Evidence map›Paper›PMID 30477554›Full record

ArticleGenome biology2018

CODEX2: full-spectrum copy number variation detection by high-throughput DNA sequencing.

Yuchao Jiang, Rujin Wang, Eugene Urrutia, Ioannis N Anastopoulos, Katherine L Nathanson, Nancy R Zhang

Abstract readEvaluation Study
In one paragraph

Article in Genome biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing 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

47 citing papers in PubMed.

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  5. A UniqueInternational journal of molecular sciences · 2026
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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

6 authors.

Yuchao JiangDepartment of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA. yuchaoj@email.unc.edu.
Rujin WangDepartment of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA.
Eugene UrrutiaDepartment of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA.
Ioannis N AnastopoulosDivision of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Katherine L NathansonDivision of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Nancy R ZhangDepartment of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, 19104, USA. nzh@wharton.upenn.edu.

Funding

Targeting the MAP and PI3 Kinase Pathways in MelanomaP01CA114046 · NCI · WISTAR INSTITUTE · PI MURPHY, MAUREEN E. · 2008 to 2023
$37.1M
Biostatstics for Research in Environmental HealthT32ES007018 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Stephanie Engel, Rebecca Fry · 1985 to 2026
$31.3M
Statistical Methods for Cancer Clinical TrialsP01CA142538 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVIDIAN, MARIE, KOSOROK, MICHAEL R · 2010 to 2019
$21.3M
Targeted Combination Therapy for MelanomaP50CA174523 · NCI · WISTAR INSTITUTE · PI HERLYN, MEENHARD F · 2014 to 2018
$11.1M
Molecular Mechanism of Mammalian DNA Excision Repair, DNA Damage Checkpoints and the Circadian ClockR35GM118102 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI AZIZ SANCAR · 2016 to 2026
$10.6M
Statistical Models for Genome Sequencing and AssociationR01HG006137 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI JI, HANLEE P, ZHANG, NANCY R · 2011 to 2022
$4.3M
NCI NIH HHS P01 CA114046NCI NIH HHS P01 CA142538NCI NIH HHS P50 CA174523NHGRI NIH HHS R01 HG006137NIEHS NIH HHS T32 ES007018NIGMS NIH HHS R35 GM118102NIH HHS P01 CA114046NIH HHS P01 CA142538NIH HHS P50 CA174523NIH HHS R01 HG006137NIH HHS R35 GM118102NIH HHS T32 ES007018
6 · The paper itself

Abstract

High-throughput DNA sequencing enables detection of copy number variations (CNVs) on the genome-wide scale with finer resolution compared to array-based methods but suffers from biases and artifacts that lead to false discoveries and low sensitivity. We describe CODEX2, as a statistical framework for full-spectrum CNV profiling that is sensitive for variants with both common and rare population frequencies and that is applicable to study designs with and without negative control samples. We demonstrate and evaluate CODEX2 on whole-exome and targeted sequencing data, where biases are the most prominent. CODEX2 outperforms existing methods and, in particular, significantly improves sensitivity for common CNVs.

Indexed as

DNA Copy Number VariationsHigh-Throughput Nucleotide SequencingGenomicsHumansMelanomaCopy number variationLatent factorNegative controlNext-generation sequencingNormalization

Identifiers

PMID30477554
PMCPMC6260772

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.