stefanches/genomic-bioimaging

Clustering phenotype populations by genome-wide RNAi and multiparametric imaging

52224 images of a high-content RNAi knockdown screening.

Author one-liner: "To cluster genes and predict function on a genome-wide scale, we measured the effects of 22 839 siRNA-mediated knockdowns on HeLa cells. Each siRNA effect was summarized by a phenotypic profile."

Dataset Details

Organism: human (Homo sapiens) Cell type: HeLa Imaging method: Fluorescence microscopy

Study metadata: metadata/S-EPMC2913390.json - authors and IDs (BioStudies extract); metadata/msb201025-s1.pdf - Supplementary information (incl. variable definitions); metadata/msb201025-s1.xls - biological process annotation for some wells.

Dataset Description

Genetic screens for phenotypic similarity have made key contributions to associating genes with biological processes. With RNA interference (RNAi), highly parallel phenotyping of loss-of-function effects in cells has become feasible. One of the current challenges however is the computational categorization of visual phenotypes and the prediction of biological function and processes. In this study, we describe a combined computational and experimental approach to discover novel gene functions and explore functional relationships. We performed a genome-wide RNAi screen in human cells and used quantitative descriptors derived from high-throughput imaging to generate multiparametric phenotypic profiles. We show that profiles predicted functions of genes by phenotypic similarity. Specifically, we examined several candidates including the largely uncharacterized gene DONSON, which shared phenotype similarity with known factors of DNA damage response (DDR) and genomic integrity. Experimental evidence supports that DONSON is a novel centrosomal protein required for DDR signalling and genomic integrity. Multiparametric phenotyping by automated imaging and computational annotation is a powerful method for functional discovery and mapping the landscape of phenotypic responses to cellular perturbations.

• Curated by: University of Dundee
• Funded by: IDR: BBSRC (Ref: BB/M018423/1), 688945 (Euro-BioImaging Prep Phase II), 653493 (Global BioImaging Project), 654248 (CORBEL), Wellcome Trust (Ref: 212962/Z/18/Z)
• Shared by: IDR, Stefan Dvoretskii ([email protected])
• License: CC BY-NC-ND 4.0

Dataset Sources

• Repository: IDR, Bioimage Archive,
• Paper [optional]: Clustering phenotype populations by genome‐wide RNAi and multiparametric imaging

Uses

Machine Learning pipelines for Bioimaging, drug screening data.

Dataset Structure

Dataset is structured in High-Content-Screening structure of OMERO. Images are 16-bit PNG converted from OME-Zarr. NB!: be aware of automatic 8-bit conversion by image tools, e.g. OpenCV!

Metadata is provided in the tabular format (CSV) as well as JSON-LD objects.

Dataset Creation

Curation Rationale

Bioimaging and drug screening is cool, and HuggingFace lacks that!

Source Data

More information on experiments

Data Collection and Processing

Data collection overview

Who are the source data producers?

Florian Fuchs, Gregoire Pau, Dominique Kranz, Oleg Sklyar, Christoph Budjan, Sandra Steinbrink, Thomas Horn, Angelika Pedal, Wolfgang Huber [email protected], and Michael Boutros

Annotations [optional]

Annotation files on Github

Annotation process

https://idr.openmicroscopy.org/about/screens.html

Who are the annotators?

IDR staff and original scientists

Personal and Sensitive Information

No human PII / PHI has been noticed in the samples.

Bias, Risks, and Limitations

Experiments could have contained errors / artifacts. Please refer to the original paper for more details.

Recommendations

NB!: be aware of automatic 8-bit conversion by image tools, e.g. OpenCV!

Original Zarr files contain a better resolution / additional lazy loading capabilities.

Citation

BibTeX:

@article{fuchs2010clustering, title={Clustering phenotype populations by genome-wide RNAi and multiparametric imaging}, author={Fuchs, Florian and Pau, Gregoire and Kranz, Dominique and Sklyar, Oleg and Budjan, Christoph and Steinbrink, Sandra and Horn, Thomas and Pedal, Angelika and Huber, Wolfgang and Boutros, Michael}, journal={Molecular systems biology}, volume={6}, number={1}, pages={370}, year={2010}, publisher={John Wiley & Sons, Ltd Chichester, UK} }

APA:

Fuchs, F., Pau, G., Kranz, D., Sklyar, O., Budjan, C., Steinbrink, S., ... & Boutros, M. (2010). Clustering phenotype populations by genome‐wide RNAi and multiparametric imaging. Molecular systems biology, 6(1), 370.

Glossary

IDR glossary Google doc

More Information

IDR annotation

Dataset Card Contact

Stefan Dvoretskii