ArticleBioinformatics advances2022
metaLINCS: an R package for meta-level analysis of LINCS L1000 drug signatures using stratified connectivity mapping.
Article in Bioinformatics advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 4 citations in OpenAlex.
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- Comprehensive characterization of AP-1 adaptor complex genes in lung cancer reveals AP1AR as a novel prognostic and therapeutic biomarker.Journal of Cancer · 2026Article
- Blood molecular subtypes to guide precision treatment strategies in systemic juvenile idiopathic arthritis.Arthritis research & therapy · 2025Article
- Integration of multi-omics and single-cell transcriptome reveals mitochondrial outer membrane protein-2 (MTX-2) as a prognostic biomarker and characterizes ubiquinone metabolism in lung adenocarcinoma.Journal of Cancer · 2025Article
- A comparative analysis of Marburg virus-infected bat and human models from public high-throughput sequencing data.International journal of medical sciences · 2025Article
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Authors and funding
4 authors.
Funding
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Abstract
Summary: Accessing the collection of perturbed gene expression profiles, such as the LINCS L1000 connectivity map, is usually performed at the individual dataset level, followed by a summary performed by counting individual hits for each perturbagen. With the metaLINCS R package, we present an alternative approach that combines rank correlation and gene set enrichment analysis to identify meta-level enrichment at the perturbagen level and, in the case of drugs, at the mechanism of action level. This significantly simplifies the interpretation and highlights overarching themes in the data. We demonstrate the functionality of the package and compare its performance against those of three currently used approaches. Availability and implementation: metaLINCS is released under GPL3 license. Source code and documentation are freely available on GitHub (https://github.com/bigomics/metaLINCS). Supplementary information: Supplementary data are available at
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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.