Mercurial > repos > nilesh > rseqc

annotate RPKM_saturation.xml @ 14:b21f0167e197 draft default tip

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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 15:05:13 +0000
parents a7f9084572fe
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1 <tool id="rseqc_RPKM_saturation" name="RPKM Saturation" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@GALAXY_VERSION@">
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2 <description>calculates raw count and RPKM values for transcript at exon, intron, and mRNA level</description>
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3 <macros>
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4 <import>rseqc_macros.xml</import>
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5 </macros>
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6 <expand macro="bio_tools"/>
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8 <expand macro="requirements" />
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10 <expand macro="stdio" />
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12 <version_command><![CDATA[RPKM_saturation.py --version]]></version_command>
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14 <command><![CDATA[
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15 @BAM_SAM_INPUTS@
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16 RPKM_saturation.py -i 'input.${extension}' -o output -r '${refgene}'
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18 #if str($strand_type.strand_specific) == "pair"
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19 -d
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20 #if str($strand_type.pair_type) == "sd"
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21 '1++,1--,2+-,2-+'
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22 #else
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23 '1+-,1-+,2++,2--'
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24 #end if
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25 #end if
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26
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27 #if str($strand_type.strand_specific) == "single"
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28 -d
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29 #if str($strand_type.single_type) == "s"
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30 '++,--'
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31 #else
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32 '+-,-+'
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33 #end if
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34 #end if
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35
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36 -l ${percentileFloor} -u ${percentileCeiling} -s ${percentileStep} -c ${rpkmCutoff}
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37 --mapq $mapq
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38 ]]></command>
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39
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40 <inputs>
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41 <expand macro="bam_sam_param" />
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42 <expand macro="refgene_param" />
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43 <expand macro="strand_type_param" />
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44 <param name="percentileFloor" type="integer" value="5" label="Begin sampling from this percentile (default=5)" help="(--percentile-floor)"/>
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45 <param name="percentileCeiling" type="integer" value="100" label="End sampling at this percentile (default=100)" help="(--percentile-ceiling)" />
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46 <param name="percentileStep" type="integer" value="5" label="Sampling step size (default=5)" help="(--percentile-step)" />
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47 <param name="rpkmCutoff" type="text" value="0.01" label="Ignore transcripts with RPKM smaller than this number (default=0.01)" help="(--rpkm-cutoff)" />
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48 <expand macro="mapq_param" />
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49 <expand macro="rscript_output_param" />
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50 </inputs>
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51
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52 <outputs>
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53 <expand macro="pdf_output_data" filename="output.saturation.pdf" />
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54 <data format="tabular" name="outputxls" from_work_dir="output.eRPKM.xls" label="${tool.name} on ${on_string}: RPKM"/>
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55 <data format="tabular" name="outputrawxls" from_work_dir="output.rawCount.xls" label="${tool.name} on ${on_string}: raw count"/>
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56 <expand macro="rscript_output_data" filename="output.saturation.r" />
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57 </outputs>
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58
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59 <tests>
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60 <test>
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61 <param name="input" value="pairend_strandspecific_51mer_hg19_random.bam"/>
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62 <param name="refgene" value="hg19.HouseKeepingGenes_30.bed"/>
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63 <param name="rscript_output" value="true" />
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64 <output name="outputxls">
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65 <assert_contents>
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66 <has_n_columns n="26" />
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67 <has_line_matching expression="chr1\t16174358\t16266950\tNM_015001.*" />
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68 </assert_contents>
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69 </output>
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70 <output name="outputrawxls">
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71 <assert_contents>
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72 <has_n_columns n="26" />
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73 <has_line_matching expression="chr1\t16174358\t16266950\tNM_015001.*" />
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74 </assert_contents>
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75 </output>
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76 <output name="outputr">
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77 <assert_contents>
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78 <has_text text="pdf('output.saturation.pdf')" />
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79 <has_line_matching expression="S5=c\(\d+\.\d+\)" />
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80 </assert_contents>
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81 </output>
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82 <output name="outputpdf" file="output.saturation.pdf" compare="sim_size" />
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83 </test>
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84 </tests>
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85
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86 <help><![CDATA[
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87 RPKM_saturation.py
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88 ++++++++++++++++++
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89
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90 The precision of any sample statitics (RPKM) is affected by sample size (sequencing depth);
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91 \'resampling\' or \'jackknifing\' is a method to estimate the precision of sample statistics by
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92 using subsets of available data. This module will resample a series of subsets from total RNA
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93 reads and then calculate RPKM value using each subset. By doing this we are able to check if
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94 the current sequencing depth was saturated or not (or if the RPKM values were stable or not)
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95 in terms of genes' expression estimation. If sequencing depth was saturated, the estimated
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96 RPKM value will be stationary or reproducible. By default, this module will calculate 20
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97 RPKM values (using 5%, 10%, ... , 95%,100% of total reads) for each transcripts.
