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  • mycrobe
    Junior Member
    • Apr 2013
    • 2

    #1

    RNA MiSeq analysis: workflow and software suggestions?

    The scenario: I have archaeal RNA MiSeq data (Illumina single end 50 bp reads in fastq files) from two different growth conditions. I would like to calculate the number of reads per gene in each condition and display the relative change in expression as a heat map and/or a table.

    Flailing in the dark: So far I have mapped the reads to my reference genome with bowtie2. Using the resulting sam files I looked at the assembled reads on Tablet, with an imported GFF3 file of my reference genome to identify the genes. This let me visually see the packed reads for each gene, but it won't calculate the number of reads per gene. I need to be able to do this before I can go on to calculate the change in expression, which I think I can do with DEGseq.

    My file toolkit so far: I have fastq files of the original MiSeq reads, sam files of the mapped reads, and fasta, gbf, and GFF3 formatted files of the reference genome.

    My program toolkit so far: Bowtie2, Tablet, R, DEGseq R package. I have installed R and DEGseq, but have not actually used them yet.

    My hearts desire: I'm looking for advice on a workflow and a list of software that will help me go from raw reads to relative change in expression. Maybe incorporating what I already have, more likely suggestions of alternate programs. Also, I am not a computer wiz. I barely have a handle on navigating with command line in terminal. But I can learn!
  • shi
    Wei Shi
    • Feb 2010
    • 236

    #2
    Alternatively, you can try the Subread + featureCounts + limma(voom) pipeline. This is a R pipeline using all Bioconductor packages (Subread and featureCounts are available in the Rsubread package). This is the pipeline we now routinely use in our institution. Displaying fold changes in heat maps using limma output is quite straightforward.

    Comment

    • mycrobe
      Junior Member
      • Apr 2013
      • 2

      #3
      Thank you very much! I will try those out.

      Comment

      • chadn737
        Senior Member
        • Jan 2009
        • 392

        #4
        I'm not really sure who uses DEGseq or poisson based models like DEGseq. I would suggest that you use a negative binomial model like EdgeR or DESeq.

        Comment

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