Alien Index: detect HGT and contamination in genomes

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The Alien Index (AI) is a sequence similarity based score to flag genes with significantly better hits to distantly related organisms than to closely related ones and thereby identify candidate HGT events as well as likely assembly contamination. aiViz, a tool for running an AI each and visualizing the results is available on our GitHub.

Publications that used the Alien Index: Gonçalves et al. 2018. eLife, Zhang et al. 2018. Scientific Reports, Wisecaver et al. 2016. MBE, Alexander et al. 2016. PNAS

Mutual Ranks and Modules: identify co-expressed gene sets

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Transforming Pearson’s correlations into Mutual Ranks (MRs) — first described by Obayashi & Kinoshita — is a good idea if you want to compare between different datasets and/or functional categories. However, MRs range from 1 to n (where n is the number of genes in the genome), which does not translate well to network edge weights, which typically range from 1 to 0. We’ve implemented exponential decay functions to transform MRs to edge weights and call co-expressed gene sets (i.e. modules) using the program ClusterONE. The full MR to modules workflow is available on on GitHub.

Publications that used our workflow: Wisecaver et al. 2017 Plant Cell.