Source for paper, "Identification and correction of sample mix-ups in expression genetic data: A case study"
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Analysis
Figs
ProcessedFiles
R
SuppFigs
SuppTables
.gitignore
Makefile
ReadMe.md
add_legends.pl
genetics.bst
legends.txt
samplemixups.bib
samplemixups_nolegends.Rnw
samplemixups_supp_nolegends.tex

ReadMe.md

Paper: Identification and correction of sample mix-ups in expression genetic data

The full manuscript (with supplementary tables and figures) is here.

The paper will appear at G3, and is also available at arXiv.

I'm still working out how to include the data, or links to the data (because they're about 2 GB compressed). At the moment, this isn't fully reproducible.

The data are available at the Mouse Phenome Database, though not in exactly the form used in this repository.

The primary manuscript files are samplemixups_nolegends.Rnw and samplemixups_supp_nolegends.tex.

The Perl script add_legends.pl adds all of the legends, and then the .Rnw file is run through knitr to create a LaTeX file, and the two LaTeX files are sent through pdflatex and xelatex, respectively, to create PDFs.

The Makefile tells the full story.

The Analysis/R subdirectory has an asciidoc file for the analyses in the work. That directory has its own Makefile.

Cached intermediate results are available at figshare: samplemixups_rcache.zip (This contains a bunch of .RData files that go in Analysis/R/Rcache.)


Necessary tools

  • R
  • Perl
  • Python 2.7
  • GNU make
  • Asciidoc
  • R packages: knitr, qtl, broman, lineup, ascii, data.table, igraph, beeswarm, RColorBrewer

To Do

  • Do clean tests, with and without the intermediate files