POSE @ Karchin lab

POSE (Phenotype-optimized Sequence Ensembles)

is a supervised learning method that predicts the functional significance of missense mutations in a specific protein. Current release is POSE 0.60, last updated on 01/12/2015. POSE software is intended for those with substantial bioinformatics and Python expertise.

POSE is free for non-commercial use. Commercial users should contact the Johns Hopkins Technology Transfer office

Documentation for the developer

Download POSE source code here
For documentation details, please contact the primary developer.

Primary citations

If you use POSE software for a publication, please cite the following:

Masica D, Sosnay P, Cutting G, Karchin R (2012) Phenotype-optimized sequence ensembles substantially improve prediction of disease-causing mutation in cystic fibrosis Human Mutation. 33(8):1267-74

Masica D, Sosnay P, Raraigh K, Cutting G, Karchin R (2014) Missense variants in CFTR nucleotide-binding domains predict quantitative phenotypes associated with cystic fibrosis disease severity Human Molecular Genetics. ddu607 [Epub ahead of print]

Software primary contact/developer

David Masica  david dot masica at gmail dot com

This is a beta version of the POSE documentation page. Please contact the primary developer with feedback, suggestions, and requests to improve this page.