
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89 -->
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90 </tests>
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91 <help><![CDATA[
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92 Calisp (Calgary approach to isotopes in proteomics) is a program that estimates
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93 isotopic composition (e.g. 13C/12C, delta13C, 15N/14N etc) of peptides from
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94 proteomics mass spectrometry data. Input data consist of mzML files and files
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95 with peptide spectrum matches.
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96
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97 Calisp was originally developed in Java. This Galaxy tool uses the python
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98 reimplementation https://github.com/kinestetika/Calisp.
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99 Note that, in contrast to the Java version the python reimplementation does
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100 not use ``mcl`` .
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101 Compared to Java versions of calisp, the workflow has been simplified.
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102 Calisp does not filter out any isotopic patterns, or adds up isotopic
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103 patterns to reduce noise - like the Java version does. It simply estimates the
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104 ratio for the target isotopes (e.g. 13C/12C) for every isotopic pattern it can
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105 subsample. It estimates this ratio based on neutron abundance and using fast
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106 fourier transforms. The former applies to stable isotope probing experiments.
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107 The latter applies to natural abundances, or to isotope probing experiments with
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108 very little added label (e.g. using substrates with <1% additional 13C). The
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109 motivation for omitting filtering is that keeping all subsampled isotopic
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110 patterns, including bad ones, will enable training of machine learning
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111 classifiers. Also, because it was shown that the median provides better
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112 estimates for species in microbial communities than the mean, adding up isotopic
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113 patterns to improve precision has lost its purpose. There is more power (and
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114 sensitivity) in numbers.
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115
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116 Because no data are filtered out and no isotopic patterns get added up,
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117 calisp analyzes at least ten times as many isotopic patterns compared to the
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118 Java version. That means calisp.py is about ten times slower, it takes about
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119 5-10 min per .mzML file on a Desktop computer. For natural
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120 abundance data, it works well to only use those spectra that have a FFT fitting
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121 error ("error_fft") of less than 0.001. Note that this threshold is less
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122 stringent then thew one used by the java program.
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123
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124 Input
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125 =====
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126
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127 Calisp needs two inputs: a spectra file in mzML format and tabular peptipe file (PSM).
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128 The PSM file contains a column "Spectrum File" that links the peptides to the
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129 original spectra files. The mzML files are identified by the run id
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130 information stored in the mzML files or the file name.
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131 In order to make the association via the file name work in Galaxy one can either
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132
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133 - use collections where the element identifiers are equal to the data in the column
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134 - make sure that dataset names are equal to the data in this column
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135
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136 Output table
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137 ============
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138
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139 Each row contains one isotopic pattern, defined by the following columns:
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140
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141 ========================================== ===================
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142 Header name Content
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143 ========================================== ===================
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144 experiment filename of the peptide spectrum match (psm) file
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145 ms_run filename of the .mzml file
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146 bins bin/mag ids, separated by commas. Calisp expects the protein ids in the psm file to consist of two parts, separated by a delimiter (_ by default). The first part is the bin/mag id, the second part the protein id
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147 proteins the ids of the proteins associated with the pattern (without the bin id)
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148 peptide the aminoacid sequence of the peptide
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149 peptide_mass the mass of the peptide
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150 C # of carbon atoms in the peptide
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151 N # of nitrogen atoms in the peptide
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152 O # of oxygen atoms in the peptide
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153 H # of hydrogen atoms in the peptide
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154 S # of sulfur atoms in the peptide
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155 psm_id psm id
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156 psm_mz psm m over z
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157 psm_charge psm charge
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158 psm_neutrons number of neutrons inferred from custom 'neutron' modifications
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159 psm_rank rank of the psm
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160 psm_precursor_id id of the ms1 spectrum that was the source of the psm
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161 psm_precursor_mz mass over charge of the precursor of the psm
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162 pattern_charge charge of the pattern
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163 pattern_precursor_id id of the ms1 spectrum that was the source of the pattern
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164 pattern_total_intensity total intensity of the pattern
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165 pattern_peak_count # of peaks in the pattern
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166 pattern_median_peak_spacing medium mass difference between a pattern's peaks
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167 spectrum_mass_irregularity a measure for the standard deviation in the mass difference between a pattern's peaks
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168 ratio_na the estimated isotope ratio inferred from neutron abundance (sip experiments)
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169 ratio_fft the estimated isotope ratio inferred by the fft method (natural isotope abundances)
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170 error_fft the remaining error after fitting the pattern with fft
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171 error_clumpy the remaining error after fitting the pattern with the clumpy carbon method
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172 flag_peptide_contains_sulfur true if peptide contains sulfur
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173 flag_peptide_has_modifications true if peptide has no modifications
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174 flag_peptide_assigned_to_multiple_bins true if peptide is associated with multiple proteins from different bins/mags
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175 flag_peptide_assigned_to_multiple_proteins true if peptide is associated with multiple proteins
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176 flag_peptide_mass_and_elements_undefined true if peptide has unknown mass and elemental composition
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177 flag_psm_has_low_confidence true if psm was flagged as having low confidence (peptide identity uncertain)
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178 flag_psm_is_ambiguous true if psm could not be assigned with certainty
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179 flag_pattern_is_contaminated true if multiple patterns have one or more shared peaks
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180 flag_pattern_is_wobbly true if pattern_median_peak_spacing exceeds a treshold
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181 flag_peak_at_minus_one_pos true if a peak was detected immediately before the monoisotopic peak, could indicate overlap with another pattern
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182 i0 - i19 the intensities of the first 20 peaks of the pattern
d158a7909193 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tools/calisp commit 060699366b6dd19ad6c3ef3f332f63cc55d75dce
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183 m0 - m19 the masses of the first 20 peaks of the pattern
d158a7909193 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tools/calisp commit 060699366b6dd19ad6c3ef3f332f63cc55d75dce
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184 c1 - c6 contributions of clumps of 1-6 carbon to ratio_na. These are the outcomes of the clumpy carbon model. These results are only meaningful if the biomass was labeled to saturation.
d158a7909193 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tools/calisp commit 060699366b6dd19ad6c3ef3f332f63cc55d75dce
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185 ========================================== ===================
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186 ]]></help>
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187 <citations>
d158a7909193 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tools/calisp commit 060699366b6dd19ad6c3ef3f332f63cc55d75dce
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188 <citation type="doi">10.1186/s40168-022-01454-1</citation>
d158a7909193 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tools/calisp commit 060699366b6dd19ad6c3ef3f332f63cc55d75dce
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189 <citation type="doi">10.1073/pnas.1722325115</citation>
d158a7909193 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tools/calisp commit 060699366b6dd19ad6c3ef3f332f63cc55d75dce
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190 <citation type="doi">10.1101/2021.03.29.437612</citation>
d158a7909193 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tools/calisp commit 060699366b6dd19ad6c3ef3f332f63cc55d75dce
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191 <citation type="doi">10.1093/bioinformatics/bty046</citation>
d158a7909193 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tools/calisp commit 060699366b6dd19ad6c3ef3f332f63cc55d75dce
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192 </citations>
d158a7909193 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tools/calisp commit 060699366b6dd19ad6c3ef3f332f63cc55d75dce
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193 </tool>