Evidence map›Paper›PMID 28122605›Full record

ArticleGenome biology2017

Estimating and accounting for tumor purity in the analysis of DNA methylation data from cancer studies.

Xiaoqi Zheng, Naiqian Zhang, Hua-Jun Wu, Hao Wu

Abstract read
In one paragraph

Article in Genome biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.

0numbers the graph read from it
0cells of the map it votes in
85citing 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

85 citing papers in PubMed.

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25 more citing papers are in PubMed but not listed here.

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.

Xiaoqi ZhengDepartment of Mathematics, Shanghai Normal University, Shanghai, 200234, China. xqzheng@shnu.edu.cn.
Naiqian ZhangDepartment of Mathematics, Weifang University, Weifang, Shandong, 261061, China.
Hua-Jun WuDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA, 02215, USA.
Hao WuDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, 1518 Clifton Road, Atlanta, Georgia, 30322, USA. hao.wu@emory.edu.

Funding

Statistical Methods for Single-Cell RNA-SeqR01GM122083 · NIGMS · EMORY UNIVERSITY · PI WU, HAO · 2016 to 2020
$1.7M
NIGMS NIH HHS R01 GM122083
6 · The paper itself

Abstract

We present a set of statistical methods for the analysis of DNA methylation microarray data, which account for tumor purity. These methods are an extension of our previously developed method for purity estimation; our updated method is flexible, efficient, and does not require data from reference samples or matched normal controls. We also present a method for incorporating purity information for differential methylation analysis. In addition, we propose a control-free differential methylation calling method when normal controls are not available. Extensive analyses of TCGA data demonstrate that our methods provide accurate results. All methods are implemented in InfiniumPurify.

Indexed as

DNA MethylationEpigenesis, GeneticAlgorithmsCluster AnalysisComputer SimulationCpG IslandsEpigenomicsHumansNeoplasmsROC CurveCancer epigenomicsDifferential methylationDNA methylationTumor purity

Identifiers

PMID28122605
PMCPMC5267453

What OpenQuestion holds

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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.