A collection of 27 papers from The Cancer Genome Atlas (TCGA) consortium has been published reporting on the integrated project to analyze all 33 cancer types and to classify mutations and specific pathways. Many of the papers feature significant contributions from Baylor College of Medicine and its Human Genome Sequencing Center researchers. The findings from the 11,000 patient cohort data appear in Cell publications.
In a study published in BMC Bioinformatics, researchers from Baylor College of Medicine’s Human Genome Sequencing Center, along with Oak Ridge National Laboratory, DNAnexus and the Human Genetics Center at the University of Texas Health Science Center, have developed a novel hybrid computational strategy to address the growing need for scalable, cost effective and real time variant calling of whole genome sequencing data.
This new strategy has proven successful in analyzing an unprecedented set of 5,000 samples, which constitute a critical part for the international consortia efforts known as The Cohorts for Heart and Aging Research in Genomic Epidemiology, or CHARGE.
An Open Access Pilot Freely Sharing Cancer Genomic Data From Participants in Texas
In a pilot Open Access (OA) project from the CPRIT-funded Texas Cancer Research Biobank (TCRB), many Texas cancer patients were willing to openly share genomic data from tumor and normal matched pair specimens. For the first time, genetic data from seven human cancer cases with matched normal are freely available without requirement for data use agreements nor any major restriction except that end users cannot attempt to re-identify the participants.
The TCRB was created to bridge the gap between doctors and scientific researchers to improve the prevention, diagnosis and treatment of cancer.
In a paper published in BMC Genomics, a team led by scientists from Baylor College of Medicine’s Human Genome Sequencing Center present Parliament, a structural variant (SV) calling pipeline that brings together multiple data types and SV detection methods to improve the characterization of these larger variants.