mapping reads to single human chromosome

rodrigo.duarte88 · 05-12-2015, 03:54 AM

Dear colleagues,

I have started working with RNAseq very recently and got stuck with the following:

- Should I map my reads to the whole human genome or only to the chromosome I am interested?

I've seen mapping to a single chromosome can skew my data, but it took 2 days for tophat to map the reads of a single RNAseq library to a single chromosome (I am on an octa-core PC running Ubuntu).

Should I definitely buy access to a cluster or there are ways to over come this?

GenoMax · 05-12-2015, 04:12 AM

Sounds like you are not using multiple threads on your PC (-p option, not all parts of tophat are threaded so don't expect "n" fold speed-up).

Do you have an extraordinarily large input data set?

rodrigo.duarte88 · 05-12-2015, 04:36 AM

I did use this option. I used all 8 cores of my PC, the machine (the cooling fan) sounded like a train for those 2 days. haha

Because our lab is interested in allele specific expression, we aimed for high depth of sequencing. Each fastq file generated (Forw and Rev) contains approx 170 million reads each.

I know in the long term using a cluster will be essential.. But now for primary analysis I am wishing I didn't need one..

GenoMax · 05-12-2015, 04:46 AM

If your primary objective of getting the mapping done is now over then you could move on to other analysis

If you expect to do this for multiple samples then using a more robust computational resource is a no-brainer. Using a single chromosome (or even the region where you gene of interest is) is a possibility but due to the short nature of illumina reads you may get false positive hits (to regions of common domains/repeats etc).

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05-12-2015, 03:54 AM	#1
rodrigo.duarte88 Member Location: London Join Date: Jan 2015 Posts: 10	mapping reads to single human chromosome Dear colleagues, I have started working with RNAseq very recently and got stuck with the following: - Should I map my reads to the whole human genome or only to the chromosome I am interested? I've seen mapping to a single chromosome can skew my data, but it took 2 days for tophat to map the reads of a single RNAseq library to a single chromosome (I am on an octa-core PC running Ubuntu). Should I definitely buy access to a cluster or there are ways to over come this?

05-12-2015, 04:12 AM	#2
GenoMax Senior Member Location: East Coast USA Join Date: Feb 2008 Posts: 7,088	Sounds like you are not using multiple threads on your PC (-p option, not all parts of tophat are threaded so don't expect "n" fold speed-up). Do you have an extraordinarily large input data set?

05-12-2015, 04:36 AM	#3
rodrigo.duarte88 Member Location: London Join Date: Jan 2015 Posts: 10	I did use this option. I used all 8 cores of my PC, the machine (the cooling fan) sounded like a train for those 2 days. haha Because our lab is interested in allele specific expression, we aimed for high depth of sequencing. Each fastq file generated (Forw and Rev) contains approx 170 million reads each. I know in the long term using a cluster will be essential.. But now for primary analysis I am wishing I didn't need one..

05-12-2015, 04:46 AM	#4
GenoMax Senior Member Location: East Coast USA Join Date: Feb 2008 Posts: 7,088	If your primary objective of getting the mapping done is now over then you could move on to other analysis If you expect to do this for multiple samples then using a more robust computational resource is a no-brainer. Using a single chromosome (or even the region where you gene of interest is) is a possibility but due to the short nature of illumina reads you may get false positive hits (to regions of common domains/repeats etc).