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SONAR: A High-Throughput Pipeline for Inferring Antibody Ontogenies from Longitudinal Sequencing of B Cell Transcripts

Overview of attention for article published in Frontiers in immunology, September 2016
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Title
SONAR: A High-Throughput Pipeline for Inferring Antibody Ontogenies from Longitudinal Sequencing of B Cell Transcripts
Published in
Frontiers in immunology, September 2016
DOI 10.3389/fimmu.2016.00372
Pubmed ID
Authors

Chaim A. Schramm, Zizhang Sheng, Zhenhai Zhang, John R. Mascola, Peter D. Kwong, Lawrence Shapiro

Abstract

The rapid advance of massively parallel or next-generation sequencing technologies has made possible the characterization of B cell receptor repertoires in ever greater detail, and these developments have triggered a proliferation of software tools for processing and annotating these data. Of especial interest, however, is the capability to track the development of specific antibody lineages across time, which remains beyond the scope of most current programs. We have previously reported on the use of techniques such as inter- and intradonor analysis and CDR3 tracing to identify transcripts related to an antibody of interest. Here, we present Software for the Ontogenic aNalysis of Antibody Repertoires (SONAR), capable of automating both general repertoire analysis and specialized techniques for investigating specific lineages. SONAR annotates next-generation sequencing data, identifies transcripts in a lineage of interest, and tracks lineage development across multiple time points. SONAR also generates figures, such as identity-divergence plots and longitudinal phylogenetic "birthday" trees, and provides interfaces to other programs such as DNAML and BEAST. SONAR can be downloaded as a ready-to-run Docker image or manually installed on a local machine. In the latter case, it can also be configured to take advantage of a high-performance computing cluster for the most computationally intensive steps, if available. In summary, this software provides a useful new tool for the processing of large next-generation sequencing datasets and the ontogenic analysis of neutralizing antibody lineages. SONAR can be found at https://github.com/scharch/SONAR, and the Docker image can be obtained from https://hub.docker.com/r/scharch/sonar/.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 1%
Unknown 74 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 19%
Student > Ph. D. Student 11 15%
Student > Master 11 15%
Student > Bachelor 7 9%
Professor > Associate Professor 5 7%
Other 9 12%
Unknown 18 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 24%
Agricultural and Biological Sciences 12 16%
Immunology and Microbiology 12 16%
Engineering 5 7%
Computer Science 3 4%
Other 6 8%
Unknown 19 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 21 September 2016.
All research outputs
#22,759,802
of 25,374,647 outputs
Outputs from Frontiers in immunology
#27,421
of 31,520 outputs
Outputs of similar age
#288,892
of 328,377 outputs
Outputs of similar age from Frontiers in immunology
#136
of 165 outputs
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So far Altmetric has tracked 31,520 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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