Journal article

Defining a landscape of molecular phenotypes using a simple single sample scoring method

Momeneh Foroutan, Dharmesh Bhuva, Kristy Horan, Ruqian Lyu, Joseph Cursons, Melissa Davis

Published : 2017


Abstract Background Gene set scoring provides a useful approach for quantifying concordance between sample transcriptomes and selected molecular signatures. Most methods use information from all samples to score an individual sample, leading to unstable scores in small data sets and introducing biases from sample composition across a data set (e.g. varying numbers of samples for different cancer subtypes). To address these issues we have developed a truly single sample scoring method, and associated R/Bioconductor package singscore . Results We have developed a rank-based single sample scoring method, implemented as a Bioconductor package. We use multiple cancer data sets to compare it again..

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University of Melbourne Researchers

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