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  • Little desperate and alone (Help Me)

    Hello world!
    Well, I am a master degree student and need your help. I think this forum will help to me get more help in the web.
    I did an experiment and extract total RNA of mice heart. I sent this material to BGI sequence in Illumina Hiseq for 10M reads.
    I was studying the pipeline for what to do with the raw sequence until the visualization but I do not know anything about the computer skills I needed to perform each step. For example:
    I have a raw sequence and I need to perform trimming and after that align with genome reference but what is the commands in linux and the informatics.
    I would appreciate a lot references, books, sites, articles, little help.
    Thank you a lot since now and sorry for my poor english.

  • #2
    Maybe start here but remember this is only guide. The appropriate workflow and analysis may differ for your data.

    Comment


    • #3
      Originally posted by N311V View Post
      Maybe start here but remember this is only guide. The appropriate workflow and analysis may differ for your data.

      http://www.broadinstitute.org/gatk/g...ices?bpm=index
      Thank you very much.

      Comment


      • #4
        I've never used it myself, but the Galaxy project may be the best answer for you.
        They offer a web-based interface to all these command line tools.
        I don't know that the wait time is on their public server though.
        Galaxy is a community-driven web-based analysis platform for life science research.


        I would not run the analysis on a personal desktop, unless you have a lot of RAM and hard drive space.
        To run the analysis on your own Linux server, you'll need to install the following tools.
        Trimming: Trimmomatic
        Alignment: TopHat
        Gene quantification: Cufflinks (or htseq-count and DESeq2, but these tools are a bit harder to use).

        You'll also need the genome and its annotation.
        I would recommend downloading the iGenome for the mouse.

        You can easily find all these resources by googling them.

        If the wait time on the Galaxy public server is too long, you're probably better off finding a bioinformatician with access to a Unix server to help you.

        I suppose it is your supervisor's idea that you do the analysis yourself. Time and again, I've seen principal investigators overestimate the ability of their wet lab students to use the Unix command line, as well as overestimate their students' knowledge of the basic statistics required to understand the results of a differential expression analysis.

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        • #5
          The simple way to proceed is to download a demo version of CLC Bio or NextGene.

          10 million reads is not very many. A decent desktop computer can align this.

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          • #6
            I suppose it is your supervisor's idea that you do the analysis yourself. Time and again, I've seen principal investigators overestimate the ability of their wet lab students to use the Unix command line, as well as overestimate their students' knowledge of the basic statistics required to understand the results of a differential expression analysis.
            Too true. "Computer literacy" is an excellent metaphor; if you're not already proficient with statistics and the Unix-like command line, then your PI's asking you to learn those things just to analyze one sequencing run is like asking you to learn Ancient Greek just to translate one document. I do encourage every scientist who works with large datasets to learn these things, but don't hold up your whole project for it. Even aside from the huge delay while you start your education from scratch, you're inevitably going to make mistakes and get wrong results (possibly without knowing it) the first time. At least get an expert to do the analysis for you and then go over her scripts to understand how they work.
            Last edited by jwfoley; 07-09-2014, 08:53 AM.

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            • #7
              Thanks everybody that help me!

              Comment


              • #8
                You could check out Practical Computing for Biologists. Gives a pretty good intro into using command interfaces, setting up environments, etc.

                Comment


                • #9
                  I would recommend iPlantcolloaborative.org as it a lot of useful tools and guides on what to do and how to do everything including visualization of the results.

                  Comment


                  • #10
                    Greg Wilson's Software Carpentry is designed to help people in your position.
                    Contact them, and convince your University to invite them down for a bootcamp
                    but in the meanwhile they have their teaching materials online

                    http://software-carpentry.org/lessons.html

                    n.b. I have no compeating interests, just respect for Greg's work.
                    Last edited by tomc; 09-26-2014, 01:20 AM. Reason: add disclaimer

                    Comment


                    • #11
                      Originally posted by jwfoley View Post
                      Too true. "Computer literacy" is an excellent metaphor; if you're not already proficient with statistics and the Unix-like command line, then your PI's asking you to learn those things just to analyze one sequencing run is like asking you to learn Ancient Greek just to translate one document. I do encourage every scientist who works with large datasets to learn these things, but don't hold up your whole project for it. Even aside from the huge delay while you start your education from scratch, you're inevitably going to make mistakes and get wrong results (possibly without knowing it) the first time. At least get an expert to do the analysis for you and then go over her scripts to understand how they work.
                      I agree with jwfoley. If you dont have any bioinformatics skills you better ask someone to do it for you at this moment. I think BGI does provide data analysis plans but of course you'll have to pay extra.

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