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  • sakeebz
    Junior Member
    • May 2015
    • 2

    #1

    Getting RNA Sequence data for differential analysis

    Hi I am new to bioinformatics and I am doing a project on differential analysis using splicemap.

    I am trying to get long reads RNA-seq data for different tissue samples. So far I found data in fastq format on the encode website here http://genome.ucsc.edu/ENCODE/dataMa...trixHuman.html.

    But this data does not work with splicemap which omits all lines because they are less than 50 bp.

    Does anyone know where I could get long read RNA-seq data on different human tissue samples? I noticed that a sample file from splicemap was called long_reads_1_100K.txt.seq.

    Any help will be greatly appreciated!

    Thank you!
  • GenoMax
    Senior Member
    • Feb 2008
    • 7142

    #2
    You can get all kinds of datasets from NCBI SRA: http://www.ncbi.nlm.nih.gov/sra/?term=human+rna-seq Add additional filters as needed.

    That said since you are new and doing this as a project (one time?) you probably want to start with a good quality dataset. One option is to get the TruSeq Stranded mRNA data from Illumina basespace. You will need to create a free account. Here is the data library link: http://www.illumina.com/informatics/...a-library.html

    If you are able to use a slightly older illumina dataset that is a mix of paired-end 50 bp and single-end 75 bp reads then you can try the human bodymap (16 tissues) dataset here: http://www.ncbi.nlm.nih.gov/geo/quer...i?acc=GSE30611 Additional info about this set here: http://www.ensembl.info/blog/2011/05...from-illumina/

    Comment

    • GenoMax
      Senior Member
      • Feb 2008
      • 7142

      #3
      If you are looking for quality data to look for splice isoforms then above illumina datasets will work great (these are independent tissue samples).

      On the other hand, if you are interested in differential expression analysis then you will need to get a dataset that has appropriate groups of samples (e.g. control/mutant, cancer/normal etc). You can either start with a published paper and get the SRA accession number from it to download the data or search SRA with a query like this: http://www.ncbi.nlm.nih.gov/sra/?term=cancer+normal

      Comment

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