Evidence map›Paper›PMID 26500154›Full record

ArticleBioinformatics (Oxford, England)2016

BGT: efficient and flexible genotype query across many samples.

Heng Li

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–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

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. An Efficient Dynamic Data Structure for Haplotype Matching and Compression on Biobank-Scale Data.Journal of computational biology : a journal of computational molecular cell biology · 2026
    Article
  3. Article
  4. DynamicbioRxiv : the preprint server for biology · 2025
    Article
  5. Analysis-ready VCF at Biobank scale using Zarr.bioRxiv : the preprint server for biology · 2025
    Article
  6. Article
  7. IGD: a simple, efficient genotype data format.Bioinformatics advances · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Data Structures for SMEM-Finding in the PBWT.International Symposium on String Processing and Information Retrieval : SPIRE ... : proceedings. SPIRE (Symposium) · 2023
    Article
  12. Article
  13. Article
  14. A novel splice-affectingThe Lancet regional health. Europe · 2023
    Article
  15. Article
  16. d-PBWT: dynamic positional Burrows-Wheeler transform.Bioinformatics (Oxford, England) · 2021
    Article
  17. Article
  18. Article
  19. Article
  20. 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

1 author.

Heng LiMedical Population Genetics Program, Broad Institute, Cambridge, MA 02142, USA.

Funding

Population mixture in evolutionary and medical geneticsR01GM100233 · NIGMS · HARVARD MEDICAL SCHOOL · PI PATTERSON, NICK J, REICH, DAVID E · 2012 to 2019
$2.7M
NHGRI NIH HHS U54HG003037NIGMS NIH HHS GM100233
6 · The paper itself

Abstract

unlabelledBGT is a compact format, a fast command line tool and a simple web application for efficient and convenient query of whole-genome genotypes and frequencies across tens to hundreds of thousands of samples. On real data, it encodes the haplotypes of 32 488 samples across 39.2 million SNPs into a 7.4 GB database and decodes up to 420 million genotypes per CPU second. The high performance enables real-time responses to complex queries. AVAILABILITY AND IMPLEMENTATION: https://github.com/lh3/bgt.

Indexed as

AlgorithmsGenome, HumanGenotypeSoftwareDatabases, FactualDatasets as TopicGenetic VariationHaplotypesHumans

Identifiers

PMID26500154
PMCPMC5963361

What OpenQuestion holds

Textmetadata
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.