Evidence map›Paper›PMID 39411512›Full record

ArticleNAR genomics and bioinformatics2024

bcRflow: a Nextflow pipeline for characterizing B cell receptor repertoires from non-targeted transcriptomic data.

Brent T Schlegel, Michael Morikone, Fangping Mu, Wan-Yee Tang, Gary Kohanbash, Dhivyaa Rajasundaram

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Brent T SchlegelDepartment of Pediatrics, Division of Health Informatics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, John G. Rangos Sr. Research Center, 4401 Penn Avenue, Pittsburgh, PA 15224, USA.ORCID https://orcid.org/0000-0002-4444-5111
Michael MorikoneDepartment of Pediatrics, Division of Health Informatics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, John G. Rangos Sr. Research Center, 4401 Penn Avenue, Pittsburgh, PA 15224, USA.ORCID https://orcid.org/0009-0004-7413-6020
Fangping MuCenter for Research Computing, University of Pittsburgh, 312 Schenley Place, 4420 Bayard Street, Pittsburgh, PA 15260, USA.
Wan-Yee TangDepartment of Environmental and Occupational Health, University of Pittsburgh, School of Public Health, 130 DeSoto Street, Pittsburgh, PA 15261, USA.
Gary KohanbashDepartment of Neurological Surgery, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, John G. Rangos Sr. Research Center, 4401 Penn Avenue, Pittsburgh, PA 15224, USA.
Dhivyaa RajasundaramDepartment of Pediatrics, Division of Health Informatics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, John G. Rangos Sr. Research Center, 4401 Penn Avenue, Pittsburgh, PA 15224, USA.

Funding

Impact of Maternal Arsenic Exposure on Offspring's Epigenetic Reprogramming of Allergic Airway DiseaseR01ES034760 · NIEHS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Wan-yee Tang · 2023 to 2026
$1.8M
High-Throughput Computing for Genomics and Bioinformatics ResearchS10OD028483 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LEE, ADRIAN V · 2021 to 2021
$574k
NIEHS NIH HHS R01 ES034760NIH HHS S10 OD028483
6 · The paper itself

Abstract

B cells play a critical role in the adaptive recognition of foreign antigens through diverse receptor generation. While targeted immune sequencing methods are commonly used to profile B cell receptors (BCRs), they have limitations in cost and tissue availability. Analyzing B cell receptor profiling from non-targeted transcriptomics data is a promising alternative, but a systematic pipeline integrating tools for accurate immune repertoire extraction is lacking. Here, we present bcRflow, a Nextflow pipeline designed to characterize BCR repertoires from non-targeted transcriptomics data, with functional modules for alignment, processing, and visualization. bcRflow is a comprehensive, reproducible, and scalable pipeline that can run on high-performance computing clusters, cloud-based computing resources like Amazon Web Services (AWS), the Open OnDemand framework, or even local desktops. bcRflow utilizes institutional configurations provided by nf-core to ensure maximum portability and accessibility. To demonstrate the functionality of the bcRflow pipeline, we analyzed a public dataset of bulk transcriptomic samples from COVID-19 patients and healthy controls. We have shown that bcRflow streamlines the analysis of BCR repertoires from non-targeted transcriptomics data, providing valuable insights into the B cell immune response for biological and clinical research. bcRflow is available at https://github.com/Bioinformatics-Core-at-Childrens/bcRflow.

Identifiers

PMID39411512
PMCPMC11474772

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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.