DRUG-seq

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DRUG (Digital RNA with pertUrbation of Genes)-seq data analysis pipeline

DRUG-seq 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# DRUG-seq
DRUG (Digital RNA with pertUrbation of Genes)-seq data analysis pipeline

## Introduction
Unbiased transcriptomic RNA-seq data has provided deep insights about biological processes. However, its impact in drug discovery has been narrow given high costs and low throughput. Proof-of-concept studies with Digital RNA with pertUrbation of Genes (DRUG)-seq demonstrated the potential to address this gap. We extended the DRUG-seq platform by subjecting it to rigorous testing and by adding an open-source analysis pipeline. The results demonstrate high reproducibility and ability to resolve the mechanism(s) of action for a diverse set of compounds. Overall, the protocol and open-source analysis pipeline are a step towards industrializing RNA-seq for high complexity transcriptomics studies performed at a saturating scale.
## Description
Raw data is available in [GEO](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi). Both Counts data and meta data are available in the data folder of the repo. After cloning the repo, run DRUG-seq_data_analysis_pipeline.Rmd and all results will be saved in a folder called out. 
## Data analysis pipeline
Check our [paper](https://www.biorxiv.org/content/10.1101/2021.06.07.447456v1) for additional information.
![DRUG-Seq data analysis pipeline](https://raw.githubusercontent.com/Novartis/DRUG-seq/main/DRUG-seq_data_analysis_flow_chart.png)

## Publication
If you are interest in using DRUG-seq in your research, please cite our publication:
```
@article {Li2021.06.07.447456,
	author = {Li, Jingyao and Ho, Daniel J and Henault, Martin and Yang, Chian and Neri, Marilisa and Ge, Robin and Renner, Steffen and Mansur, Leandra and Lindeman, Alicia and Tumkaya, Tayfun and Russ, Carsten and Hild, Marc and Gubser Keller, Caroline and Jenkins, Jeremy L and Worringer, Kathleen A and Sigoillot, Frederic D. and Ihry, Robert J},
	title = {DRUG-seq Provides Unbiased Biological Activity Readouts for Drug Discovery},
	elocation-id = {2021.06.07.447456},
	year = {2021},
	doi = {10.1101/2021.06.07.447456},
	publisher = {Cold Spring Harbor Laboratory},
	URL = {https://www.biorxiv.org/content/early/2021/06/08/2021.06.07.447456},
	eprint = {https://www.biorxiv.org/content/early/2021/06/08/2021.06.07.447456.full.pdf},
	journal = {bioRxiv}
}
```

DRUG-seq

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