| Literature DB >> 25428347 |
Aaron A Diaz1, Han Qin2, Miguel Ramalho-Santos3, Jun S Song4.
Abstract
Genetic screens of an unprecedented scale have recently been made possible by the availability of high-complexity libraries of synthetic oligonucleotides designed to mediate either gene knockdown or gene knockout, coupled with next-generation sequencing. However, several sources of random noise and statistical biases complicate the interpretation of the resulting high-throughput data. We developed HiTSelect, a comprehensive analysis pipeline for rigorously selecting screen hits and identifying functionally relevant genes and pathways by addressing off-target effects, controlling for variance in both gene silencing efficiency and sequencing depth of coverage and integrating relevant metadata. We document the superior performance of HiTSelect using data from both genome-wide RNAi and CRISPR/Cas9 screens. HiTSelect is implemented as an open-source package, with a user-friendly interface for data visualization and pathway exploration. Binary executables are available at http://sourceforge.net/projects/hitselect/, and the source code is available at https://github.com/diazlab/HiTSelect.Entities:
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Year: 2014 PMID: 25428347 PMCID: PMC4330337 DOI: 10.1093/nar/gku1197
Source DB: PubMed Journal: Nucleic Acids Res ISSN: 0305-1048 Impact factor: 16.971