title: Quantification of read species behavior within whole genome sequencing of cancer genomes for the stratification and visualization of genomic variation.
abstract: The cancer genome is abnormal genome, and the ability to monitor its sequence had undergone a technological revolution. Yet prognosis and diagnosis remain an expert-based decision, with only limited abilities to provide machine-based decisions. We introduce a heterogeneity-based method for stratifying and visualizing whole-genome sequencing (WGS) reads. This method uses the heterogeneity within WGS reads to markedly reduce the dimensionality of next-generation sequencing data; it is available through the tool HiBS (Heterogeneity-Based Subclassification) that allows cancer sample classification. We validated HiBS using >200 WGS samples from nine different cancer types from The Cancer Genome Atlas (TCGA). With HiBS, we show progress with two WGS related issues: (i) differentiation between normal (NB) and tumor (TP) samples based solely on the information structure of their WGS data, and (ii) identification of specific regions of chromosomal amplification/deletion and their association with tumor stage. By comparing results to those obtained through available WGS analyses tools, we demonstrate some of the novelties obtained by the approach implemented in HiBS and also show nearly perfect normal/tumor classification, used to identify known and unknown chromosomal aberrations. Finally, the HiBS index has been associated with breast cancer tumor stage.
authors.affiliation: Faculty of Life Sciences, Bar-Ilan University, Ramat Gan 52900, Israel.
authors.forename: Dror
authors.initials: D
authors.lastname: Hibsh
authors.affiliation: Computational Sciences and Informatics Program, Complex Adaptive Systems Initiative, Arizona State University, Tempe AZ 85281, USA.
authors.forename: Kenneth H
authors.initials: KH
authors.lastname: Buetow
authors.affiliation: Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel.
authors.forename: Gur
authors.initials: G
authors.lastname: Yaari
authors.affiliation: Faculty of Life Sciences, Bar-Ilan University, Ramat Gan 52900, Israel sol.efroni@biu.ac.il.
authors.forename: Sol
authors.initials: S
authors.lastname: Efroni
mesh_terms: D000465:Algorithms; D019313:BRCA1 Protein / Q000235:genetics; D024682:BRCA2 Protein / Q000235:genetics; D001483:Base Sequence; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000235:genetics* / Q000401:mortality; D019295:Computational Biology / Q000379:methods*; D015894:Genome, Human / Q000235:genetics*; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D006801:Humans; D009367:Neoplasm Staging; D017422:Sequence Analysis, DNA / Q000379:methods
chemical_list: D019313:BRCA1 Protein; C492913:BRCA1 protein, human; D024682:BRCA2 Protein; C551750:BRCA2 protein, human
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