Difference between revisions of "RNASeq: Obtaining read counts"

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Read counting may be CPU-intensive, depending on the size of the BAM file(s) used. It is thus recommended to run this process as a job script on Abel. Such a job script must first load the R module on Abel, subsequently executing an R script containing the read-counting R code. Such a job script may look like:
 
Read counting may be CPU-intensive, depending on the size of the BAM file(s) used. It is thus recommended to run this process as a job script on Abel. Such a job script must first load the R module on Abel, subsequently executing an R script containing the read-counting R code. Such a job script may look like:
 
<div style="line-height:90%; background-color: LightGray; border-style: solid; border-width:1px; font-family:courier new,courier,monospace;">
 
<div style="line-height:90%; background-color: LightGray; border-style: solid; border-width:1px; font-family:courier new,courier,monospace;">
#!/bin/bash
+
<nowiki>#</nowiki>!/bin/bash
  
#SBATCH --job-name=my_R_script_name
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<nowiki>#</nowiki>SBATCH --job-name=my_R_script_name
  
#SBATCH --account=myAccountName
+
<nowiki>#</nowiki>SBATCH --account=myAccountName
  
#SBATCH --time=48:00:00
+
<nowiki>#</nowiki>SBATCH --time=48:00:00
  
#SBATCH --mem-per-cpu=3500M
+
<nowiki>#</nowiki>SBATCH --mem-per-cpu=3500M
  
#SBATCH --nodes=1
+
<nowiki>#</nowiki>SBATCH --nodes=1
  
#SBATCH --ntasks-per-node=1
+
<nowiki>#</nowiki>SBATCH --ntasks-per-node=1
  
  
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module load R  
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module load R
  
 
R CMD BATCH /path/to/Rscript.R
 
R CMD BATCH /path/to/Rscript.R
 
</div>
 
</div>

Latest revision as of 12:41, 28 May 2015

Read counting implies counting the number of reads that map inside a specific annotation feature. The tutorials listed here demonstrate read counting as part of differential gene expression using the R library DESeq/DESeq2. Alternatively, reads may be counted with the python program HTSeq-count, see the manual for instructions (http://www-huber.embl.de/users/anders/HTSeq/doc/overview.html).

Read counting may be CPU-intensive, depending on the size of the BAM file(s) used. It is thus recommended to run this process as a job script on Abel. Such a job script must first load the R module on Abel, subsequently executing an R script containing the read-counting R code. Such a job script may look like:

#!/bin/bash

#SBATCH --job-name=my_R_script_name

#SBATCH --account=myAccountName

#SBATCH --time=48:00:00

#SBATCH --mem-per-cpu=3500M

#SBATCH --nodes=1

#SBATCH --ntasks-per-node=1


source /cluster/bin/jobsetup


module load R

R CMD BATCH /path/to/Rscript.R