Evidence map›Paper›PMID 32789006›Full record

ArticleF1000Research2020

scRepertoire: An R-based toolkit for single-cell immune receptor analysis.

Nicholas Borcherding, Nicholas L Bormann, Gloria Kraus

Open access · goldAbstract read
In one paragraph

Article in F1000Research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 410 papers.

0numbers the graph read from it
0cells of the map it votes in
410citing papers in PubMed
12.5field-weighted citation impact, top 1% of its field
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

410 citing papers in PubMed, 371 citations in OpenAlex.

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  8. Distinct CD8Cancer cell · 2025
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  13. Abundant CD8British journal of cancer · 2026
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350 more citing papers are in PubMed but not listed here.

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 at 2 institutions in 2 countries.

Nicholas BorcherdingDepartment of Pathology, University of Iowa, Iowa City, IA, USA.ORCID 0000-0003-1427-6342
Nicholas L BormannDepartment of Psychiatry, University of Iowa, Iowa ity, IA, USA.
Gloria KrausFaculty of Medicine, Center for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany.
University of Iowa · USTechnische Universität Dresden · DE

Funding

The role of paracrine WNT5A/RYK in ErbB2-driven tumorigenesisF30CA206255 · NCI · UNIVERSITY OF IOWA · PI BORCHERDING, NICHOLAS · 2017 to 2020
$143k
NCI NIH HHS F30 CA206255
6 · The paper itself

Abstract

Single-cell sequencing is an emerging technology in the field of immunology and oncology that allows researchers to couple RNA quantification and other modalities, like immune cell receptor profiling at the level of an individual cell. A number of workflows and software packages have been created to process and analyze single-cell transcriptomic data. These packages allow users to take the vast dimensionality of the data generated in single-cell-based experiments and distill the data into novel insights. Unlike the transcriptomic field, there is a lack of options for software that allow for single-cell immune receptor profiling. Enabling users to easily combine mRNA and immune profiling, scRepertoire was built to process data derived from 10x Genomics Chromium Immune Profiling for both T-cell receptor (TCR) and immunoglobulin (Ig) enrichment workflows and subsequently interacts with a number of popular R packages for single-cell expression, such as Seurat. The scRepertoire R package and processed data are open source and available on GitHub and provides in-depth tutorials on the capability of the package.

Indexed as

Single-Cell AnalysisSoftwareGenomicsReceptors, Antigen, T-CellReceptors, ImmunologicRNAWorkflowReceptors, Antigen, T-CellReceptors, ImmunologicRNAclonotypic analysisimmune receptor profilingRSingle-cell RNA sequencing

Identifiers

PMID32789006
PMCPMC7400693
OpenAlexW3002623081

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.