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  • GenoMax
    replied
    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).

    Leave a comment:


  • rodrigo.duarte88
    replied
    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..

    Leave a comment:


  • GenoMax
    replied
    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?

    Leave a comment:


  • rodrigo.duarte88
    started a topic mapping reads to single human chromosome

    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?

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