Evidence map›Paper›PMID 38129777›Full record

ArticleBMC bioinformatics2023

IgMAT: immunoglobulin sequence multi-species annotation tool for any species including those with incomplete antibody annotation or unusual characteristics.

Daniel Dorey-Robinson, Giuseppe Maccari, John A Hammond

Abstract read
In one paragraph

Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Daniel Dorey-Robinson *The Pirbright Institute, Pirbright, UK.
Giuseppe Maccari *The Pirbright Institute, Pirbright, UK.
John A HammondThe Pirbright Institute, Pirbright, UK. john.hammond@pirbright.ac.uk.

Funding

Biotechnology and Biological Sciences Research Council BB/M011488/1Biotechnology and Biological Sciences Research Council BBS/E/I/00007038
6 · The paper itself

Abstract

backgroundThe advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative regardless of study species. However, to fully map dynamic changes in polyclonal responses precise framework and complementarity determining region annotation of rearranging genes is pivotal. Most sequence annotation tools are designed primarily for use with human and mouse antibody sequences which use databases with fixed species lists, applying very specific assumptions which select against unique structural characteristics. For this reason, data agnostic tools able to learn from presented data can be very useful with new species or with novel datasets.

resultsWe have developed IgMAT, which utilises a reduced amino acid alphabet, that incorporates multiple HMM alignments into a single consensus to automatically annotate immunoglobulin sequences from most organisms. Additionally, the software allows the incorporation of user defined databases to better represent the species and/or antibody class of interest. To demonstrate the accuracy and utility of IgMAT, we present analysis of sequences extracted from structural data and immunoglobulin sequence datasets from several different species.

conclusionsIgMAT is fully open-sourced and freely available on GitHub ( https://github.com/TPI-Immunogenetics/igmat ) for download under GPLv3 license. It can be used as a CLI application or as a python module to be integrated in custom scripts.

Indexed as

ImmunoglobulinsSoftwareAnimalsDatabases, FactualHumansMiceImmunoglobulinsAnnotationIMGTImmunoglobulin

Identifiers

PMID38129777
PMCPMC10740263

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.