An HMM-based framework for B-cell receptor sequence annotation, simulation, and clonal family inference. partis is especially effective for modern large sequencing data sets because it can infer detailed parameters concerning the rearrangement process, and then perform annotation inference on each sequence in the set. It is built on top of the ham Hiden Markov Model (HMM) compiler, and also uses the ig-sw set of Smith-Waterman annotation tools.

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partis specifications

Software type:
Package
Restrictions to use:
None
Input format:
FASTA
Output format:
CSV
License:
GNU General Public License version 3.0
Stability:
Stable
Interface:
Command line interface
Input data:
B-cell receptor sequences, parameters particular to the input sequence file
Output data:
The germline genes used to make the BCR, the amount of junctional exonuclease deletion for each gene, the size of junctional insertions (N-regions) between the trimmed germline genes, the joint probability of sequence and annotation
Programming languages:
Python
Computer skills:
Advanced
Requirements:
ham, ig-sw
Source code URL:
https://github.com/psathyrella/partis.git

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Documentation

Maintainer

Credits

Publications

  • (Ralph and Matsen, 2016) Consistency of VDJ Rearrangement and Substitution Parameters Enables Accurate B Cell Receptor Sequence Annotation. PLOS Computational Biology.
    PMID: 26751373
  • (Ralph and Matsen, 2016) Likelihood-Based Inference of B Cell Clonal Families. PLoS Computational Biology.
    DOI: 10.1371/journal.pcbi.1005086

Institution(s)

Fred Hutchinson Cancer Research Center, Seattle, WA, USA

Funding source(s)

This research was funded by National Institutes of Health grants R01 GM113246-01 & R01 AI103981, and in part by a 2013 emerging opportunity award from the University of Washington Center for AIDS Research (CFAR), an NIH funded program under award number P30AI027757 which is supported by the following NIH Institutes and Centers (NIAID, NCI, NIMH, NIDA, NICHD, NHLBI, NIA, NIGMS, NIDDK).

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