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  • am_Abdullah
    Junior Member
    • Apr 2015
    • 2

    RNA seq gene expression data and clustering

    I have some questions:

    1. where can I find some RNA-seq gene expression data to download ?

    2. I want to do some clustering and classification on RNA-seq gene expression data? from my reading I read that I should normalize the read count before input them to classification or clustering. Is it correct?

    Thank you
  • dpryan
    Devon Ryan
    • Jul 2011
    • 3478

    #2
    1. GEO, SRA, ENA, etc.
    2. Likely, it depends on how your classifier works. You'll definitely want to normalize before clustering.

    Comment

    • am_Abdullah
      Junior Member
      • Apr 2015
      • 2

      #3
      Is there any tutorial teach me how to search in these databases to find gene expression across different samples?

      Comment

      • diego diaz
        Member
        • Oct 2013
        • 62

        #4
        This is a good tutorial to perform differential expression analysis with Deseq2



        Most popular programs to perform differential expression analysis are written in R, a programming language oriented to statistical analysis. If you aren't familiar with R, I recommend you learn

        Comment

        • GenoMax
          Senior Member
          • Feb 2008
          • 7142

          #5
          Originally posted by am_Abdullah View Post
          Is there any tutorial teach me how to search in these databases to find gene expression across different samples?
          In general there is raw data in databases such as SRA, ENA etc. Some records may have summarized gene expression values but you can't search for those easily. You will need to get the sequence data and do the analysis yourself following a tutorial such as the one Diego posted or referring to this vignette: http://www.bioconductor.org/packages...doc/DESeq2.pdf

          If you are only interested in browsing expression levels (without doing any analysis) then ArrayExpress may help: http://www.ebi.ac.uk/arrayexpress/browse.html

          Comment

          • Michael Love
            Senior Member
            • Jul 2013
            • 333

            #6
            Another pointer: our DESeq2 tutorial for people just starting with RNA-seq is here:

            Here we walk through an end-to-end gene-level RNA-seq differential expression workflow using Bioconductor packages. We will start from the FASTQ files, show how these were aligned to the reference genome, and prepare a count matrix which tallies the number of RNA-seq reads/fragments within each gene for each sample. We will perform exploratory data analysis (EDA) for quality assessment and to explore the relationship between samples, perform differential gene expression analysis, and visually explore the results.

            Comment

            • maxsalm
              Member
              • Feb 2015
              • 18

              #7
              This is also a great tutorial: http://arxiv.org/abs/1302.3685

              Comment

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