ArticleSLAS discovery : advancing life sciences R & D2021
Comparison of Approaches for Determining Bioactivity Hits from High-Dimensional Profiling Data.
Article in SLAS discovery : advancing life sciences R & D, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed, 43 citations in OpenAlex.
- Progress and new challenges in image-based profiling.Molecular systems biology · 2026Review
- Single-cell hit calling in high-content imaging screens with Buscar.bioRxiv : the preprint server for biology · 2026Article
- Cell Painting PLUS: An Iterative Staining-Elution Protocol for High-Content Phenotypic Screenings.Current protocols · 2026Article
- Analyzing Cell Painting PLUS Data Using Cell Profiler and KNIME Analytics Platform.Methods in molecular biology (Clifton, N.J.) · 2026Article
- The OASIS Consortium: integrating multi-omics technologies to transform chemical safety assessment.Toxicological sciences : an official journal of the Society of Toxicology · 2025Article
- Statistical analysis of multi-endpoint phenotypic screening increases sensitivity of planarian neurotoxicity testing.Toxicological sciences : an official journal of the Society of Toxicology · 2025Article
- Assessing the impact of in vitro xenobiotic metabolism on estrogenic chemical bioactivity in high-throughput profiling assays.Toxicology · 2025Article
- Smaller scale, same impact: replicating high-throughput phenotypic profiling in a medium-throughput lab for use in chemical risk assessment.Archives of toxicology · 2025Article
- Article
- Improvement in Transient Agarose Spot (TAS) Cell Migration Assay: Microplate-Based Detection and Evaluation.International journal of molecular sciences · 2025Article
- Cell Painting PLUS: expanding the multiplexing capacity of Cell Painting-based phenotypic profiling using iterative staining-elution cycles.Nature communications · 2025Article
- Cell Painting: a decade of discovery and innovation in cellular imaging.Nature methods · 2025Review
- Modeling omics dose-response at the pathway level with DoseRider.Computational and structural biotechnology journal · 2025Article
- Bayesian gene set benchmark dose estimation for "omic" responses.Bioinformatics (Oxford, England) · 2024Article
- High-Throughput Transcriptomics Screen of ToxCast Chemicals in U-2 OS Cells.Toxicology and applied pharmacology · 2024Article
- Community-Engaged Research and the Use of Open Access ToxVal/ToxRef In Vivo Databases and New Approach Methodologies (NAM) to Address Human Health Risks From Environmental Contaminants.Birth defects research · 2024Article
- A Decade in a Systematic Review: The Evolution and Impact of Cell Painting.bioRxiv : the preprint server for biology · 2024Article
- Article
- A Comparison of In Vitro Points of Departure with Human Blood Levels for Per- and Polyfluoroalkyl Substances (PFAS).Toxics · 2024Article
- Investigating open access new approach methods (NAM) to assess biological points of departure: A case study with 4 neurotoxic pesticides.Current research in toxicology · 2024Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
Phenotypic profiling assays are untargeted screening assays that measure a large number (hundreds to thousands) of cellular features in response to a stimulus and often yield diverse and unanticipated profiles of phenotypic effects, leading to challenges in distinguishing active from inactive treatments. Here, we compare a variety of different strategies for hit identification in imaging-based phenotypic profiling assays using a previously published Cell Painting data set. Hit identification strategies based on multiconcentration analysis involve curve fitting at several levels of data aggregation (e.g., individual feature level, aggregation of similarly derived features into categories, and global modeling of all features) and on computed metrics (e.g., Euclidean and Mahalanobis distance metrics and eigenfeatures). Hit identification strategies based on single-concentration analysis included measurement of signal strength (e.g., total effect magnitude) and correlation of profiles among biological replicates. Modeling parameters for each approach were optimized to retain the ability to detect a reference chemical with subtle phenotypic effects while limiting the false-positive rate to 10%. The percentage of test chemicals identified as hits was highest for feature-level and category-based approaches, followed by global fitting, whereas signal strength and profile correlation approaches detected the fewest number of active hits at the fixed false-positive rate. Approaches involving fitting of distance metrics had the lowest likelihood for identifying high-potency false-positive hits that may be associated with assay noise. Most of the methods achieved a 100% hit rate for the reference chemical and high concordance for 82% of test chemicals, indicating that hit calls are robust across different analysis approaches.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.