Previous changeset 2:52ac6fde9a5b (2020-08-14) Next changeset 4:593839e1f2c3 (2021-02-25) |
Commit message:
"planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msstats commit ad490a2f231f5ee1b6db160c117181e693ea1079" |
modified:
msstats.xml test-data/MSstats ProfilePlot.pdf test-data/QC_plot.pdf test-data/condition_plot.pdf test-data/profile_wsum_plot.pdf test-data/qq_plot.pdf test-data/residual_plot.pdf test-data/residualplot.pdf test-data/volcanoplot.pdf |
added:
test-data/Comparison_plot_skyline.pdf test-data/Heatmap_openms.pdf test-data/Profile_plot_skyline.pdf test-data/Volcano_plot_skyline.pdf test-data/comparison_list_skyline.tabular test-data/comparison_matrix_skyline.tabular test-data/condition_plot_openms.pdf test-data/openms_comparisonmatrix.tabular test-data/openms_input.tabular test-data/skyline_annotations.csv test-data/skyline_input_first100.csv |
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diff -r 52ac6fde9a5b -r 8212e342e482 msstats.xml --- a/msstats.xml Fri Aug 14 12:19:14 2020 -0400 +++ b/msstats.xml Thu Jan 28 20:48:40 2021 +0000 |
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b'@@ -1,18 +1,18 @@\n <tool id="msstats" name="MSstats" version="@VERSION@.0">\n <description>statistical relative protein significance analysis in DDA, SRM and DIA Mass Spectrometry</description>\n <macros>\n- <token name="@VERSION@">3.20.1</token>\n+ <token name="@VERSION@">3.22.0</token>\n <xml name="useUniquePeptide">\n- <param name="useUniquePeptide" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true" label="remove peptides that are assigned for more than one proteins" help="We assume to use unique peptide for each protein"/>\n+ <param name="useUniquePeptide" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true" label="Remove peptides that are assigned for more than one proteins"/>\n </xml>\n <xml name="summaryforMultipleRows">\n- <param name="summaryforMultipleRows" type="select" label="Summary for MultipleRows" help="summaryforMultipleRows - when there are multiple measurements for certain feature and certain run, use highest or sum of all">\n+ <param name="summaryforMultipleRows" type="select" label="Summary for MultipleRows" help="When there are multiple measurements for certain feature and certain run, use highest or sum of all">\n <option value="max" selected="true">max</option>\n <option value="sum">sum</option>\n </param>\n </xml>\n <xml name="fewMeasurements">\n- <param name="fewMeasurements" type="select" label="Remove the features that have 1 or 2 measurements across runs" help="(fewMeasurements)">\n+ <param name="fewMeasurements" type="select" label="Features with few measurements " help="Remove the features that have 1 or 2 measurements across runs or keep all features or keep all features (the latter could give an error in fitting the statistical model)">\n <option value="remove" selected="true">remove</option>\n <option value="keep">keep</option>\n </param>\n@@ -32,6 +32,7 @@\n ]]></command>\n <configfiles>\n <configfile name="msstats_script"><![CDATA[\n+\n library(\'MSstats\', warn.conflicts = F, quietly = T, verbose = F)\n \n #if $input.input_src == \'MSstats\'\n@@ -51,12 +52,12 @@\n \\# Read in annotation including condition and biological replicates per run.\n \\# Users should make this annotation file. It is not the output from MaxQuant.