Evidence map›Paper›PMID 25136349›Full record

ArticleFrontiers in genetics2014

The CNVrd2 package: measurement of copy number at complex loci using high-throughput sequencing data.

Hoang T Nguyen, Tony R Merriman, Michael A Black

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

15 citing papers in PubMed, 25 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Statistical Considerations on NGS Data for Inferring Copy Number Variations.Methods in molecular biology (Clifton, N.J.) · 2021
    Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. HumanWellcome open research · 2018
    Article
  11. Copy number variation and disease resistance in plants.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2017
    Review
  12. Article
  13. Article
  14. Review
  15. 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

3 authors at 1 institution in 1 country.

Hoang T NguyenDepartment of Biochemistry, University of Otago Dunedin, New Zealand ; Department of Mathematics and Statistics, University of Otago Dunedin, New Zealand ; Department of Biochemistry, Virtual Institute of Statistical Genetics, University of Otago Dunedin, New Zealand.
Tony R MerrimanDepartment of Biochemistry, University of Otago Dunedin, New Zealand ; Department of Biochemistry, Virtual Institute of Statistical Genetics, University of Otago Dunedin, New Zealand.
Michael A BlackDepartment of Biochemistry, University of Otago Dunedin, New Zealand ; Department of Biochemistry, Virtual Institute of Statistical Genetics, University of Otago Dunedin, New Zealand.
University of Otago · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advances in high-throughout sequencing technologies have made it possible to accurately assign copy number (CN) at CN variable loci. However, current analytic methods often perform poorly in regions in which complex CN variation is observed. Here we report the development of a read depth-based approach, CNVrd2, for investigation of CN variation using high-throughput sequencing data. This methodology was developed using data from the 1000 Genomes Project from the CCL3L1 locus, and tested using data from the DEFB103A locus. In both cases, samples were selected for which paralog ratio test data were also available for comparison. The CNVrd2 method first uses observed read-count ratios to refine segmentation results in one population. Then a linear regression model is applied to adjust the results across multiple populations, in combination with a Bayesian normal mixture model to cluster segmentation scores into groups for individual CN counts. The performance of CNVrd2 was compared to that of two other read depth-based methods (CNVnator, cn.mops) at the CCL3L1 and DEFB103A loci. The highest concordance with the paralog ratio test method was observed for CNVrd2 (77.8/90.4% for CNVrd2, 36.7/4.8% for cn.mops and 7.2/1% for CNVnator at CCL3L1 and DEF103A). CNVrd2 is available as an R package as part of the Bioconductor project: http://www.bioconductor.org/packages/release/bioc/html/CNVrd2.html.

Indexed as

1000 GenomesCCL3L1copy number variationDEFB4read depth

Identifiers

PMID25136349
PMCPMC4117933
OpenAlexW2014010495

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.