Reference-free transcriptome signatures for prostate cancer prognosis.

ABSTRACT:

Background

RNA-seq data are increasingly used to derive prognostic signatures for cancer outcome prediction. A limitation of current predictors is their reliance on reference gene annotations, which amounts to ignoring large numbers of non-canonical RNAs produced in disease tissues. A recently introduced kind of transcriptome classifier operates entirely in a reference-free manner, relying on k-mers extracted from patient RNA-seq data.

Methods

In this paper, we set out to compare conventional and reference-free signatures in risk and relapse prediction of prostate cancer. To compare the two approaches as fairly as possible, we set up a common procedure that takes as input either a k-mer count matrix or a gene expression matrix, extracts a signature and evaluates this signatu

SUBMITTER: Nguyen HTN 

PROVIDER: S-EPMC8040209 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature