Statistical classifiers for diagnosing disease from immune repertoires: a case study using multiple sclerosis

Statistical classifiers for diagnosing disease from immune repertoires: a case study using multiple sclerosis

Abstract Background Deep sequencing of lymphocyte receptor repertoires has made it possible to comprehensively profile the clonal composition of lymphocyte populations. This opens the door for novel approaches to diagnose and prognosticate diseases with a driving immune component by identifying repe...

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Bibliographic Details
Main Authors: Jared Ostmeyer, Scott Christley, William H. Rounds, Inimary Toby, Benjamin M. Greenberg, Nancy L. Monson, Lindsay G. Cowell
Format: Article
Language:English
Published: BMC 2017-09-01
Series:BMC Bioinformatics
Subjects:
Antibody
Immune repertoire
CDR3
Machine learning
Multiple sclerosis
Statistical classifier
Online Access:http://link.springer.com/article/10.1186/s12859-017-1814-6

Internet

http://link.springer.com/article/10.1186/s12859-017-1814-6

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