Evidence map›Paper›PMID 26640477›Full record

ArticleFrontiers in genetics2015

Identification of Low-Confidence Regions in the Pig Reference Genome (Sscrofa10.2).

Amanda Warr, Christelle Robert, David Hume, Alan L Archibald, Nader Deeb, Mick Watson

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.5field-weighted citation impact, top 7% 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

19 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. CNV analysis of Meishan pig by next-generation sequencing and effects ofJournal of animal science and biotechnology · 2020
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. 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

6 authors at 3 institutions in 2 countries.

Amanda WarrDivision of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh Edinburgh, UK.
Christelle RobertDivision of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh Edinburgh, UK.
David HumeDivision of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh Edinburgh, UK.
Alan L ArchibaldDivision of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh Edinburgh, UK.
Nader DeebGenus plc., Hendersonville TN, USA.
Mick WatsonDivision of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh Edinburgh, UK.
University of Edinburgh · GBRoslin Institute · GBGenus (United States) · US

Funding

Biotechnology and Biological Sciences Research Council BBS/E/D/20211550Biotechnology and Biological Sciences Research Council BBS/E/D/20211551Biotechnology and Biological Sciences Research Council BBS/E/D/20251969Biotechnology and Biological Sciences Research Council BBS/E/I/00001140Biotechnology and Biological Sciences Research Council BBS/E/I/00001425Medical Research Council G0900740Medical Research Council MR/K001744/1
6 · The paper itself

Abstract

Many applications of high throughput sequencing rely on the availability of an accurate reference genome. Variant calling often produces large data sets that cannot be realistically validated and which may contain large numbers of false-positives. Errors in the reference assembly increase the number of false-positives. While resources are available to aid in the filtering of variants from human data, for other species these do not yet exist and strict filtering techniques must be employed which are more likely to exclude true-positives. This work assesses the accuracy of the pig reference genome (Sscrofa10.2) using whole genome sequencing reads from the Duroc sow whose genome the assembly was based on. Indicators of structural variation including high regional coverage, unexpected insert sizes, improper pairing and homozygous variants were used to identify low quality (LQ) regions of the assembly. Low coverage (LC) regions were also identified and analyzed separately. The LQ regions covered 13.85% of the genome, the LC regions covered 26.6% of the genome and combined (LQLC) they covered 33.07% of the genome. Over half of dbSNP variants were located in the LQLC regions. Of copy number variable regions identified in a previous study, 86.3% were located in the LQLC regions. The regions were also enriched for gene predictions from RNA-seq data with 42.98% falling in the LQLC regions. Excluding variants in the LQ, LC, or LQLC from future analyses will help reduce the number of false-positive variant calls. Researchers using WGS data should be aware that the current pig reference genome does not give an accurate representation of the copy number of alleles in the original Duroc sow's genome.

Indexed as

copy number variable regionsdraft assembliesfalse positivesmissassemblystructural variation

Identifiers

PMID26640477
PMCPMC4662242
OpenAlexW2178498207

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.