\n #if $input.annotation.is_of_type(\'csv\')\n-annot <- read.csv("$input.annotation", header=TRUE)\n+\tannot <- read.csv("$input.annotation", header=TRUE)\n #else\n-annot <- read.table("$input.annotation", sep="\\t", header=TRUE)\n+\tannot <- read.table("$input.annotation", sep="\\t", header=TRUE)\n #end if\n \n-raw <- MaxQtoMSstatsFormat(evidence=mq_evidence, \n+raw <- MaxQtoMSstatsFormat(evidence=mq_evidence,\n proteinGroups=mq_proteinGroups,\n annotation=annot, \n proteinID="$input.proteinID",\n@@ -69,35 +70,41 @@\n \n #elif $input.input_src == \'OpenMS\'\n \n- #if $input.evidence.is_of_type(\'csv\')\n-input <- read.csv("$input.evidence", header=TRUE)\n+ #if $input.openms_input.is_of_type(\'csv\')\n+\tinput <- read.csv("$input.openms_input", header=TRUE)\n #else\n-input <- read.table("$input.evidence", sep="\\t", header=TRUE)\n- #end if\n- #if $input.annotation.is_of_type(\'csv\')\n-annot <- read.csv("$input.annotation", header=TRUE)\n- #else\n-annot <- read.table("$input.annotation", sep="\\t", header=TRUE)\n+\tinput <- read.table("$input.openms_input", sep="\\t", header=TRUE)\n #end if\n \n-raw <- OpenMStoMSstatsFormat(input,\n+ #if $input.annotation:\n+ #if $input.annotation.is_of_type(\'csv\')\n+\t annot <- read.csv("$input.annotation", header=TRUE)\n+ #else\n+\t annot <- read.table("$input.annotation", sep="\\t", header=TRUE)\n+ #end if\n+ #end if\n+\n+ raw <- OpenMStoMSstatsFormat(input,\n+ #if $input.annotation:\n annotation=annot,'..b'for inference in corresponding protein and comparison,for example,OneConditionMissing or CompleteMissing. If one of condition for compariosn is completely missing, it would flag with OneConditionMissing with adj.pvalue=0 and log2FC=Inf or -Inf even though pvalue=NA. For example, if you want to compare \xe2\x80\x98condition1-condition2\xe2\x80\x99, but condition2 has complete missing, log2FC=Inf and adj.pvalue=0. SE,Tvalue, and pvalue will be NA. If you want to compare \xe2\x80\x98conditions - condition2\xe2\x80\x99, but condition1 has complete missing, then log2FC=-Inf and adj.pvalue=0. But, please be careful for using this log2FC and adj.pvalue.\n+\n+ - MSstats ModelQC - summary statistics per run and protein (tabular)\n+\n+ - MSstats QQPlot - one QQplot per protein (pdf)\n+\n+ - Normal quantile-quantile plots for each protein, taking as input the results of model fitting and testing in groupComparison. Only large deviations of transition intensities from the straight line are problematic and indicate that the assumption of the normal distribution of the measurement errors may not hold.\n+\n+ - MSstats ResiudalPlot - one residual plot per protein (pdf)\n+\n+ - Residual plot shows variance of the residuals that is associated with the mean feature intensity. Any specific pattern, such as increasing or decreasing by predicted abundance, is problematic and indicates that the assumption of constant variance of the measurement error may not hold.\n+\n+ - MSstats VolcanoPlot - one volcano plot per comparison (pdf)\n+\n+ - Visualizes the outcome of one comparison between conditions for all the proteins, and combine the information on statistical and practical significance. The y-axis displays the FDR-adjusted p-values on the negative log10 scale, representing statistical significance. The horizontal dashed line shows the FDR cutoff. The points above the FDR cutoff line are statistically significant proteins that are differentially abundant across conditions. These points are colored in red and blue for upregulated and downregulated proteins, respectively. The x-axis is the model-based estimate of fold change on log scale and represents practical significance. It is possible to specify a practical significance cutoff based on the estimate of fold change in addition to the statistical significance cutoff. If the fold change cutoff is specified, the points above the horizontal cutoff line but within the vertical cutoff line will be considered as not differentially abundant (and will be colored in black).