clusterSeq: methods for identifying co-expression in high-throughput sequencing data

Hardcastle, T. J.; Papatheodorou, I.

doi:10.1101/188581

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bioRxiv · 10.1101/188581

clusterSeq: methods for identifying co-expression in high-throughput sequencing data

Hardcastle, T. J.·Papatheodorou, I.

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Abstract

Summary:Identifying gene co-expression is a significant step in understanding functional relationships between genes. Existing methods primarily depend on analyses of correlation between pairs of genes; however, this neglects structural elements between experimental conditions. We present a novel approach to identifying clusters of co-expressed genes that incorporates these structures.\n\nAvailability:The methods are released on Bioconductor as the clusterSeq package (https://bioconductor.org/packages/release/bioc/html/clusterSeq.html).\n\nContact: tjh48@cam.ac.uk

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Hardcastle, T. J., Papatheodorou, I.. 2017-09-13. clusterSeq: methods for identifying co-expression in high-throughput sequencing data. https://doi.org/10.1101/188581

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