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Practical guidelines for B-cell receptor repertoire sequencing analysis

Overview of attention for article published in Genome Medicine, November 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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27 X users
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Title
Practical guidelines for B-cell receptor repertoire sequencing analysis
Published in
Genome Medicine, November 2015
DOI 10.1186/s13073-015-0243-2
Pubmed ID
Authors

Gur Yaari, Steven H. Kleinstein

Abstract

High-throughput sequencing of B-cell immunoglobulin repertoires is increasingly being applied to gain insights into the adaptive immune response in healthy individuals and in those with a wide range of diseases. Recent applications include the study of autoimmunity, infection, allergy, cancer and aging. As sequencing technologies continue to improve, these repertoire sequencing experiments are producing ever larger datasets, with tens- to hundreds-of-millions of sequences. These data require specialized bioinformatics pipelines to be analyzed effectively. Numerous methods and tools have been developed to handle different steps of the analysis, and integrated software suites have recently been made available. However, the field has yet to converge on a standard pipeline for data processing and analysis. Common file formats for data sharing are also lacking. Here we provide a set of practical guidelines for B-cell receptor repertoire sequencing analysis, starting from raw sequencing reads and proceeding through pre-processing, determination of population structure, and analysis of repertoire properties. These include methods for unique molecular identifiers and sequencing error correction, V(D)J assignment and detection of novel alleles, clonal assignment, lineage tree construction, somatic hypermutation modeling, selection analysis, and analysis of stereotyped or convergent responses. The guidelines presented here highlight the major steps involved in the analysis of B-cell repertoire sequencing data, along with recommendations on how to avoid common pitfalls.

X Demographics

X Demographics

The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 653 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 <1%
Netherlands 3 <1%
Germany 1 <1%
Brazil 1 <1%
Italy 1 <1%
Denmark 1 <1%
South Africa 1 <1%
Unknown 640 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 149 23%
Student > Ph. D. Student 140 21%
Student > Master 72 11%
Student > Bachelor 46 7%
Other 34 5%
Other 84 13%
Unknown 128 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 153 23%
Agricultural and Biological Sciences 131 20%
Immunology and Microbiology 101 15%
Medicine and Dentistry 44 7%
Computer Science 22 3%
Other 52 8%
Unknown 150 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 27. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 October 2023.
All research outputs
#1,442,120
of 25,552,933 outputs
Outputs from Genome Medicine
#304
of 1,596 outputs
Outputs of similar age
#23,399
of 393,726 outputs
Outputs of similar age from Genome Medicine
#6
of 30 outputs
Altmetric has tracked 25,552,933 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,596 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.7. This one has done well, scoring higher than 81% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 393,726 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.