Data Standards and Data Reproducibility
The LSP is strongly committed to FAIR (Findable, Accessible, Interoperable and Reusable) research.
We thoughtfully consider the factors that influence the reproducibility of laboratory-based research findings and advocate for solutions through publications and a seminar series that features speakers at the cutting edge of data and knowledge management. Whenever feasible, LSP results and software are open-source, and data is available under public domain (i.e., Creative Commons) licenses.
LSP investigators have studied the irreproducibility of preclinical drug response and pharmacodynamic data in detail (Niepel, 2019) and developed multiple methods to address the problem (Hafner, 2016; Mills, 2022), commented on the importance of public data release for reproducibility (AlQuraishi, 2016), and developed methods to liberate survival data about from clinical trials from pictorial representations (Plana, 2022). In the emerging field of multiplexed imaging, we have created open-source data processing pipelines to increase the reliability of complex data analysis (Schapiro, 2022a), developed a metadata scheme for standardizing the description of tissue images (Schapiro, 2022b), and developed the first quality control software for high-plex imaging data (Baker, 2024). These efforts underline the lab’s strong commitment to FAIR data practices and data reproducibility in general.
Relevant publications:
AlQuraishi M, Sorger PK. Reproducibility will only come with data liberation. Sci Transl Med. 2016 May 18;8(339):339ed7. DOI: 10.1126/scitranslmed.aaf0968. PMCID: PMC5084089.
Hafner M, Niepel M, Chung M, Sorger PK. Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs. Nat Methods. 2016 Jun 1;13(6):521–527. DOI:10.1038/nmeth.3853. PMCID: PMC4887336.
Mills CE, Subramanian K, Hafner M, Niepel M, Gerosa L, Chung M, Victor C, Gaudio B, Yapp C, Nirmal AJ, Clark N, Sorger PK. Multiplexed and reproducible high content screening of live and fixed cells using Dye Drop. Nat Commun. 2022 Nov 14;13(1):6918. DOI: 10.1038/s41467-022-34536-7. PMCID: PMC9663587.
Niepel M, Hafner M, Mills CE, Subramanian K, Williams EH, Chung M, Gaudio B, Barrette AM, Stern AD, Hu B, Korkola JE, LINCS Consortium, Gray JW, Birtwistle MR, Heiser LM, Sorger PK. A Multi-center Study on the Reproducibility of Drug-Response Assays in Mammalian Cell Lines. Cell Syst. 2019 Jul 5;9(1):35-48.e5. DOI: 10.1016/j.cels.2019.06.005. PMCID: PMC6700527.
Plana D, Fell G, Alexander BM, Palmer AC, Sorger PK. Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects. Nat Commun. 2022 Feb 15;13(1):873. DOI: 10.1038/s41467-022-28410-9. PMCID: PMC8847344.
Schapiro D, Sokolov A, Yapp C, Chen YA, Muhlich JL, Hess J, Creason AL, Nirmal AJ, Baker GJ, Nariya MK, Lin JR, Maliga Z, Jacobson CA, Hodgman MW, Ruokonen J, Farhi SL, Abbondanza D, McKinley ET, Persson D, Betts C, Sivagnanam S, Regev A, Goecks J, Coffey RJ, Coussens LM, Santagata S, Sorger PK. MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging. Nat Methods. 2022 Mar;19(3):311–315. DOI: 10.1038/s41592-021-01308-y. PMCID: PMC8916956.
Schapiro D, Yapp C, Sokolov A, Reynolds SM, Chen YA, Sudar D, Xie Y, Muhlich J, Arias-Camison R, Arena S, Taylor AJ, Nikolov M, Tyler M, Lin JR, Burlingame EA, Human Tumor Atlas Network, Chang YH, Farhi SL, Thorsson V, Venkatamohan N, Drewes JL, Pe’er D, Gutman DA, Herrmann MD, Gehlenborg N, Bankhead P, Roland JT, Herndon JM, Snyder MP, Angelo M, Nolan G, Swedlow JR, Schultz N, Merrick DT, Mazzili SA, Cerami E, Rodig SJ, Santagata S, Sorger PK. MITI minimum information guidelines for highly multiplexed tissue images. Nat Methods. 2022 Mar;19(3):262–267. DOI: 10.1038/s41592-022-01415-4. PMCID: PMC9009186.
Baker GJ, Novikov E, Zhao Z, Vallius T, Davis JA, Lin JR, Muhlich JL, Mittendorf EA, Santagata S, Guerriero JL, Sorger PK. Quality Control for Single Cell Analysis of High-plex Tissue Profiles using CyLinter. bioRxiv. 2023. DOI: 10.1101/2023.11.01.565120. PMCID: PMC10634977.