\n+\n+ - MSstats Heatmap - needs at least 2 comparisons, one heatmap for all proteins and comparisons (pdf)\n+\n+ - Illustrates the patterns of up- and down-regulation of proteins in several comparisons. Columns in the heatmaps are comparison of conditions assigned in contrast matrix, and rows are proteins. The heatmaps display signed FDR-adjusted p-values of the tests, colored in red/blue for significantly up-/down-regulated proteins, while taking into account the specified FDR cutoff and the additional optional fold change cutoff. Brighter colors indicate stronger evidence in favor of differential abundance. Black color represents proteins that are not significantly differentially abundant.\n+\n+ - MSstats ComparisonPlot - log2 intensity range for each protein and comparison (pdf)\n+\n+ - Illustrates model-based estimates of log-fold changes, and the associated uncertainty, in several comparisons of conditions for one protein. X-axis is the comparison of interest. Y-axis is the log fold change. The dots are the model-based estimates of log-fold change, and the error bars are the model-based 95% confidence intervals. For simplicity, the confidence intervals are adjusted for multiple comparisons within protein only, using the Bonferroni approach. For proteins with N comparisons, the individual confidence intervals are at the level of 1-sig/N.\n \n For additional help please visit the `MSstats documentation <http://msstats.org/msstats-2/>`_\n \n' |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/Comparison_plot_skyline.pdf |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/Heatmap_openms.pdf |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/MSstats ProfilePlot.pdf |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/Profile_plot_skyline.pdf |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/QC_plot.pdf |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/Volcano_plot_skyline.pdf |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/comparison_list_skyline.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/comparison_list_skyline.tabular Thu Jan 28 20:48:40 2021 +0000 |
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@@ -0,0 +1,1 @@ +c1-c2 |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/comparison_matrix_skyline.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/comparison_matrix_skyline.tabular Thu Jan 28 20:48:40 2021 +0000 |
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@@ -0,0 +1,4 @@ +name Condition1 Condition2 Condition3 Condition4 Condition5 +c1-c2 1 -1 0 0 0 +c1-c4 1 0 0 -1 0 +c5-c3 0 0 -1 0 1 |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/condition_plot.pdf |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/condition_plot_openms.pdf |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/openms_comparisonmatrix.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/openms_comparisonmatrix.tabular Thu Jan 28 20:48:40 2021 +0000 |
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@@ -0,0 +1,3 @@ +name c1 c2 c3 c4 +c1-c2 1 -2 0 0 +c3-c4 0 0 1 -1 |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/openms_input.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/openms_input.tabular Thu Jan 28 20:48:40 2021 +0000 |
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@@ -0,0 +1,100 @@ +ProteinName PeptideSequence PrecursorCharge FragmentIon ProductCharge IsotopeLabelType Condition BioReplicate Run Intensity +sp|P09938|RIR2_YEAST AAADALSDLEIK 2 NA 0 L c1 1 1 391797000 +sp|P09938|RIR2_YEAST AAADALSDLEIK 2 NA 0 L c4 4 10 103656000 +sp|P09938|RIR2_YEAST AAADALSDLEIK 2 NA 0 L c4 4 11 361107000 +sp|P09938|RIR2_YEAST AAADALSDLEIK 2 NA 0 L c1 1 2 456756000 +sp|P09938|RIR2_YEAST AAADALSDLEIK 2 NA 0 L c1 1 3 389268000 +sp|P09938|RIR2_YEAST AAADALSDLEIK 2 NA 0 L c2 2 4 433488000 +sp|P09938|RIR2_YEAST AAADALSDLEIK 2 NA 0 L c2 2 5 371698000 +sp|P09938|RIR2_YEAST AAADALSDLEIK 2 NA 0 L c2 2 6 403492000 +sp|P09938|RIR2_YEAST AAADALSDLEIK 2 NA 0 L c3 3 7 366753000 +sp|P09938|RIR2_YEAST AAADALSDLEIK 2 NA 0 L c3 3 8 509756000 +sp|P09938|RIR2_YEAST AAADALSDLEIK 2 NA 0 L c3 3 9 74323100 +sp|P09938|RIR2_YEAST