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  • softwares for bacterial RNA-Seq analysis?

    Hi everyone,
    in our lab we are going to try to do some bacterial RNA-Seq run with our Ion Torrent.

    Anyone with experience in Bacterial RNA-Seq that can suggest the best softwares to analyze the data?

    We prefer to run software locally on our servers!

    Thanks everyone!

  • #2
    You may try Subread, which is a splice-aware aligner and is very powerful in aligning long reads. It tolerates quite a lot of errors in the mapping while maintaining its high accuracy at the same time, making it particularly suitable for mapping reads generated from Ion Torrent platform which is known to have a high sequencing error rate.

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    • #3
      Originally posted by shi View Post
      You may try Subread, which is a splice-aware aligner and is very powerful in aligning long reads. It tolerates quite a lot of errors in the mapping while maintaining its high accuracy at the same time, making it particularly suitable for mapping reads generated from Ion Torrent platform which is known to have a high sequencing error rate.
      Thanks, i'll try it!

      Do you know any paper/review to be used as a first-time guide to RNA-seq?

      EDIT: you mentioned splicing, i'm going to analyze only bacterial data, so no splicing, can i use eukaryotic tools without problems?
      Last edited by Gorbenzer; 05-03-2013, 01:46 AM.

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      • #4
        softwares for bacterial RNA-Seq analysis?

        There is a review article, Studying bacterial transcriptomes using RNA-seq,
        in Current Opinion in Microbiology, which should be useful if you are working on bacteria.



        The SEQanswers SeqWiki has a how-to section on RNA-Seq analysis,



        As good starting points for RNA-Seq and data analysis of RNA-Seq in general,
        see this review article by Wong et al in Nature Reviews Genetics,



        and this review by Pepke et al in Nature Methods on computational methods,

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        • #5
          Originally posted by mastal View Post
          There is a review article, Studying bacterial transcriptomes using RNA-seq,
          in Current Opinion in Microbiology, which should be useful if you are working on bacteria.



          The SEQanswers SeqWiki has a how-to section on RNA-Seq analysis,



          As good starting points for RNA-Seq and data analysis of RNA-Seq in general,
          see this review article by Wong et al in Nature Reviews Genetics,



          and this review by Pepke et al in Nature Methods on computational methods,

          http://www.nature.com/nmeth/journal/...meth.1371.html
          Thanks so much,
          i'll read those in the week end!!

          Comment


          • #6
            Hi guys,
            Which is the best pipeline to use for analysis of strand-specific bacterial RNAseq data (illumina platform). i have tried bowtie2 (using default settings), cufflinks (cuffmerge and cuffdiff) pipeline but i'm not getting any differentially expressed genes. Which pipeline is most ideal for bacterial DE analysis.
            I have read through most of the articles cited above but i still cant get any DE genes.
            Thanx,
            Stan
            Last edited by stanikay; 11-21-2013, 12:16 PM.

            Comment


            • #7
              Originally posted by stanikay View Post
              Hi guys,
              Which is the best pipeline to use for analysis of strand-specific bacterial RNAseq data (illumina platform). i have tried bowtie2 (using default settings), cufflinks (cuffmerge and cuffdiff) pipeline but i'm not getting any differentially expressed genes. Which pipeline is most ideal for bacterial DE analysis.
              I have read through most of the articles cited above but i still cant get any DE genes.
              Thanx,
              Stan
              Mine is:

              -mapping with TMAP (Ion Torrent specific)
              -counting with HTSeq
              -edgeR for differential expression
              -TopGO for enrichment, previously run Blast2GO if working with non-model organism.

              Best, Bernardo

              Comment


              • #8
                Here is a Bioconductor R pipeline:

                http://bioinf.wehi.edu.au/RNAseqCaseStudy/

                Comment

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