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Old 06-18-2010, 01:53 AM   #1
Junior Member
Location: India

Join Date: Jun 2010
Posts: 5
Smile Ngs data analysis

Dear All,

As a part of my curriculum, i am currently planning to do a pipeline like sort on NGS data. Through various reading and other sorts i found that there are some leading tools like bowtie, tophat, Maq, Cufflinks etc.

From NCBI SRA sample of RNASEQ of illumina. but as i am new to these technologies i dont know what are the sequential steps i should follow to get a meaning full result.

what i am trying to analyse is to get the differential expression between two different organ data. How can i identify the control sample(is it needed?), and what are the tools i should use and in which order.

I know this will be a mundane task for some of you, but i am hopefull that you people can help me to sort this out.

Hoping for a positive replay asap
bassu is offline   Reply With Quote
Old 06-18-2010, 06:49 AM   #2
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Location: Kansas City

Join Date: Mar 2008
Posts: 197

If you're comparing two organs, there's probably no control, but just liver vs. kidney or vice versa.

First you'll need to align the sequences to a genome (bowtie, bwa, or tophat if you want a spliced alignment). Then you may want to get either RPKMs or count data (cufflinks, bedtools coverageBed) with which you can use something to calculate differentially expressed genes (DEseq, DEGseq, edgeR).

I doubt it's a mundane task to very many people at this point, It's still pretty new and complicated to most people...
mgogol is offline   Reply With Quote
Old 06-18-2010, 01:07 PM   #3
Location: USA

Join Date: Apr 2010
Posts: 76

In addition to the reply by Mgogol (which is what I do too)...

1) TopHat and Cufflinks for alignment. Cufflinks gives you FPKM values now instead of the previous RPKM by TopHat, which is mostly the same. Output file in SAM format gives coordinate information i.e. where each read maps onto genome. You can write a simple python script to find out whether the read overlaps any known gene to get read count data for each gene.

2) EdgeR for differential expression. But I think edgeR doesnt work with FPKM data. You need to supply EdgeR with count data to get differential expression.

Hope that helps
flobpf is offline   Reply With Quote
Old 06-19-2010, 03:07 AM   #4
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Location: India

Join Date: Jun 2010
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Dear mgogol & flobpf,

Thanks for your kind informations, i will work with your provided information and let you informed about my progress time to time.

Once again thank you guys!!
bassu is offline   Reply With Quote
Old 10-12-2015, 04:28 AM   #5
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Location: pune,India

Join Date: Sep 2015
Posts: 7

Dear All,
i am currently doing variant analysis of NF2 ,after visualisation the result ,but i am confuse my result is it correct or not? and also i couldn't find the no. of snp , rather i check the another site dbsnp , i put individually gene i.d for search but no answere has come. plz tell me how can i do it step by step?
and also how can i identify the result or no.of snp ?
I doubt it's a pretty and complicaited question but i am hopefull that you people can help me to sort this out..
hoping fir a positive rply asap is offline   Reply With Quote

differential expression, rnaseq

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