Evidence map›Paper›PMID 38866901›Full record

ArticleScientific reports2024

Variant ranking pipeline for complex familial disorders.

Sneha Ralli, Tariq Vira, Carla Daniela Robles-Espinoza, David J Adams, Angela R Brooks-Wilson

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Sneha RalliCanada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, V5Z 1L3, Canada.
Tariq ViraCanada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, V5Z 1L3, Canada.
Carla Daniela Robles-EspinozaExperimental Cancer Genetics, Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.
David J AdamsExperimental Cancer Genetics, Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.
Angela R Brooks-WilsonCanada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, V5Z 1L3, Canada. arw6@sfu.ca.

Funding

Canadian Institutes for Health Research MOP-130311Cancer Research UK 21717CONACyT A3-S-31603Medical Research Council MR/V000292/1Melanoma Research Alliance Pilot Award 825924Newton Advanced Fellowship NAF\R2\180782Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica IN209422Wellcome Trust
6 · The paper itself

Abstract

Identifying genetic susceptibility factors for complex disorders remains a challenging task. To analyze collections of small and large pedigrees where genetic heterogeneity is likely, but biological commonalities are plausible, we have developed a weights-based pipeline to prioritize variants and genes. The Weights-based vAriant Ranking in Pedigrees (WARP) pipeline prioritizes variants using 5 weights: disease incidence rate, number of cases in a family, genome fraction shared amongst cases in a family, allele frequency and variant deleteriousness. Weights, except for the population allele frequency weight, are normalized between 0 and 1. Weights are combined multiplicatively to produce family-specific-variant weights that are then averaged across all families in which the variant is observed to generate a multifamily weight. Sorting multifamily weights in descending order creates a ranked list of variants and genes for further investigation. WARP was validated using familial melanoma sequence data from the European Genome-phenome Archive. The pipeline identified variation in known germline melanoma genes POT1, MITF and BAP1 in 4 out of 13 families (31%). Analysis of the other 9 families identified several interesting genes, some of which might have a role in melanoma. WARP provides an approach to identify disease predisposing genes in studies with small and large pedigrees.

Indexed as

Genetic Predisposition to DiseasePedigreeFemaleGene FrequencyGenetic VariationHumansMaleMelanomaMicrophthalmia-Associated Transcription FactorMicrophthalmia-Associated Transcription FactorMITF protein, human

Identifiers

PMID38866901
PMCPMC11169219

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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.