1.
McQuin C, Goodman A, Chernyshev V, et al. CellProfiler 3.0: Next-generation image processing for biology. PLoS Biol. 2018;16(7):e2005970. doi:10.1371/journal.pbio.2005970.
1.
Sanghvi RV, Buhay CJ, Powell BC, et al. Characterizing reduced coverage regions through comparison of exome and genome sequencing data across 10 centers. Genet Med. 2018;20(8):855-866. doi:10.1038/gim.2017.192.
1.
Levet F, Carpenter AE, Eliceiri KW, Kreshuk A, Bankhead P, Haase R. Developing open-source software for bioimage analysis: opportunities and challenges. F1000Res. 2021;10:302. doi:10.12688/f1000research.52531.1.
1.
Lareau CA, Aryee MJ. diffloop: a computational framework for identifying and analyzing differential DNA loops from sequencing data. Bioinformatics. 2018;34(4):672-674. doi:10.1093/bioinformatics/btx623.
1.
Grüning B, Dale R, Sjödin A, et al. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods. 2018;15(7):475-476. doi:10.1038/s41592-018-0046-7.
1.
Zamanighomi M, Jain SS, Ito T, Pal D, Daley TP, Sellers WR. GEMINI: a variational Bayesian approach to identify genetic interactions from combinatorial CRISPR screens. Genome Biol. 2019;20(1):137. doi:10.1186/s13059-019-1745-9.
1.
Doan M, Barnes C, McQuin C, et al. Deepometry, a framework for applying supervised and weakly supervised deep learning to imaging cytometry. Nat Protoc. 2021;16(7):3572-3595. doi:10.1038/s41596-021-00549-7.
1.
Wang L, Yang Q, Jaimes A, et al. MightyScreen: An Open-Source Visualization Application for Screening Data Analysis. SLAS Discov. 2018;23(2):218-223. doi:10.1177/2472555217731983.
1.
Clement K, Farouni R, Bauer DE, Pinello L. AmpUMI: design and analysis of unique molecular identifiers for deep amplicon sequencing. Bioinformatics. 2018;34(13):i202-i210. doi:10.1093/bioinformatics/bty264.
1.
Sherman MA, Barton AR, Lodato MA, et al. PaSD-qc: quality control for single cell whole-genome sequencing data using power spectral density estimation. Nucleic Acids Res. 2018;46(4):e20. doi:10.1093/nar/gkx1195.