Evidence map›Paper›PMID 30871461›Full record

ArticleBMC bioinformatics2019

Similarities and differences between variants called with human reference genome HG19 or HG38.

Bohu Pan, Rebecca Kusko, Wenming Xiao, Yuanting Zheng, Zhichao Liu, Chunlin Xiao, Sugunadevi Sakkiah, Wenjing Guo, Ping Gong, Chaoyang Zhang and 4 more

Erratum issuedAbstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Integrating Long-Read Nanopore Sequencing for Precision Resolution of Genomic Variants in Dystonia.Movement disorders : official journal of the Movement Disorder Society · 2026
    Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Bohu PanDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
Rebecca KuskoImmuneering Corporation, Cambridge, MA, 02142, USA.
Wenming XiaoDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
Yuanting ZhengCenter for Pharmacogenomics, Fudan University, Shanghai, China.
Zhichao LiuDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
Chunlin XiaoNational Center for Biotechnological Information, National Institutes of Health, Bethesda, MD, 20894, USA.
Sugunadevi SakkiahDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
Wenjing GuoDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
Ping GongEnvironmental Laboratory, US Army Engineer Research and Development Center, Vicksburg, MS, 39180, USA.
Chaoyang ZhangSchool of Computing, The University of Southern Mississippi, Hattiesburg, MS, 39406, USA.
Weigong GeDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
Leming ShiCenter for Pharmacogenomics, Fudan University, Shanghai, China.
Weida TongDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
Huixiao HongDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA. huixiao.hong@fda.hhs.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReference genome selection is a prerequisite for successful analysis of next generation sequencing (NGS) data. Current practice employs one of the two most recent human reference genome versions: HG19 or HG38. To date, the impact of genome version on SNV identification has not been rigorously assessed.

methodsWe conducted analysis comparing the SNVs identified based on HG19 vs HG38, leveraging whole genome sequencing (WGS) data from the genome-in-a-bottle (GIAB) project. First, SNVs were called using 26 different bioinformatics pipelines with either HG19 or HG38. Next, two tools were used to convert the called SNVs between HG19 and HG38. Lastly we calculated conversion rates, analyzed discordant rates between SNVs called with HG19 or HG38, and characterized the discordant SNVs.

resultsThe conversion rates from HG38 to HG19 (average 95%) were lower than the conversion rates from HG19 to HG38 (average 99%). The conversion rates varied slightly among the various calling pipelines. Around 1.5% SNVs were discordantly converted between HG19 or HG38. The conversions from HG38 to HG19 had more SNVs which failed conversion and more discordant SNVs than the opposite conversion (HG19 to HG38). Most of the discordant SNVs had low read depth, were low confidence SNVs as defined by GIAB, and/or were predominated by G/C alleles (52% observed versus 42% expected).

conclusionA significant number of SNVs could not be converted between HG19 and HG38. Based on careful review of our comparisons, we recommend HG38 (the newer version) for NGS SNV analysis. To summarize, our findings suggest caution when translating identified SNVs between different versions of the human reference genome.

Indexed as

Genome, HumanHigh-Throughput Nucleotide SequencingHumansCalling pipeline comparisonHuman reference genomesNext generation sequencingSNV

Identifiers

PMID30871461
PMCPMC6419332

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.