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+close(HTML);
+
diff -r 000000000000 -r 91ca33096034 edgeR.xml
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+++ b/edgeR.xml Tue Jan 13 21:12:26 2015 -0500
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+ - Estimates differential gene expression for short read sequence count using methods appropriate for count data
+
+ edgeR
+ limma
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+ edgeR.pl -a $analysis_type.analysis -e $html_file.files_path -f BH -h $html_file -o $output
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+ #if $analysis_type.analysis == "pw":
+ -r $analysis_type.rowsumfilter
+ #if $analysis_type.tagwise_disp.twd == "TRUE":
+ -u movingave
+ -t
+ #end if
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+ #else if $analysis_type.analysis == "glm":
+ #if $analysis_type.exp.export_norm == "true":
+ -n $norm_exp
+ #end if
+ -d tag
+ $analysis_type.cont_pw
+ #for $cnt in $analysis_type.contrasts:
+ "cnt::${cnt.add_cont}"
+ #end for
+
+
+ #else
+ #if $analysis_type.exp.export_norm == "true":
+ -n $norm_exp $analysis_type.exp.log
+ #end if
+ $analysis_type.cont_pw
+ #for $cnt in $analysis_type.contrasts:
+ "cnt::${cnt.add_cont}"
+ #end for
+ #end if
+ $matrix
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+ analysis_type[ "analysis" ] != "pw" and analysis_type[ "exp" ][ "export_norm" ] == "true"
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+.. class:: infomark
+
+**What it does**
+
+Estimates differential gene expression for short read sequence count using methods appropriate for count data.
+If you have paired data you may also want to consider Tophat/Cufflinks.
+Input must be raw count data for each sequence arranged in a rectangular matrix as a tabular file.
+Note - no scaling - please make sure you have untransformed raw counts of reads for each sequence.
+
+Performs digital differential gene expression analysis between groups (eg a treatment and control).
+Biological replicates provide information about experimental variability required for reliable inference.
+
+**What it does not do**
+edgeR_ requires biological replicates.
+Without replicates you can't account for known important experimental sources of variability that the approach implemented here requires.
+
+
+**Input**
+A count matrix containing sequence names as rows and sample specific counts of reads from this sequence as columns.
+The matrix must have 2 header rows, the first indicating the group assignment and the second uniquely identifiying the samples. It must also contain a unique set of (eg Feature) names in the first column.
+
+Example::
+
+ # G1:Mut G1:Mut G1:Mut G2:WT G2:WT G2:WT
+ #Feature Spl1 Spl2 Spl3 Spl4 Spl5 Spl6
+ NM_001001130 97 43 61 34 73 26
+ NM_001001144 25 8 9 3 5 5
+ NM_001001152 72 45 29 20 31 13
+ NM_001001160 0 1 1 1 0 0
+ NM_001001177 0 1 0 4 3 3
+ NM_001001178 0 2 1 0 4 0
+ NM_001001179 0 0 0 0 0 2
+ NM_001001180 0 0 0 0 0 2
+ NM_001001181 415 319 462 185 391 155
+ NM_001001182 1293 945 987 297 938 496
+ NM_001001183 5 4 11 7 11 2
+ NM_001001184 135 198 178 110 205 64
+ NM_001001185 186 1 0 1 1 0
+ NM_001001186 75 90 91 34 63 54
+ NM_001001187 267 236 170 165 202 51
+ NM_001001295 5 2 6 1 7 0
+ NM_001001309 1 0 0 1 2 1
+ ...
+
+
+Please use the "Count reads in features with htseq-count" tool to generate the count matrix.
+
+**Output**
+
+A tabular file containing relative expression levels, statistical estimates of differential expression probability, R scripts, log, and some helpful diagnostic plots.
+
+**Fixed Parameters**
+
+Method for allowing the prior distribution for the dispersion to be abundance-dependent used: movingave
+
+False discovery rate adjustment method used: Benjamini and Hochberg (1995)
+
+GLM dispersion estimate used: Tagwise Dispersion
+
+Gene filter used: less than 1 count per million reads
+
+.. class:: infomark
+
+**Attribution**
+This tool wraps the edgeR_ Bioconductor package so all calculations and plots are controlled by that code. See edgeR_ for all documentation and appropriate attribution.
+Recommended reference is Mark D. Robinson, Davis J. McCarthy, Gordon K. Smyth, PMCID: PMC2796818
+
+.. class:: infomark
+
+**Attribution**
+When applying the LIMMA (Linear models for RNA-Seq) anlysis the tool also makes use of the limma_ Bioconductor package.
+Recommended reference is Smyth, G. K. (2005). Limma: linear models for microarray data. In: 'Bioinformatics and Computational Biology Solutions using R and Bioconductor'. R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, W. Huber (eds), Springer, New York, pages 397--420.
+
+ .. _edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html
+ .. _limma: http://www.bioconductor.org/packages/release/bioc/html/limma.html
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