Detecting independent and recurrent copy number aberrations using interval graphs

Abstract

Motivation: Somatic copy number aberrations (SCNAs) are frequent in cancer genomes, but many of these are random, passenger events. A common strategy to distinguish functional aberrations from passengers is to identify those aberrations that are recurrent across multiple samples. However, the extensive variability in the length and position of SCNAs makes the problem of identifying recurrent aberrations notoriously difficult.Results: We introduce a combinatorial approach to the problem of identifying independent and recurrent SCNAs, focusing on the key challenging of separating the overlaps in aberrations across individuals into independent events. We derive independent and recurrent SCNAs as maximal cliques in an interval graph constructed from overlaps between aberrations. We efficiently enumerate all such cliques, and derive a dynamic programming algorithm to find an optimal selection of non-overlapping cliques, resulting in a very fast algorithm, which we call RAIG (Recurrent Aberrations from Interval Graphs). We show that RAIG outperforms other methods on simulated data and also performs well on data from three cancer types from The Cancer Genome Atlas (TCGA). In contrast to existing approaches that employ various heuristics to select independent aberrations, RAIG optimizes a well-defined objective function. We show that this allows RAIG to identify rare aberrations that are likely functional, but are obscured by overlaps with larger passenger aberrations.Availability: http://compbio.cs.brown.edu/software.Contact: braphael@brown.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Rsu1 contributes to cell adhesion and spreading in MCF10A cells via effects on P38 map kinase signaling

“…In addition to MKK4 deletion or mutation in tumors, the loss of Rsu1 activity may interfere with MKK4 signaling and thereby contribute to the loss of tumor suppressor activity. Genomic deletions in Rsu1 have been detected in both a subset of human hepatocellular carcinomas as well as in gliomas 65,66 , and according to recent reports the depletion of Rsu1 in prostate tumors occurs via stroma-produced miRs. 67,68 Hence, the connection of Rsu1 to MKK4, p38, Jun kinase and ATF2 may be a potential regulatory event in tumorigenesis.…”

Model‐based and data‐driven with multiscale sum of squares double EWMA control chart for fault detection in biological systems

“…The existence of copy number irregularities is frequent in many genomic illnesses especially the genomes of cancer. () Nevertheless, the majority of such irregularities occurs unsystematically with a risk of being unrecognizable . One of the empirical techniques adopted in inspecting the data of DNA is the microarray comparative genomic hybridization.…”

DGPathinter: a novel model for identifying driver genes via knowledge-driven matrix factorization with prior knowledge from interactome and pathways

“…The cancer specific genes from the two benchmarking gene lists are used to assess the prioritizing results of the investigated methods. By using these benchmarking genes as ground truth genes in the evaluation studies, we firstly compute the precisions and recalls under different rank thresholds and draw precision-recall curves of the competing methods, where a curve closer to the top and right indicates a better performance (Wu, Hajirasouliha & Raphael, 2014;Yang et al, 2017). The precision is calculated as the fraction of selected genes that are also benchmarking genes, and the recall is computed as the fraction of benchmarking genes that are selected by the rank threshold.…”