ArticlePloS one2020
OpenStats: A robust and scalable software package for reproducible analysis of high-throughput phenotypic data.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- International Mouse Phenotyping Consortium Portal: facilitating investigation of gene function and providing insights into human disease.Nucleic acids research · 2026Article
- International Mouse Phenotyping Consortium: Investigating gene function and providing insights into human disease.bioRxiv : the preprint server for biology · 2025Article
- Identifying genetic determinants of outer retinal function in mice using a large-scale gene-targeted screen.PLoS genetics · 2025Article
- Multi-omics analysis highlights the link of aging-related cognitive decline with systemic inflammation and alterations of tissue-maintenance.bioRxiv : the preprint server for biology · 2025Article
- Article
- Investigating the effects of a cryptic splice site in the En2 splice acceptor sequence used in the IKMC knockout-first alleles.Mammalian genome : official journal of the International Mammalian Genome Society · 2024Article
- Computational identification of disease models through cross-species phenotype comparison.Disease models & mechanisms · 2024Article
- A consensus score to combine inferences from multiple centres.Mammalian genome : official journal of the International Mammalian Genome Society · 2023Article
- Knockout mice are an important tool for human monogenic heart disease studies.Disease models & mechanisms · 2023Article
- Genome-wide screening reveals the genetic basis of mammalian embryonic eye development.BMC biology · 2023Article
- KOMPUTE: imputing summary statistics of missing phenotypes in high-throughput model organism data.Bioinformatics advances · 2023Article
- Article
- Pleiotropy data resource as a primer for investigating co-morbidities/multi-morbidities and their role in disease.Mammalian genome : official journal of the International Mammalian Genome Society · 2022Article
- Extensive identification of genes involved in congenital and structural heart disorders and cardiomyopathy.Nature cardiovascular research · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Reproducibility in the statistical analyses of data from high-throughput phenotyping screens requires a robust and reliable analysis foundation that allows modelling of different possible statistical scenarios. Regular challenges are scalability and extensibility of the analysis software. In this manuscript, we describe OpenStats, a freely available software package that addresses these challenges. We show the performance of the software in a high-throughput phenomic pipeline in the International Mouse Phenotyping Consortium (IMPC) and compare the agreement of the results with the most similar implementation in the literature. OpenStats has significant improvements in speed and scalability compared to existing software packages including a 13-fold improvement in computational time to the current production analysis pipeline in the IMPC. Reduced complexity also promotes FAIR data analysis by providing transparency and benefiting other groups in reproducing and re-usability of the statistical methods and results. OpenStats is freely available under a Creative Commons license at www.bioconductor.org/packages/OpenStats.
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What OpenQuestion holds
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.