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  • Conversion of .fastq to .txt RNA-seq files for EdgeR package

    Hi all,

    I want to do the TMM normalization on my RNA-seq data using EdgeR package in R and have two questions:

    1) How can I convert .fastq files to .txt files to be able to feed them into the EdgeR package?

    2) My RNA-seq data are paired sequence .fastq files. What quality control should I do on them and how should I merge them together prior to analysis?

    Thanks for the help,

    Hamid

  • #2
    1) Align them on your reference genome with a splice-junction aware aligner like TopHat or STAR. Count the aligned reads with htseq-count or featureCounts.

    2) Do the quality controls on the FASTQ files with FASTQC. Don't merge the paired FASTQ files. Give both files in input to your aligner.

    Comment


    • #3
      Thanks a a lot for the help blancha. I'm doing the analysis in windows-based R.

      I'm wondering if you know any package for windows-based R (or Mac-based R) for aligning the fastq files on my reference genome?

      Comment


      • #4
        R is really more useful at a later stage, when you already have the count matrices.
        There may be a way to do the alignment with an R package, but I've never done it with R.
        Even the official document on BioConductor for RNA-Seq analysis recommends using a command-line program, most of which are written in C++ or Java, to do the alignment first.
        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.


        The aligner I use is TopHat, which is historically the most popular aligner.
        STAR is becoming increasingly popular due to its speed of execution.
        BBMap is also becoming more widely used, partly because of Brian Bushell's work on this forum, giving technical support.

        Most of these programs are Unix command line programs.
        BBMap is written in Java though, so it will run on Windows.
        Note that NGS data is generally requires quite significant computational resources, hence the reason the alignment is generally done on computing clusters.

        If you are unfamiliar with the Unix command line, you could do the alignment on the public server for Galaxy, but I don't know how long you would have to wait for the resource to be available on the public server for you to do your alignment.

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        • #5
          There is a Bioconductor package called Rsubread that can carry out read alignment. This package provides R wrapper functions for those programs (Subread aligner, Subjunc aligner, featureCounts ...) included in the Subread package, which is released via SourceForge.

          Subread and Subjunc are among the fastest aligners available so far, and they only use a moderate amount of memory.

          Here is a complete Bioconductor/R pipeline for RNA-seq analysis from read mapping to the discovery of differentially expressed genes:

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          • #6
            Thanks everyone for all the help.

            Comment

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