ArticleNature communications2016
High-dimensional genomic data bias correction and data integration using MANCIE.
Article in Nature communications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
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- Interpretable meta-learning of multi-omics data for survival analysis and pathway enrichment.Bioinformatics (Oxford, England) · 2023Article
- Comparative analysis of dimension reduction methods for cytometry by time-of-flight data.Nature communications · 2023Article
- Intrinsic bias estimation for improved analysis of bulk and single-cell chromatin accessibility profiles using SELMA.Nature communications · 2022Article
- DeepProg: an ensemble of deep-learning and machine-learning models for prognosis prediction using multi-omics data.Genome medicine · 2021Article
- Predictors of colorectal cancer survival using cox regression and random survival forests models based on gene expression data.PloS one · 2021Article
- A novel single-cell based method for breast cancer prognosis.PLoS computational biology · 2020Article
- Spectrum: fast density-aware spectral clustering for single and multi-omic data.Bioinformatics (Oxford, England) · 2020Article
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- Overexpression of MUC1 predicts poor prognosis in patients with breast cancer.Oncology reports · 2019Article
- Trends in the characteristics of human functional genomic data on the gene expression omnibus, 2001-2017.Laboratory investigation; a journal of technical methods and pathology · 2019Article
- High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis.Frontiers in genetics · 2019Article
- An ontology-based method for assessing batch effect adjustment approaches in heterogeneous datasets.Bioinformatics (Oxford, England) · 2018Article
- Characterization of H5N1 Influenza Virus Quasispecies with Adaptive Hemagglutinin Mutations from Single-Virus Infections of Human Airway Cells.Journal of virology · 2018Article
- Combining Pathway Identification and Breast Cancer Survival Prediction via Screening-Network Methods.Frontiers in genetics · 2018Article
- VGLL4 Selectively Represses YAP-Dependent Gene Induction and Tumorigenic Phenotypes in Breast Cancer.Scientific reports · 2017Article
- Imputation for transcription factor binding predictions based on deep learning.PLoS computational biology · 2017Article
- CAM: A quality control pipeline for MNase-seq data.PloS one · 2017Article
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14 authors.
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Abstract
High-dimensional genomic data analysis is challenging due to noises and biases in high-throughput experiments. We present a computational method matrix analysis and normalization by concordant information enhancement (MANCIE) for bias correction and data integration of distinct genomic profiles on the same samples. MANCIE uses a Bayesian-supported principal component analysis-based approach to adjust the data so as to achieve better consistency between sample-wise distances in the different profiles. MANCIE can improve tissue-specific clustering in ENCODE data, prognostic prediction in Molecular Taxonomy of Breast Cancer International Consortium and The Cancer Genome Atlas data, copy number and expression agreement in Cancer Cell Line Encyclopedia data, and has broad applications in cross-platform, high-dimensional data integration.
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