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Code used to perform analyses and generate figures for Roth, Muench et. al.
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README.md

README.md

16p_resource

This repo contains the code used to generate analyses and generate figures for Roth, Muench et. al. This paper describes a new resource of patient-derived iPSCs bearing a 16p11.2 copy number variant, explores the potential utility of these clones, and describes the possible impact of clonal integration on iPSC-derived tissue models. I have written this README with other biologists in mind who might be interested in following up on our analyses or investigating their own integration effects.

It is divided into two sections. The directory "figure5" contains a differential expression analysis of the Integration-negative clones aligned with STAR and counted with htseq-count. The directory "figure6" contains an independent bioinformatic comparison of Integration-negative and Integration-positive clones aligned using kallisto.

Within each figure directory, the code is intended to be modular. You should run the code in this order:

Figure 5

  1. setup.Rmd
  2. deseq.Rmd

Figure 6

  1. tximport_setup.Rmd
  2. deseq.Rmd
  3. barPlots.Rmd OR heatmaps.Rmd OR GSEA.Rmd

This code is written to have a separate output file for each distinct date of run, when the date of run is defined within the userVars.csv file. This way, the user can maintain copies of all output as small tweaks are made to the code.

Getting Started

Prerequisites

For the alignment and counting steps, I used one of two different aligners

I performed both of these on the Stanford Center for Personalized Medicine Cluster. I recommend running STAR on a cluster. In theory, you should be able to run kallisto on a laptop.

I performed subsequent analyses using R and RStudio.

You will also need:

== Figure 5 ==

Setup

DESeq

  • In addition to the packages required for Setup, install the following

== Figure 6 ==

tximport_Setup

deseq

heatmaps

barPlots

  • In addition to the packages required for Setup, install the following

GSEA

Versioning

For the versions available, see the tags on this repository.

Authors

License

This project is licensed under the MIT License - see the license.txt file for details

Acknowledgments

  • Thank you to PurpleBooth for the README template
  • Thank you to the Bader Lab for their GSEA tutorial.
  • Thank you to John Hanks at the SCPGM cluster and the team at the Stanford Functional Genomics Facility for their help supporting this work.
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