Evidence map›Paper›PMID 24955378›Full record

ArticleAnnual review of statistics and its application2014

Next Generation Statistical Genetics: Modeling, Penalization, and Optimization in High-Dimensional Data.

Kenneth Lange, Jeanette C Papp, Janet S Sinsheimer, Eric M Sobel

Abstract read
In one paragraph

Article in Annual review of statistics and its application, 2014. 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
–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

19 citing papers in PubMed.

  1. Article
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  10. Article
  11. Article
  12. Review
  13. The use of vector bootstrapping to improve variable selection precision in Lasso models.Statistical applications in genetics and molecular biology · 2016
    Article
  14. Article
  15. Article
  16. Matrix Completion Discriminant Analysis.Computational statistics & data analysis · 2015
    Article
  17. Article
  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

4 authors.

Kenneth LangeDepts of Biomathematics, Human Genetics, and Statistics, UCLA.
Jeanette C PappDept of Human Genetics, UCLA.
Janet S SinsheimerDepts of Biomathematics, Human Genetics, Statistics, and Biostatistics, UCLA.
Eric M SobelDept of Human Genetics, UCLA.

Funding

STATISTICAL METHODS FOR GENE MAPPINGR01GM053275 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LANGE, KENNETH L · 1995 to 2019
$9.3M
Genomics, GPUs, and Next Generation Computational StatisticsR01HG006139 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SOBEL, ERIC · 2011 to 2023
$5.1M
Statistical Genomics and Systems Biology WorkshopR25GM103774 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HORVATH, STEVE, PAPP, JEANETTE CHRISTINE · 2013 to 2016
$729k
Computer Cluster and Storage to Support Whole Genome Sequencing and AnalysisS10RR025521 · NCRR · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SOBEL, ERIC · 2009 to 2009
$236k
NCRR NIH HHS S10 RR025521NHGRI NIH HHS R01 HG006139NIGMS NIH HHS R01 GM053275NIGMS NIH HHS R25 GM103774
6 · The paper itself

Abstract

Statistical genetics is undergoing the same transition to big data that all branches of applied statistics are experiencing. With the advent of inexpensive DNA sequencing, the transition is only accelerating. This brief review highlights some modern techniques with recent successes in statistical genetics. These include: (a) lasso penalized regression and association mapping, (b) ethnic admixture estimation, (c) matrix completion for genotype and sequence data, (d) the fused lasso and copy number variation, (e) haplotyping, (f) estimation of relatedness, (g) variance components models, and (h) rare variant testing. For more than a century, genetics has been both a driver and beneficiary of statistical theory and practice. This symbiotic relationship will persist for the foreseeable future.

Indexed as

computational statisticsdata miningDNA sequence analysisgene mappingpedigrees

Identifiers

PMID24955378
PMCPMC4062304

What OpenQuestion holds

Textmetadata
LicenceTDM
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.