Evidence map›Paper›PMID 27605188›Full record

ReviewMicroarrays (Basel, Switzerland)2013

Comparative Analysis of CNV Calling Algorithms: Literature Survey and a Case Study Using Bovine High-Density SNP Data.

Lingyang Xu, Yali Hou, Derek M Bickhart, Jiuzhou Song, George E Liu

Abstract readReview
In one paragraph

Review in Microarrays (Basel, Switzerland), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Mapping copy number variable regions correlated with reproduction and production traits in Karan Fries cattle mammalian genomics.Mammalian genome : official journal of the International Mammalian Genome Society · 2025
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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

5 authors.

Lingyang XuBovine Functional Genomics Laboratory, BARC, BA, USDA-ARS, Beltsville, MD 20705, USA. songj88@umd.edu.
Yali HouLaboratory of Disease Genomics and Individualized Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, China. houyali1210@gmail.com.
Derek M BickhartAnimal Improvement Programs Laboratory, BARC, BA, USDA-ARS, Beltsville, MD 20705, USA. Derek.Bickhart@ars.usda.gov.
Jiuzhou SongDepartment of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA. songj88@umd.edu.
George E LiuBovine Functional Genomics Laboratory, BARC, BA, USDA-ARS, Beltsville, MD 20705, USA. George.Liu@ars.usda.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Copy number variations (CNVs) are gains and losses of genomic sequence between two individuals of a species when compared to a reference genome. The data from single nucleotide polymorphism (SNP) microarrays are now routinely used for genotyping, but they also can be utilized for copy number detection. Substantial progress has been made in array design and CNV calling algorithms and at least 10 comparison studies in humans have been published to assess them. In this review, we first survey the literature on existing microarray platforms and CNV calling algorithms. We then examine a number of CNV calling tools to evaluate their impacts using bovine high-density SNP data. Large incongruities in the results from different CNV calling tools highlight the need for standardizing array data collection, quality assessment and experimental validation. Only after careful experimental design and rigorous data filtering can the impacts of CNVs on both normal phenotypic variability and disease susceptibility be fully revealed.

Indexed as

algorithmcattle genomecopy number variation (CNV)segmental duplicationsingle nucleotide polymorphism (SNP)

Identifiers

PMID27605188
PMCPMC5003459

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.