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  • Mathematical fool

    Hello!

    Well my problem is that I'm a Biologist and so I've got no much statistical or mathematical background to understand some procedures in R. (I'm working in differential expression of RNA-seq data nowadays). What should I read or do to help me through? Are there some specific books or lessons that could be useful for people like me?

    Thank you in advance!

  • #2
    Read through the DESeq2 vignette (or that from edgeR or limma). In particular, they generally have test datasets so you can follow along with how an analysis works. Other than that, you might try taking a short course on RNAseq from one of the many companies that seem to be popping up to offer that.

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    • #3
      I am learn a lot from Coursera.
      There is an article to help improving your skills:
      Online learning initiatives over the past decade have become increasingly comprehensive in their selection of courses and sophisticated in their presentation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university education on the internet, free of charge, a real possibility. At this pivotal moment it is appropriate to explore the potential for obtaining comprehensive bioinformatics training with currently existing free video resources. This article presents such a bioinformatics curriculum in the form of a virtual course catalog, together with editorial commentary, and an assessment of strengths, weaknesses, and likely future directions for open online learning in this field.

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      • #4
        Rafael Irizarry and I put together the Data Analysis for Genomics class on edx.

        Rafa's lectures (as well as all course content) are free to watch.

        You could jump to the differential expression content in week 3, which covers statistical inference and linear models.

        An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.


        The lecture notes are here (still be polished up):

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        • #5
          Thank you very much, all of you!

          I think your advices and links will help me a lot

          Comment

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