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.
In our work with biomedical data, we are fortunate to count many of the experts quoted in the article as friends and colleagues. We agree genomic data sharing is not yet living up to its promise, yet are optimistic about the emergence of new approaches and platforms.
New year, new partnership… and a new blog series focusing on highlighting papers that we think will be of interest to many of you. For this first iteration, we review a review paper (review-ception!) fresh off the virtual press over at GigaScience, coming out of C. Titus Brown's lab at UC Davis, on the topic of workflow systems.
As we have discussed previously, our collaborators in the Sabeti Lab at the Broad Institute have been analyzing SARS-CoV-2 viral genomes from COVID-19 cases in the Boston area, in partnership with the MA Department of Public Health and Massachusetts General Hospital. From the beginning of this work, they have shared their [...]