Format

Send to

Choose Destination
Methods Mol Biol. 2012;802:389-98. doi: 10.1007/978-1-61779-400-1_26.

BiNGS!SL-seq: a bioinformatics pipeline for the analysis and interpretation of deep sequencing genome-wide synthetic lethal screen.

Author information

1
Division of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. Jihye.Kim@UCDenver.edu

Abstract

While targeted therapies have shown clinical promise, these therapies are rarely curative for advanced cancers. The discovery of pathways for drug compounds can help to reveal novel therapeutic targets as rational combination therapy in cancer treatment. With a genome-wide shRNA screen using high-throughput genomic sequencing technology, we have identified gene products whose inhibition synergizes with their target drug to eliminate lung cancer cells. In this chapter, we described BiNGS!SL-seq, an efficient bioinformatics workflow to manage, analyze, and interpret the massive synthetic lethal screen data for finding statistically significant gene products. With our pipeline, we identified a number of druggable gene products and potential pathways for the screen in an example of lung cancer cells.

PMID:
22130895
DOI:
10.1007/978-1-61779-400-1_26
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Springer
Loading ...
Support Center