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fly_xqtl's Introduction

fly_XQTL

GitHub for the Drosophila X-QTL paper

There are folders for notes, scripts, helperfiles:

-notes contain text files to reproduce results in the paper
-scripts are scripts that are required (typically bash/R/python)
-helpfiles are various files used by the scripts
-some of the scripts (*.sh files) assume SGE some SLURM (over time I will migtrate to all SLURM).

notes:

  • raw.data.txt
    • code to massage the raw data, including fastq file to treatments, and SRA info
  • make.bams.txt
    • code to make bams for each file, including code to sub-sample to lower coverage, or combine samples to make pseudo-high-coverage data
  • call.SNPs.txt
    • code to call SNPs by sample. We call at a fixed set of HQ SNPs based on founders. In the pools for each SNP we calculate the frequency of the ALT allele
  • call.haplotypes.txt
    • call haplotypes separately by pooled sample using "limSolve" (see paper and Linder et al 2020). Requires a pooled sample, and founder bams
  • figure1.txt
    • code to generate representative haplotypes for Figure 1
  • figure2.txt
    • code to generate Figure 2 = distribution of LOD scores at causative site
      • this is a simple model of equally frequent founders and Gaussian effects, only a marker at the QTL is simulated
      • we also simulate a QTL of zero effect to get a null distribution
  • resolution.coarse.txt
    • code to look at resolution under coarse markers (markers every 200kb) including code for
      • Figure3, Supp Figure 2A, and Supp NRILs_looselinkage
  • resolution.fine.txt
    • code to look at resolution under fine markers (markers every 10kb) for a subset of conditions (smaller region, n_gens_random_mate = 4), including code for
      • Supp Figure 2B
  • manhattan.txt
    • code to reproduce the Manhattan plots (Fig 4 and Supp Fig 4), including code to make manhattan plots more generally (qqman wasn't flexible enough!)
  • QQplot.txt
    • code to reproduce the QQ plot of Supp Figure 3
  • haplotype.change.at.QTL.txt
    • code to reproduce Figure 5, showing changes in haplotypes at QTL (and local LOD scores)

If you are analyzing real data (and do not wish to reproduce simulations)

  • raw.data.txt -> make.bams.txt -> call.SNPs.txt -> call.haplotypes.txt -> manhattan.txt -> haplotype.change.at.QTL.txt

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