For researchers trying to understand and treat cancer, searching for useful datasets consumes valuable time. Even after accessing a dataset, researchers must figure out how—and where—to analyze it. After all, it is no mean task to wrangle petabytes of data.
This pediatric oncology study used Terra to identify germline variants contributing to Ewing sarcoma pathogenesis in 1,147 individuals with pediatric sarcoma diagnoses.
Guest author Sam Ahuno describes his published work on African cancer genomics and shares his vision of a cloud-powered future for computational research in Africa.
This chronic lymphocytic leukemia (CLL) study used Terra to process and analyze WES, WGS, RNA-seq, RRBS, and targeted NOTCH1 sequencing data.
This prostate cancer study used Terra to process exome sequencing and single-cell RNAseq data with automated workflows.
This cancer drug discovery study used Terra to process transcriptome profiling data with TOPMED RNA-Seq workflows.
Brendan Reardon, computational biologist at Dana Farber Cancer Institute, describes how the MOAlmanac algorithm and analysis portal enable a wide range of users to leverage large-scale genomics to guide individualized patient care in oncology.
PANOPLY is a computational framework for applying statistical and machine learning algorithms to transform multi-omic data from cancer samples into biologically meaningful and interpretable results. In this post, D. R. Mani explains how his team is leveraging Terra to make PANOPLY accessible to a wide range of researchers.
How a team of designers and engineers rose to the challenge of supporting TestBoston, a collaborative project with Brigham and Women’s Hospital that aims to monitor the infection rate of COVID-19 in Massachusetts over time.
In the last decade, we’ve seen exponential growth in the amount and breadth of cancer research data. We’ve harnessed the power of cloud repositories to host large oncology datasets, including genomics, proteomics, imaging, and more! Although this diversity in datasets is a strength, combining these data to leverage the full range of information […]
Terra is developed by the Broad Institute of MIT and Harvard in collaboration with Microsoft and Verily.
