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Fig. 1 | BMC Bioinformatics

Fig. 1

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

Fig. 1

Study Overview (a) B cells are collected from patient cerebrospinal fluid. (b) DNA is extracted, and next generation sequencing is used to sequence immunoglobulin heavy chain loci expressing IGHV4 rearrangements. (c) Snippets of amino acid sequence taken from the CDR3 are converted into a set of chemical features using Atchley factors. (d) The chemical features are scored by a detector function. The detector function used in this study is the same function used in logistic regression. A positive diagnosis (for RRMS) is flagged whenever a high scoring snippet is found. Values for the weights on each Atchley factor as well as the bias term are determined by maximizing the likelihood of obtaining the correct diagnoses on a training set of patients

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BMC Bioinformatics

ISSN: 1471-2105

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