Evidence map›Paper›PMID 29159827›Full record

ArticleGenetic epidemiology2018

Family-based tests for associating haplotypes with general phenotype data: Improving the FBAT-haplotype algorithm.

Julian Hecker, Xin Xu, F William Townes, Heide Loehlein Fier, Chris Corcoran, Nan Laird, Christoph Lange

Abstract read
In one paragraph

Article in Genetic epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. 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

7 authors.

Julian HeckerDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0001-7918-089X
Xin XuNanfang Hospital, Southern Medical University, Guangzhou, China.
F William TownesDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.
Heide Loehlein FierDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0002-7214-1764
Chris CorcoranDepartment of Mathematics and Statistics, Utah State University, Logan, UT, USA.
Nan LairdDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.
Christoph LangeDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.

Funding

Genetic Epidemiology of COPDU01HL089897 · NHLBI · NATIONAL JEWISH HEALTH · PI CRAPO, JAMES D · 2007 to 2021
$56.9M
Genetic Epidemiology of COPDU01HL089856 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SILVERMAN, EDWIN K · 2007 to 2021
$20.7M
Systems Biology of Airway DiseaseP01HL132825 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI DEMEO, DAWN L · 2016 to 2020
$12.6M
Training Grant in Quantitative Sciences for Cancer ResearchT32CA009337 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI QUACKENBUSH, JOHN, TRIPPA, LORENZO · 1986 to 2025
$12.3M
Physics of collective cellular migration in lung health and diseaseP01HL120839 · NHLBI · HARVARD SCHOOL OF PUBLIC HEALTH · PI FREDBERG, JEFFREY J · 2014 to 2018
$12.2M
Novel Statistical Approaches to Mental Health Phenotype Analysis in GWA StudiesR01MH081862 · NIMH · HARVARD SCHOOL OF PUBLIC HEALTH · PI LANGE, CHRISTOPH · 2009 to 2014
$2.0M
A New Approach to Mental Health Phenotypes in Family Genomewide AssociationR01MH087590 · NIMH · HARVARD SCHOOL OF PUBLIC HEALTH · PI LANGE, CHRISTOPH · 2010 to 2013
$1.6M
Statistical and Quantitative Training in Big Data Health ScienceT32LM012411 · NLM · HARVARD SCHOOL OF PUBLIC HEALTH · PI QUACKENBUSH, JOHN · 2016 to 2020
$1.4M
Preparing Association Analysis Software Tools for Next Generation Sequencing DataR01HG008976 · NHGRI · HARVARD SCHOOL OF PUBLIC HEALTH · PI LANGE, CHRISTOPH · 2016 to 2018
$1.1M
NHGRI NIH HHS R01 HG008976NHLBI NIH HHS P01 HL120839NHLBI NIH HHS P01 HL132825NHLBI NIH HHS U01 HL089856NHLBI NIH HHS U01 HL089897NIMH NIH HHS R01 MH081862NIMH NIH HHS R01 MH087590NLM NIH HHS T32 LM012411
6 · The paper itself

Abstract

For family-based association studies, Horvath et al. proposed an algorithm for the association analysis between haplotypes and arbitrary phenotypes when the phase of the haplotypes is unknown, that is, genotype data is given. Their approach to haplotype analysis maintains the original features of the TDT/FBAT-approach, that is, complete robustness against genetic confounding and misspecification of the phenotype. The algorithm has been implemented in the FBAT and PBAT software package and has been used in numerous substantive manuscripts. Here, we propose a simplification of the original algorithm that maintains the original approach but reduces the computational burden of the approach substantially and gives valuable insights regarding the conditional distribution. With the modified algorithm, the application to whole-genome sequencing (WGS) studies becomes feasible; for example, in sliding window approaches or spatial-clustering approaches. The reduction of the computational burden that our modification provides is especially dramatic when both parental genotypes are missing. For example, for eight variants and 441 nuclear families with mostly offspring-only families, in a WGS study at the APOE locus, the running time decreased from approximately 21 hr for the original algorithm to 0.11 sec after our modification.

Indexed as

AlgorithmsHaplotypesNuclear FamilyPhenotypeApolipoproteins ECluster AnalysisFemaleHumansMaleModels, GeneticTime FactorsWhole Genome SequencingApolipoproteins Eadmixturecandidate regionFBATwhole-genome sequencing

Identifiers

PMID29159827
PMCPMC5774664

What OpenQuestion holds

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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.