PT - JOURNAL ARTICLE AU - Ajit Johnson Nirmal AU - Tim Regan AU - Barbara Bo-Ju Shih AU - David Arthur Hume AU - Andrew Harvey Sims AU - Tom Charles Freeman TI - <em>ImSig</em>: A resource for the identification and quantification of immune signatures in blood and tissue transcriptomics data AID - 10.1101/077487 DP - 2016 Jan 01 TA - bioRxiv PG - 077487 4099 - http://biorxiv.org/content/early/2016/09/26/077487.short 4100 - http://biorxiv.org/content/early/2016/09/26/077487.full AB - The outcome of many diseases is commonly correlated with the immune response at the site of pathology. The ability to monitor the status of the immune system in situ provides a mechanistic understanding of disease progression, a prognostic assessment and a guide for therapeutic intervention. Global transcriptomic data can be deconvoluted to provide an indication of the cell types present and their activation state, but the gene signatures proposed to date are either disease-specific or have been derived from data generated from isolated cell populations. Here we describe an improved set of immune gene signatures, ImSig, derived based on their co-expression in blood and tissue datasets. ImSig includes validated lists of marker genes for the main immune cell types and a number of core pathways. When used in combination with network analysis, ImSig is an accurate and easy to use approach for monitoring immune phenotypes in transcriptomic data derived from clinical samples.