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

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


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.

MeSH terms

  • Antineoplastic Agents / pharmacology
  • Chromosome Mapping
  • Computer Simulation
  • Genomics / methods*
  • High-Throughput Nucleotide Sequencing*
  • High-Throughput Screening Assays*
  • Humans
  • Lung Neoplasms / genetics
  • RNA Interference*
  • RNA, Small Interfering / genetics
  • Signal Transduction / drug effects


  • Antineoplastic Agents
  • RNA, Small Interfering