Unknown

Dataset Information

0

Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies.

ABSTRACT: In epigenome-wide association studies (EWAS), different methylation profiles of distinct cell types may lead to false discoveries. We introduce ReFACTor, a method based on principal component analysis (PCA) and designed for the correction of cell type heterogeneity in EWAS. ReFACTor does not require knowledge of cell counts, and it provides improved estimates of cell type composition, resulting in improved power and control for false positives in EWAS. Corresponding software is available at http://www.cs.tau.ac.il/~heran/cozygene/software/refactor.html.

SUBMITTER: Rahmani E 

PROVIDER: S-EPMC5548182 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

Json Xml
altmetric image

Publications

Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies.

Rahmani Elior E   Zaitlen Noah N   Baran Yael Y   Eng Celeste C   Hu Donglei D   Galanter Joshua J   Oh Sam S   Burchard Esteban G EG   Eskin Eleazar E   Zou James J   Halperin Eran E  

Nature methods 20160328 5

In epigenome-wide association studies (EWAS), different methylation profiles of distinct cell types may lead to false discoveries. We introduce ReFACTor, a method based on principal component analysis (PCA) and designed for the correction of cell type heterogeneity in EWAS. ReFACTor does not require knowledge of cell counts, and it provides improved estimates of cell type composition, resulting in improved power and control for false positives in EWAS. Corresponding software is available at http  ...[more]

Similar Datasets

Unknown A comparison of reference-based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies.
| S-EPMC5307731 | biostudies-literature
Unknown Accounting for cellular heterogeneity is critical in epigenome-wide association studies.
| S-EPMC4053810 | biostudies-literature
Unknown Detection of cell-type-specific risk-CpG sites in epigenome-wide association studies.
| S-EPMC6629651 | biostudies-literature
Unknown Estimands in epigenome-wide association studies.
| S-EPMC8086103 | biostudies-literature
Unknown Identification of differentially methylated cell types in epigenome-wide association studies.
| S-EPMC6277016 | biostudies-literature
Unknown Genome-wide association studies and epigenome-wide association studies go together in cancer control.
| S-EPMC5551540 | biostudies-literature
Unknown Epigenome-wide association studies: current knowledge, strategies and recommendations.
| S-EPMC8645110 | biostudies-literature
Unknown The EpiDiverse Plant Epigenome-Wide Association Studies (EWAS) Pipeline.
| S-EPMC8594691 | biostudies-literature
Unknown Genome-wide association studies for bivariate sparse longitudinal data.
| S-EPMC3725885 | biostudies-literature
Unknown A comparative analysis of cell-type adjustment methods for epigenome-wide association studies based on simulated and real data sets.
| S-EPMC6954449 | biostudies-literature