Evidence map›Paper›PMID 30564443›Full record

ArticleEvolution letters2018

Accounting for heteroscedasticity and censoring in chromosome partitioning analyses.

Petri Kemppainen, Arild Husby

Abstract read
In one paragraph

Article in Evolution letters, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Petri KemppainenOrganismal and Evolutionary Biology Research Programme University of Helsinki 00014 Helsinki Finland.
Arild HusbyOrganismal and Evolutionary Biology Research Programme University of Helsinki 00014 Helsinki Finland.ORCID https://orcid.org/0000-0003-1911-8351

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A fundamental assumption in quantitative genetics is that traits are controlled by many loci of small effect. Using genomic data, this assumption can be tested using chromosome partitioning analyses, where the proportion of genetic variance for a trait explained by each chromosome (

Indexed as

Chromosome partitioningGCTAgenomic relatednessheritabilityinfinitesimal modelSNP heritability

Identifiers

PMID30564443
PMCPMC6292708

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.