Paul Datlinger, André F Rendeiro*, Christian Schmidl*, Thomas Krausgruber, Peter Traxler, Johanna Klughammer, Linda C Schuster, Amelie Kuchler, Donat Alpar, Christoph Bock. (2017) Nature Methods. doi:10.1038/nmeth.4177
*These authors contributed equally to this work
Paper: http://dx.doi.org/10.1038/nmeth.4177
Website: http://crop-seq.computational-epigenetics.org
This repository contains scripts used in the analysis of the data of the data presented in this paper. Future updates will be shared at https://github.com/epigen/crop-seq/.
On the paper website you can find the key results of the bioinformatic analysis.
Here are a few steps needed to reproduce it:
- Clone the repository (
git clone git@github.com:epigen/crop-seq.git
) or download it from here: https://github.com/epigen/crop-seq/releases/tag/final_version - Install required software for the analysis:
make requirements
orpip install -r requirements.txt
- This includes looper (v0.7.2) [and pypiper (v0.6) - if you want to rerun the raw data].
If you wish to reproduce the processing of the raw data (all data have been deposited at GEO), run these steps:
- Download the data locally from GEO.
- Prepare a Looper configuration file similar to these that fits your local computing environment.
- Prepare a genome annotation containing gRNA sequences using
make makeref
and adapt the pipeline configuration file to point to the created files. - Run samples through the pipeline:
make preprocessing
orlooper run metadata/config.yaml
To run the analysis, you can either use the output from reprocessed data (make analysis
) or download the gene expression matrices that include cell metadata (replicate, perturbed gene, gRNA assignments) from GEO with accession number GSE92872.