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98
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99 In the output figure, Y axis is "Percent Relative Error" or "Percent Error" which is used
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100 to measures how the RPKM estimated from subset of reads (i.e. RPKMobs) deviates from real
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101 expression level (i.e. RPKMreal). However, in practice one cannot know the RPKMreal. As a
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102 proxy, we use the RPKM estimated from total reads to approximate RPKMreal.
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103
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104 .. image:: $PATH_TO_IMAGES/RelativeError.png
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105 :height: 80 px
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106 :width: 400 px
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107 :scale: 100 %
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108
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109 Inputs
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110 ++++++++++++++
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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.
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117
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118 Strand sequencing type (default=none)
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119 See Infer Experiment tool if uncertain.
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120
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121 Options
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122 ++++++++++++++
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123
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124 Skip Multiple Hit Reads
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125 Use Multiple hit reads or use only uniquely mapped reads.
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126
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127 Only use exonic reads
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128 Renders program only used exonic (UTR exons and CDS exons) reads, otherwise use all reads.
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129
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130 Output
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131 ++++++++++++++
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132
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133 1. output..eRPKM.xls: RPKM values for each transcript
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134 2. output.rawCount.xls: Raw count for each transcript
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135 3. output.saturation.r: R script to generate plot
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136 4. output.saturation.pdf:
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137
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138 .. image:: $PATH_TO_IMAGES/saturation.png
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139 :height: 600 px
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140 :width: 600 px
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141 :scale: 80 %
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142
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143 - All transcripts were sorted in ascending order according to expression level (RPKM). Then they are divided into 4 groups:
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144 1. Q1 (0-25%): Transcripts with expression level ranked below 25 percentile.
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145 2. Q2 (25-50%): Transcripts with expression level ranked between 25 percentile and 50 percentile.
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146 3. Q3 (50-75%): Transcripts with expression level ranked between 50 percentile and 75 percentile.
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147 4. Q4 (75-100%): Transcripts with expression level ranked above 75 percentile.
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148 - BAM/SAM file containing more than 100 million alignments will make module very slow.
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149 - Follow example below to visualize a particular transcript (using R console)::
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150
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151 pdf("xxx.pdf") #starts the graphics device driver for producing PDF graphics
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152 x &lt;- seq(5,100,5) #resampling percentage (5,10,15,...,100)
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153 rpkm &lt;- c(32.95,35.43,35.15,36.04,36.41,37.76,38.96,38.62,37.81,38.14,37.97,38.58,38.59,38.54,38.67, 38.67,38.87,38.68, 38.42, 38.23) #Paste RPKM values calculated from each subsets
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154 scatter.smooth(x,100*abs(rpkm-rpkm[length(rpkm)])/(rpkm[length(rpkm)]),type="p",ylab="Precent Relative Error",xlab="Resampling Percentage")
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155 dev.off() #close graphical device
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156
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157 .. image:: $PATH_TO_IMAGES/saturation_eg.png
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158 :height: 600 px
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159 :width: 600 px
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160 :scale: 80 %
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161
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162 @ABOUT@
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163
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164 ]]>
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165 </help>
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166
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167 <expand macro="citations" />
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168
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169 </tool>