PT  - JOURNAL ARTICLE
AU  - Giangreco, Nicholas P.
AU  - Fine, Barry
AU  - Tatonetti, Nicholas P.
TI  - cohorts: A Python package for clinical ‘omics data management
AID  - 10.1101/626051
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 626051
4099  - http://biorxiv.org/content/early/2019/05/02/626051.short
4100  - http://biorxiv.org/content/early/2019/05/02/626051.full
AB  - Summary Precision medicine uses patient clinical and molecular characteristics to personalize diagnosis and treatment. This emerging discipline integrates multi-modal data into large-scale studies of human disease to make accurate individual-level predictions. The success of these studies will depend on the generalizability of the results, the ability of other researchers and clinicians to replicate studies, and the understandability of the methods used. Tools for data management and standardization are needed to promote flexible, transparent, and reproducible analyses. Here we present cohorts, a python package facilitating clinical and biomarker data management to enhance standardization and reproducibility of clinical findings.Availability The python package cohorts is available at http://www.github.com/ngiangre/cohorts.CONTACT NPT2105{at}CUMC.COLUMBIA.EDU