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Old 02-01-2012, 09:57 AM   #1
mediator
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Default Identify and visualize differentially expressed genes from RNA-Seq data?

Hi All,
I have aligned RNA Seq data for four healthy controls and four patients, in bam format. Then I made a table for RPKM for all the genes. Now how do I quickly identify and visualize those differentially expressed genes in patients? In other words, how to identify which genes are expressed more in patients but not in healthy control? I've tried SAM (significant analysis for microarray ) but no good. Any suggestions? Thanks!
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Old 02-01-2012, 10:03 AM   #2
chadn737
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There are several programs in R that are for differential expression of RNA-seq data:

EdgeR
DESeq
BaySeq
DEGseq

However the input for these programs is raw read counts, not RPKM normalized genes.
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Old 02-01-2012, 10:08 AM   #3
Richard Finney
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What tool did you use?
is the result by exon? or gene? how does it correct for gene overlap?

How would you like to visualize the results? As a list? On the genome? On pathways or ontologies?
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Old 02-01-2012, 10:12 AM   #4
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@chadn737
Thanks!
@Richard Finney
I used Seqmonk to generate RPKM , results are by exons but can be averaged to by genes. I would like to visualize in a hierarchical clustered heat map, like many microarray data.
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Old 03-23-2012, 12:08 PM   #5
kjlee
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Hello mediator,

I have found that MeV is very helpful in visualizing RNA-seq expression data. It is well-documented and easy to implement.

Cheers,
Kevin
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Old 03-25-2012, 11:51 AM   #6
mediator
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@kjlee
Thanks for the advice! I already use MeV for microarray. Pretty handy. Let's see how RNA-Seq data goes with MeV.
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Old 05-09-2012, 12:02 AM   #7
kumardeep
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Hi all
I have RNA-seq data (2 control sets and 2 test sets). I have generated the *.sorted.bam files (~1GB) through bowtie software. Right now I am using cufflinks software to generate RPKM values to get differential gene expression quantitatively. In cufflinks, I followed the command:
cufflinks control_1.sorted.bam
It takes much time on cluster (thats reasonable for 1gb INPUT files I guess). The output file (say transcript.gtf) is having RPKM values. I want to know how to proceed further to get final list of differentially expressed genes with corresponding RPKM values.
Do I have to run the above command for all input files (viz. control_2.sorted.bam, test_1.sorted.bam, test_2.sorted.bam)?
Also How to compare RPKM values finally ?
Thanks in advance..
Kumardeep
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Old 05-09-2012, 01:00 AM   #8
LiamT
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Hi Kumardeep

You should always start a new thread if you're asking a new question, even if it is related (you can always refer to the other thread).
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