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Code for Walker, Saunders, Rai et al., (2021).

If you use the code or data from this repository, please cite our manuscript as described in CITATION.cff or using GitHub's Cite this repository link shown on the right.

Instructions

Due to complexity of many unique analyses and sensitivity of raw data, this repository cannot be run in a "one-click-all" fashion. If you wish to reproduce results from our manuscript, please first request access to the raw data from the European Genome-Phenome Archive (EGA) submission.

Once raw data is available, there are three broad topics of analyses:

  • Bulk RNA-seq
  • Multiome RNA and ATAC
  • Integration of the data modalities

These analyses are done in the following directories:

.
├── CITATION.cff
├── multiome_mapping-qc
│   ├── main --> Processing of "main" batch of Multiome
│   └── pilot --> Processing of the "pilot" batch of Multiome
├── rnaseq --> Processing of the bulk RNA-seq data
│   ├── bin
│   ├── control
│   ├── Rakefile
│   ├── scripts
│   └── src

Directory organization

Most of the analysis directories are managed using, makebio, a tool for managing computational biology projects.

For example, the rnaseq analysis directory has the following structure:

rnaseq
├── bin
├── control
├── Rakefile
├── scripts
└── src
  1. src/ - source code corresponding to external packages, if used
  2. control/ - contains distinct "sets" of analyses
  3. scripts/ - Rmd notebooks, scripts
  4. bin/ - Executable scripts used by different components of the pipeline
  5. Rakefile - Driver script

In order to run an analyses, please inspect the Rakefile driver script first. That should give you an idea of how to execute each analyses. Within control/ directory, different analyses are contained in distinct directories with each having similar structure. Please ensure that appropriate data paths and variables are set before running any code.

Data Access

Raw data submission to European Genome-Phenome Archive (EGA) is in progress (RRID:SCR_004944).

Contact

Please reach out to Steve Parker for any data and code related questions.