AAADALSDLEIKDSK 2 NA 0 L c1 1 1 19165300 +sp|P09938|RIR2_YEAST AAADALSDLEIKDSK 2 NA 0 L c4 4 10 20805400 +sp|P09938|RIR2_YEAST AAADALSDLEIKDSK 3 NA 0 L c4 4 12 44146400 +sp|P09938|RIR2_YEAST AAADALSDLEIKDSK 3 NA 0 L c1 1 2 67209100 +sp|P09938|RIR2_YEAST AAADALSDLEIKDSK 3 NA 0 L c1 1 3 53246300 +sp|P09938|RIR2_YEAST AAADALSDLEIKDSK 2 NA 0 L c2 2 4 25024400 +sp|P09938|RIR2_YEAST AAADALSDLEIKDSK 3 NA 0 L c2 2 5 66294800 +sp|P09938|RIR2_YEAST AAADALSDLEIKDSK 3 NA 0 L c2 2 6 54911100 +sp|P09938|RIR2_YEAST AAADALSDLEIKDSK 2 NA 0 L c3 3 7 22981500 +sp|P09938|RIR2_YEAST AAADALSDLEIKDSK 3 NA 0 L c3 3 8 78869100 +sp|P09938|RIR2_YEAST AAADALSDLEIKDSK 3 NA 0 L c3 3 9 43745000 +sp|P53075|SHE10_YEAST AAAEEFQR 2 NA 0 L c1 1 1 58438900 +sp|P53075|SHE10_YEAST AAAEEFQR 2 NA 0 L c4 4 10 49099300 +sp|P53075|SHE10_YEAST AAAEEFQR 2 NA 0 L c4 4 11 73350000 +sp|P53075|SHE10_YEAST AAAEEFQR 2 NA 0 L c4 4 12 52364300 +sp|P53075|SHE10_YEAST AAAEEFQR 2 NA 0 L c1 1 2 82639800 +sp|P53075|SHE10_YEAST AAAEEFQR 2 NA 0 L c1 1 3 95647200 +sp|P53075|SHE10_YEAST AAAEEFQR 2 NA 0 L c2 2 4 25141100 +sp|P53075|SHE10_YEAST AAAEEFQR 2 NA 0 L c2 2 5 59801200 +sp|P53075|SHE10_YEAST AAAEEFQR 2 NA 0 L c2 2 6 59312000 +sp|P53075|SHE10_YEAST AAAEEFQR 2 NA 0 L c3 3 7 50242100 +sp|P53075|SHE10_YEAST AAAEEFQR 2 NA 0 L c3 3 8 53652600 +sp|P53075|SHE10_YEAST AAAEEFQR 2 NA 0 L c3 3 9 100298000 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 3 NA 0 L c1 1 1 155247000 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 3 NA 0 L c4 4 10 172277000 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 3 NA 0 L c4 4 11 174546000 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 3 NA 0 L c4 4 12 147823000 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 3 NA 0 L c1 1 2 202730000 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 3 NA 0 L c1 1 3 133993000 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 3 NA 0 L c2 2 4 140896000 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 3 NA 0 L c2 2 5 187559000 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 2 NA 0 L c2 2 6 14695600 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 3 NA 0 L c2 2 6 151945000 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 3 NA 0 L c3 3 7 124059000 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 3 NA 0 L c3 3 8 186091000 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 2 NA 0 L c3 3 9 14626600 +sp|P15180|SYKC_YEAST AAAEGVANLHLDEATGEMVSK 3 NA 0 L c3 3 9 165157000 +sp|Q99186|AP2M_YEAST AAAGSVLLEDCK 2 NA 0 L c2 2 6 9275840 +sp|Q99186|AP2M_YEAST AAAGSVLLEDCK 2 NA 0 L c3 3 9 8861320 +sp|P05030|PMA1_YEAST AAALVNK 2 NA 0 L c1 1 1 563809000 +sp|P05030|PMA1_YEAST AAALVNK 2 NA 0 L c4 4 10 438937000 +sp|P05030|PMA1_YEAST AAALVNK 2 NA 0 L c4 4 11 659057000 +sp|P05030|PMA1_YEAST AAALVNK 2 NA 0 L c4 4 12 1139830000 +sp|P05030|PMA1_YEAST AAALVNK 2 NA 0 L c1 1 2 630880000 +sp|P05030|PMA1_YEAST AAALVNK 2 NA 0 L c1 1 3 1316880000 +sp|P05030|PMA1_YEAST AAALVNK 2 NA 0 L c2 2 4 541485000 +sp|P05030|PMA1_YEAST AAALVNK 2 NA 0 L c2 2 5 1100480000 +sp|P05030|PMA1_YEAST AAALVNK 2 NA 0 L c2 2 6 778427000 +sp|P05030|PMA1_YEAST AAALVNK 2 NA 0 L c3 3 7 651901000 +sp|P05030|PMA1_YEAST AAALVNK 2 NA 0 L c3 3 8 485655000 +sp|P05030|PMA1_YEAST AAALVNK 2 NA 0 L c3 3 9 1333400000 +sp|P18759|SEC18_YEAST AAANHTPPDMTNMDTR 3 NA 0 L c2 2 5 21203800 +sp|P18759|SEC18_YEAST AAANHTPPDMTNMDTR 3 NA 0 L c2 2 6 18526700 +sp|Q06505|IWS1_YEAST AAAPAQTTTDYK 2 NA 0 L c1 1 1 38302100 +sp|Q06505|IWS1_YEAST AAAPAQTTTDYK 2 NA 0 L c4 4 10 68752200 +sp|Q06505|IWS1_YEAST AAAPAQTTTDYK 2 NA 0 L c4 4 11 66311100 +sp|Q06505|IWS1_YEAST AAAPAQTTTDYK 2 NA 0 L c4 4 12 81202000 +sp|Q06505|IWS1_YEAST AAAPAQTTTDYK 2 NA 0 L c1 1 2 35729900 +sp|Q06505|IWS1_YEAST AAAPAQTTTDYK 2 NA 0 L c1 1 3 72558100 +sp|Q06505|IWS1_YEAST AAAPAQTTTDYK 2 NA 0 L c2 2 4 73702900 +sp|Q06505|IWS1_YEAST AAAPAQTTTDYK 2 NA 0 L c2 2 5 43056300 +sp|Q06505|IWS1_YEAST AAAPAQTTTDYK 2 NA 0 L c2 2 6 83497000 +sp|Q06505|IWS1_YEAST AAAPAQTTTDYK 2 NA 0 L c3 3 7 64895300 +sp|Q06505|IWS1_YEAST AAAPAQTTTDYK 2 NA 0 L c3 3 8 68602200 +sp|Q06505|IWS1_YEAST AAAPAQTTTDYK 2 NA 0 L c3 3 9 84040800 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 2 NA 0 L c1 1 1 26375400 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 2 NA 0 L c4 4 10 22316600 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 3 NA 0 L c4 4 10 19949800 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 2 NA 0 L c4 4 11 24275300 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 3 NA 0 L c4 4 11 12153800 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 2 NA 0 L c4 4 12 20450400 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 3 NA 0 L c4 4 12 46088700 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 2 NA 0 L c1 1 2 28279700 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 2 NA 0 L c1 1 3 22167900 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 3 NA 0 L c1 1 3 51390900 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 2 NA 0 L c2 2 4 22536100 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 3 NA 0 L c2 2 4 9078210 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 2 NA 0 L c2 2 5 31947800 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 3 NA 0 L c2 2 5 27529200 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 2 NA 0 L c2 2 6 23376500 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 3 NA 0 L c2 2 6 21282400 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 2 NA 0 L c3 3 7 25548800 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 2 NA 0 L c3 3 8 34622600 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 2 NA 0 L c3 3 9 34296700 +sp|Q04697|GSF2_YEAST AAAPGIQLVAGEGFQSPLEDR 3 NA 0 L c3 3 9 66102400 +sp|P09457|ATPO_YEAST AAAPPPVR 2 NA 0 L c1 1 1 102933000 +sp|P09457|ATPO_YEAST AAAPPPVR 2 NA 0 L c4 4 10 59641400 +sp|P09457|ATPO_YEAST AAAPPPVR 2 NA 0 L c4 4 11 90159100 |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/skyline_annotations.csv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/skyline_annotations.csv Thu Jan 28 20:48:40 2021 +0000 |
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@@ -0,0 +1,16 @@ +Run,Condition,BioReplicate +121219_S_CCES_01_01_LysC_Try_1to10_Mixt_1_1.raw,Condition1,1 +121219_S_CCES_01_02_LysC_Try_1to10_Mixt_1_2.raw,Condition1,1 +121219_S_CCES_01_03_LysC_Try_1to10_Mixt_1_3.raw,Condition1,1 +121219_S_CCES_01_04_LysC_Try_1to10_Mixt_2_1.raw,Condition2,2 +121219_S_CCES_01_05_LysC_Try_1to10_Mixt_2_2.raw,Condition2,2 +121219_S_CCES_01_06_LysC_Try_1to10_Mixt_2_3.raw,Condition2,2 +121219_S_CCES_01_07_LysC_Try_1to10_Mixt_3_1.raw,Condition3,3 +121219_S_CCES_01_08_LysC_Try_1to10_Mixt_3_2.raw,Condition3,3 +121219_S_CCES_01_09_LysC_Try_1to10_Mixt_3_3.raw,Condition3,3 +121219_S_CCES_01_10_LysC_Try_1to10_Mixt_4_1.raw,Condition4,4 +121219_S_CCES_01_11_LysC_Try_1to10_Mixt_4_2.raw,Condition4,4 +121219_S_CCES_01_12_LysC_Try_1to10_Mixt_4_3.raw,Condition4,4 +121219_S_CCES_01_13_LysC_Try_1to10_Mixt_5_1.raw,Condition5,5 +121219_S_CCES_01_14_LysC_Try_1to10_Mixt_5_2.raw,Condition5,5 +121219_S_CCES_01_15_LysC_Try_1to10_Mixt_5_3.raw,Condition5,5 \ No newline at end of file |
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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/skyline_input_first100.csv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/skyline_input_first100.csv Thu Jan 28 20:48:40 2021 +0000 |
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b'@@ -0,0 +1,100 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diff -r 52ac6fde9a5b -r 8212e342e482 test-data/volcanoplot.pdf |
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Binary file test-data/volcanoplot.pdf has changed |