article Open AccessTop 1% cited
variancePartition: interpreting drivers of variation in complex gene expression studies
BMC Bioinformatics · 2016 · Vol. 17(1) · pp. 483–483
Gabriel E. Hoffman✉(Icahn School of Medicine at Mount Sinai)Eric E. Schadt(Icahn School of Medicine at Mount Sinai)
Abstract
Our open source software, variancePartition, enables rapid interpretation of complex gene expression studies as well as other high-throughput genomics assays. variancePartition is available from Bioconductor: http://bioconductor.org/packages/variancePartition .
Gene expression and cancer classificationGenetic and phenotypic traits in livestockGenetic Mapping and Diversity in Plants and AnimalsDNA microarrayVariation (astronomy)Gene expressionComputational biologyBiologyExpression (computer science)GeneGeneticsGene expression profilingBioinformatics
MeSH terms
AlgorithmsGene Expression RegulationHumansSoftwareGenetic VariationLinear ModelsSequence Analysis, RNAComputational BiologyGene Expression ProfilingGenomicsHigh-Throughput Nucleotide Sequencing
Funding
- Icahn School of Medicine at Mount Sinai
- National Institutes of Health
- National Institute on Aging
- National Heart, Lung, and Blood Institute
Citations
848
FWCI
15.49
field-weighted impact
References
62
Percentile
99%
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