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differential_gene_expression_analysis [2017/08/09 13:13] – 129.173.94.20differential_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\\ 
  
 Notes on this tutorial:\\  Notes on this tutorial:\\ 
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 4- Generate ng vectors (for isoform-level differential expression assessment only):\\  4- Generate ng vectors (for isoform-level differential expression assessment only):\\ 
 <code <code
->rsem-generate-ngvector <transcriptome.fasta>  <assembly_short_name>+>rsem-generate-ngvector <transcriptome.fasta> <assembly_short_name>
 </code> </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.\\ \\  **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.\\ \\ 
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   * 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')\\ \\    * 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.)\\ \\  **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.)\\ \\ 
-1- load the EBSeq library:+1- Load the EBSeq library:
 <code> <code>
 > library(EBSeq) > library(EBSeq)
 </code> </code>
-2- Define data matrix:+2- Define the data matrix:
 <code> <code>
 > IsoMat <- data.matrix(read.table(file="<matrix_name>")) > IsoMat <- data.matrix(read.table(file="<matrix_name>"))
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