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--- differential_gene_expression_analysis [2017/08/09 13:10] – created 129.173.94.20
+++ differential_gene_expression_analysis [2017/08/09 13:37] (current) – 129.173.94.20
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-**DIFFERENTIAL GENE EXPRESSION ANALYSIS**\\ by Tommy Harding\\
+====== Differential gene expression analysis ======
+by Tommy Harding\\
-Note on this tutorial:\\
+Notes on this tutorial:\\
   * Terms in between <> are user-specified names.\\
   * Steps indicated with † are computer-intensive and should be submitted to perun through a shell script.\\
   * This tutorial summarizes the basics. To benefit the full potential of each program, refer to the user manuals.\\ \\ \\
 **A- Quantify gene expression using RSEM**
- (https://deweylab.github.io/RSEM/README.html). This program maps reads onto transcript sequences considering multi-mapping reads (i.e. reads that map at multiple locations in the transcriptome) in order to determine spliced isoform-specific expression. The gene count matrix generated by RSEM can then be used to assess differential expression using other programs like EBSeq, DESeq or VOOM-limma.\\ \\
+ (https://deweylab.github.io/RSEM/README.html). RSEM maps reads onto transcript sequences considering multi-mapping reads (i.e. reads that map at multiple locations in the transcriptome) in order to determine spliced isoform-specific expression. The gene count matrix generated by RSEM can then be used to assess differential expression using other programs like EBSeq, DESeq or VOOM-limma.\\ \\
 - Prepare reference file:\\
 <code>
@@ Line 25: / Line 26: @@
 - Generate ng vectors (for isoform-level differential expression assessment only):\\
 <code
->rsem-generate-ngvector <transcriptome.fasta>  <assembly_short_name>
+>rsem-generate-ngvector <transcriptome.fasta> <assembly_short_name>
 </code>
 **A’- Calculate fragment size using Qualimap.** In order to determine the size of your library empirically, map paired reads using bowtie and then generate statistics on your data using Qualimap. Perform this analysis in another folder than the one used for the RSEM run.\\ \\
@@ Line 50: / Line 51: @@
   * Important to set java-mem-size value to higher than the default otherwise you run out of memory. Also, use the higher RAM nodes (e.g. 'qsub -q 256G-batch')\\ \\
 **B- Assess differential expression using EBSeq** (http://www.bioconductor.org/packages/devel/bioc/vignettes/EBSeq/inst/doc/EBSeq_Vignette.pdf). In order to access to the full potential of EBSeq, run the program in R. (To start an R session on perun, type R.)\\ \\
-- load the EBSeq library:
+- Load the EBSeq library:
 <code>
 > library(EBSeq)
 </code>
-- Define data matrix:
+- Define the data matrix:
 <code>
 > IsoMat <- data.matrix(read.table(file="<matrix_name>"))