Genomics & Informatics

Korea Genome Organization (한국유전체학회)
권호 표지
DOI QR코드

DOI QR Code

BaSDAS: a web-based pooled CRISPR-Cas9 knockout screening data analysis system

  • Park, Young-Kyu (OmicsPia Co., Ltd.) ;
  • Yoon, Byoung-Ha (Personalized Genomic Medicine Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB)) ;
  • Park, Seung-Jin (Personalized Genomic Medicine Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB)) ;
  • Kim, Byung Kwon (OmicsPia Co., Ltd.) ;
  • Kim, Seon-Young (Personalized Genomic Medicine Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB))
  • Received : 2020.08.18
  • Accepted : 2020.09.24
  • Published : 2020.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

We developed the BaSDAS (Barcode-Seq Data Analysis System), a GUI-based pooled knockout screening data analysis system, to facilitate the analysis of pooled knockout screen data easily and effectively by researchers with limited bioinformatics skills. The BaSDAS supports the analysis of various pooled screening libraries, including yeast, human, and mouse libraries, and provides many useful statistical and visualization functions with a user-friendly web interface for convenience. We expect that BaSDAS will be a useful tool for the analysis of genome-wide screening data and will support the development of novel drugs based on functional genomics information.

Keywords

Acknowledgement

This research was supported by the National Research Foundation of Korea (NRF) grant (NRF-2014M3C9A3068554 and NRF-2017MBA9B5060884) funded by the Korea government (MST) and a grant from the KRIBB Research Initiative Program.

References

  1. Carpenter AE, Sabatini DM. Systematic genome-wide screens of gene function. Nat Rev Genet 2004;5:11-22. https://doi.org/10.1038/nrg1248
  2. Smith AM, Heisler LE, Mellor J, Kaper F, Thompson MJ, Chee M, et al. Quantitative phenotyping via deep barcode sequencing. Genome Res 2009;19:1836-1842. https://doi.org/10.1101/gr.093955.109
  3. Sims D, Mendes-Pereira AM, Frankum J, Burgess D, Cerone MA, Lombardelli C, et al. High-throughput RNA interference screening using pooled shRNA libraries and next generation sequencing. Genome Biol 2011;12:R104. https://doi.org/10.1186/gb-2011-12-10-r104
  4. Eason RG, Pourmand N, Tongprasit W, Herman ZS, Anthony K, Jejelowo O, et al. Characterization of synthetic DNA bar codes in Saccharomyces cerevisiae gene-deletion strains. Proc Natl Acad Sci U S A 2004;101:11046-11051. https://doi.org/10.1073/pnas.0403672101
  5. Kim DU, Hayles J, Kim D, Wood V, Park HO, Won M, et al. Analysis of a genome-wide set of gene deletions in the fission yeast Schizosaccharomyces pombe. Nat Biotechnol 2010;28:617-623. https://doi.org/10.1038/nbt.1628
  6. Parnas O, Jovanovic M, Eisenhaure TM, Herbst RH, Dixit A, Ye CJ, et al. A genome-wide CRISPR screen in primary immune cells to dissect regulatory networks. Cell 2015;162:675-686. https://doi.org/10.1016/j.cell.2015.06.059
  7. Li W, Xu H, Xiao T, Cong L, Love MI, Zhang F, et al. MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens. Genome Biol 2014;15:554. https://doi.org/10.1186/s13059-014-0554-4
  8. Wang B, Wang M, Zhang W, Xiao T, Chen CH, Wu A, et al. Integrative analysis of pooled CRISPR genetic screens using MAGe CKFlute. Nat Protoc 2019;14:756-780. https://doi.org/10.1038/s41596-018-0113-7