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annotate tin.xml @ 62:473382134e56 draft

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/rseqc commit ccb6f7edba5492f4750ef8a59c4f91eb67fdbbec
author iuc
date Wed, 22 Feb 2023 15:06:01 +0000
parents 5968573462fa
children 27e16a30667a
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1 <tool id="rseqc_tin" name="Transcript Integrity Number" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@GALAXY_VERSION@">
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2 <description>
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3 evaluates RNA integrity at a transcript level
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4 </description>
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5 <macros>
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6 <import>rseqc_macros.xml</import>
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7 </macros>
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8 <expand macro="bio_tools"/>
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10 <expand macro="requirements" />
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12 <expand macro="stdio" />
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14 <version_command><![CDATA[tin.py --version]]></version_command>
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16 <!-- Generate output files here because tin.py removes all instances of "bam"
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17 in the filename -->
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18 <command><![CDATA[
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19 #import re
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20 #set $input_list = []
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21 #for $i, $input in enumerate($input):
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22 #set $safename = re.sub('[^\w\-_]', '_', $input.element_identifier)
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23 #if $safename in $input_list:
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24 #set $safename = str($safename) + "." + str($i)
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25 #end if
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26 $input_list.append($safename)
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27 ln -sf '${input}' '${safename}.bam' &&
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28 ln -sf '${input.metadata.bam_index}' '${safename}.bam.bai' &&
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29 echo '${safename}.bam' >> 'input_list.txt' &&
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30 #end for
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31 tin.py -i 'input_list.txt' --refgene='${refgene}' --minCov=${minCov}
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32 --sample-size=${samplesize} ${subtractbackground}
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33 && mv *summary.txt summary.tab
1421603cc95b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/rseqc commit 1dfe55ca83685cadb0ce8f6ebbd8c13232376d1d
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34 && mv *tin.xls tin.xls
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35 ]]>
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36 </command>
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38 <inputs>
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39 <param name="input" type="data" format="bam" multiple="true" label="Input BAM file" help="(--input-file)"/>
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40 <expand macro="refgene_param" />
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41 <param name="minCov" type="integer" value="10" label="Minimum coverage (default=10)"
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42 help="Minimum number of reads mapped to a transcript (--minCov)." />
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43 <param name="samplesize" type="integer" value="100" label="Sample size (default=100)"
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44 help="Number of equal-spaced nucleotide positions picked from mRNA.
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45 Note: if this number is larger than the length of mRNA (L), it will
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46 be halved until is's smaller than L. (--sample-size)." />
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47 <param name="subtractbackground" type="boolean" value="false" falsevalue=""
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48 truevalue="--subtract-background" label="Subtract background noise
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49 (default=No)" help="Subtract background noise (estimated from
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50 intronic reads). Only use this option if there are substantial
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51 intronic reads (--subtract-background)." />
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52 </inputs>
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54 <outputs>
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55 <data name="outputsummary" format="tabular" from_work_dir="summary.tab" label="TIN on ${on_string} (summary)" />
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56 <data name="outputxls" format="tabular" from_work_dir="tin.xls" label="TIN on ${on_string} (tin)" />
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57 </outputs>
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59 <!-- PDF Files contain R version, must avoid checking for diff -->
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60 <tests>
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61 <test expect_num_outputs="2">
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62 <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
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63 <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" ftype="bed12"/>
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64 <output name="outputsummary" file="summary.tin.txt" ftype="tabular"/>
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65 <output name="outputxls" file="output.tin.xls" ftype="tabular"/>
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66 </test>
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67 </tests>
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69 <help><![CDATA[
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70 ## tin.py
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71
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72 This program is designed to evaluate RNA integrity at transcript level. TIN
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73 (transcript integrity number) is named in analogous to RIN (RNA integrity
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74 number). RIN (RNA integrity number) is the most widely used metric to
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75 evaluate RNA integrity at sample (or transcriptome) level. It is a very
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76 useful preventive measure to ensure good RNA quality and robust,
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77 reproducible RNA sequencing. However, it has several weaknesses:
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78
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79 * RIN score (1 <= RIN <= 10) is not a direct measurement of mRNA quality.
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80 RIN score heavily relies on the amount of 18S and 28S ribosome RNAs, which
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81 was demonstrated by the four features used by the RIN algorithm: the
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82 “total RNA ratio” (i.e. the fraction of the area in the region of 18S and
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83 28S compared to the total area under the curve), 28S-region height, 28S
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84 area ratio and the 18S:28S ratio24. To a large extent, RIN score was a
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85 measure of ribosome RNA integrity. However, in most RNA-seq experiments,
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86 ribosome RNAs were depleted from the library to enrich mRNA through either
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87 ribo-minus or polyA selection procedure.
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88
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89 * RIN only measures the overall RNA quality of an RNA sample. However, in real
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90 situation, the degradation rate may differs significantly among
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91 transcripts, depending on factors such as “AU-rich sequence”, “transcript
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92 length”, “GC content”, “secondary structure” and the “RNA-protein
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93 complex”. Therefore, RIN is practically not very useful in downstream
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94 analysis such as adjusting the gene expression count.
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95
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96 * RIN has very limited sensitivity to measure substantially degraded RNA
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97 samples such as preserved clinical tissues. (ref:
58
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98 https://www.scribd.com/document/352764986/DV200-Technote-Truseq-Rna-Access).
51
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99
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100 To overcome these limitations, we developed TIN, an algorithm that is able
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101 to measure RNA integrity at transcript level. TIN calculates a score (0 <=
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102 TIN <= 100) for each expressed transcript, however, the medTIN (i.e.
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103 meidan TIN score across all the transcripts) can also be used to measure
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104 the RNA integrity at sample level. Below plots demonstrated TIN is a
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105 useful metric to measure RNA integrity in both transcriptome-wise and
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106 transcript-wise, as demonstrated by the high concordance with both RIN and
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107 RNA fragment size (estimated from RNA-seq read pairs).
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108
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109
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110 ## Inputs
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111
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112 Input BAM/SAM file
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113 Alignment file in BAM/SAM format.
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114
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115 Reference gene model
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116 Gene Model in BED format. Must be standard 12-column BED file.
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117
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118 Minimum coverage
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119 Minimum number of reads mapped to a tracript (default is 10).
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120
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121 Sample size
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122 Number of equal-spaced nucleotide positions picked from mRNA. Note: if
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123 this number is larger than the length of mRNA (L), it will be halved until
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124 it’s smaller than L (default is 100).
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125
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126 Subtract background
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127 Subtract background noise (estimated from intronic reads). Only use this
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128 option if there are substantial intronic reads.
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129
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130
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131 ## Outputs
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132
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133 Text
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134 Table that includes the gene identifier (geneID), chromosome (chrom),
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135 transcript start (tx_start), transcript end (tx_end), and transcript
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136 integrity number (TIN).
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137
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138 Example output:
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139
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140 ------ ----- ---------- --------- -------------
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141 geneID chrom tx_start tx_end TIN
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142 ------ ----- ---------- --------- -------------
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143 ABCC2 chr10 101542354 101611949 67.6446525761
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144 IPMK chr10 59951277 60027694 86.383618429
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145 RUFY2 chr10 70100863 70167051 43.8967503948
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146 ------ ----- ---------- --------- -------------
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147
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148 @ABOUT@
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149
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150 ]]>
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151 </help>
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152
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153 <expand macro="citations" />
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154
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155 </tool>