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comparison edgeR.xml @ 7:3aadcea3347b draft

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author fcaramia
date Thu, 13 Sep 2012 00:50:59 -0400
parents b6de7e3b8239
children 86292c2b0ba9
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6:b6de7e3b8239 7:3aadcea3347b
1 <tool id="edgeR" name="Empirical analysis of digital gene expression data" version="0.0.1"> 1 <tool id="edgeR" name="Empirical analysis of digital gene expression data" version="0.0.1">
2 <description> - Estimates differential gene expression for short read sequence count using methods appropriate for count data</description>
2 <requirements> 3 <requirements>
3 <requirement type="R-module">edgeR</requirement> 4 <requirement type="R-module">edgeR</requirement>
4 <requirement type="R-module">limma</requirement> 5 <requirement type="R-module">limma</requirement>
5 </requirements> 6 </requirements>
6 <command interpreter="perl"> 7 <command interpreter="perl">
157 158
158 **What it does not do** 159 **What it does not do**
159 edgeR_ requires biological replicates. 160 edgeR_ requires biological replicates.
160 Without replicates you can't account for known important experimental sources of variability that the approach implemented here requires. 161 Without replicates you can't account for known important experimental sources of variability that the approach implemented here requires.
161 162
163
162 **Input** 164 **Input**
163 A count matrix containing sequence names as rows and sample specific counts of reads from this sequence as columns. 165 A count matrix containing sequence names as rows and sample specific counts of reads from this sequence as columns.
164 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. 166 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.
165 167
166 Example:: 168 Example::
206 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. 208 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.
207 209
208 .. _edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html 210 .. _edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html
209 .. _limma: http://www.bioconductor.org/packages/release/bioc/html/limma.html 211 .. _limma: http://www.bioconductor.org/packages/release/bioc/html/limma.html
210 212
213
211 </help> 214 </help>
212 215
213 </tool> 216 </tool>