Evidence map›Paper›PMID 29020925›Full record

ArticleBMC bioinformatics2017

VDJPipe: a pipelined tool for pre-processing immune repertoire sequencing data.

Scott Christley, Mikhail K Levin, Inimary T Toby, John M Fonner, Nancy L Monson, William H Rounds, Florian Rubelt, Walter Scarborough, Richard H Scheuermann, Lindsay G Cowell

Abstract read
In one paragraph

Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. VDJ-REMIX: REpertoire Module Identification and eXploration.Bioinformatics (Oxford, England) · 2026
    Article
  2. Neonatal CD19Frontiers in immunology · 2026
    Article
  3. Human IgMInternational journal of molecular sciences · 2023
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. The Pipeline Repertoire for Ig-Seq Analysis.Frontiers in immunology · 2019
    Review
  11. Article
  12. Article
  13. T Cell Receptor Profiling in Type 1 Diabetes.Current diabetes reports · 2017
    Review
  14. Article
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

10 authors.

Scott ChristleyDepartment of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
Mikhail K LevinBank of America Corporate Center, Charlotte, NC, 28202, USA.
Inimary T TobyDepartment of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
John M FonnerTexas Advanced Computing Center, Austin, TX, 78758-4497, USA.
Nancy L MonsonDepartment of Neurology and Neurotherapeutics, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
William H RoundsDepartment of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
Florian RubeltDepartment of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Walter ScarboroughTexas Advanced Computing Center, Austin, TX, 78758-4497, USA.
Richard H ScheuermannJ. Craig Venter Institute, La Jolla, CA, 92037, USA.
Lindsay G CowellDepartment of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, 75390, USA. lindsay.cowell@utsouthwestern.edu.

Funding

RepServer: Antigen Receptor Repertoire Analysis Pipelines via the WWWR01AI097403 · NIAID · UT SOUTHWESTERN MEDICAL CENTER · PI COWELL, LINDSAY G. · 2012 to 2016
$3.2M
NIAID NIH HHS HHSN272201200028CNIAID NIH HHS R01 AI097403
6 · The paper itself

Abstract

backgroundPre-processing of high-throughput sequencing data for immune repertoire profiling is essential to insure high quality input for downstream analysis. VDJPipe is a flexible, high-performance tool that can perform multiple pre-processing tasks with just a single pass over the data files.

resultsProcessing tasks provided by VDJPipe include base composition statistics calculation, read quality statistics calculation, quality filtering, homopolymer filtering, length and nucleotide filtering, paired-read merging, barcode demultiplexing, 5' and 3' PCR primer matching, and duplicate reads collapsing. VDJPipe utilizes a pipeline approach whereby multiple processing steps are performed in a sequential workflow, with the output of each step passed as input to the next step automatically. The workflow is flexible enough to handle the complex barcoding schemes used in many immunosequencing experiments. Because VDJPipe is designed for computational efficiency, we evaluated this by comparing execution times with those of pRESTO, a widely-used pre-processing tool for immune repertoire sequencing data. We found that VDJPipe requires <10% of the run time required by pRESTO.

conclusionsVDJPipe is a high-performance tool that is optimized for pre-processing large immune repertoire sequencing data sets.

Indexed as

SoftwareAnimalsB-LymphocytesDNA PrimersHigh-Throughput Nucleotide SequencingHumansImmunoglobulin GMiceTime FactorsDNA PrimersImmunoglobulin GBioinformaticsImmune repertoire analysisRep-seq

Identifiers

PMID29020925
PMCPMC5637252

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.