ArticleNucleic acids research2013
Canonical correlation analysis for RNA-seq co-expression networks.
Article in Nucleic acids research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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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.
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Who cites it
37 citing papers in PubMed.
- Article
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- A primer on correlation-based dimension reduction methods for multi-omics analysis.Journal of the Royal Society, Interface · 2023Review
- Investigation of the correlation of successive earthquakes preceding main shocks in the Greek territory.Journal of applied statistics · 2022Article
- ZERO-INFLATED QUANTILE RANK-SCORE BASED TEST (ZIQRANK) WITH APPLICATION TO SCRNA-SEQ DIFFERENTIAL GENE EXPRESSION ANALYSIS.The annals of applied statistics · 2021Article
- The pentose phosphate pathway constitutes a major metabolic hub in pathogenic Francisella.PLoS pathogens · 2021Article
- A network-based computational framework to predict and differentiate functions for gene isoforms using exon-level expression data.Methods (San Diego, Calif.) · 2021Article
- Approaches to Integrating Metabolomics and Multi-Omics Data: A Primer.Metabolites · 2021Review
- The Wild Sugarcane and Sorghum Kinomes: Insights Into Expansion, Diversification, and Expression Patterns.Frontiers in plant science · 2021Article
- Genome-wide functional association networks: background, data & state-of-the-art resources.Briefings in bioinformatics · 2020Review
- Exploring concomitant neuroimaging and genetic alterations in patients with and patients without auditory verbal hallucinations: A pilot study and mini review.The Journal of international medical research · 2020Review
- Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder.Nature communications · 2020Article
- Integration of Online Omics-Data Resources for Cancer Research.Frontiers in genetics · 2020Review
- A Weighted Gene Co-expression Network Analysis Reveals lncRNA Abnormalities in the Peripheral Blood Associated With Ultra-High-Risk for Psychosis.Frontiers in psychiatry · 2020Article
- Cluster analysis of replicated alternative polyadenylation data using canonical correlation analysis.BMC genomics · 2019Article
- A whitening approach to probabilistic canonical correlation analysis for omics data integration.BMC bioinformatics · 2019Article
- Genome-wide dynamic network analysis reveals a critical transition state of flower development in Arabidopsis.BMC plant biology · 2019Article
- Microbiome Multi-Omics Network Analysis: Statistical Considerations, Limitations, and Opportunities.Frontiers in genetics · 2019Review
- Gene co-expression analysis for functional classification and gene-disease predictions.Briefings in bioinformatics · 2018Article
- Bioinformatics challenges and perspectives when studying the effect of epigenetic modifications on alternative splicing.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018Review
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4 authors.
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Abstract
Digital transcriptome analysis by next-generation sequencing discovers substantial mRNA variants. Variation in gene expression underlies many biological processes and holds a key to unravelling mechanism of common diseases. However, the current methods for construction of co-expression networks using overall gene expression are originally designed for microarray expression data, and they overlook a large number of variations in gene expressions. To use information on exon, genomic positional level and allele-specific expressions, we develop novel component-based methods, single and bivariate canonical correlation analysis, for construction of co-expression networks with RNA-seq data. To evaluate the performance of our methods for co-expression network inference with RNA-seq data, they are applied to lung squamous cell cancer expression data from TCGA database and our bipolar disorder and schizophrenia RNA-seq study. The preliminary results demonstrate that the co-expression networks constructed by canonical correlation analysis and RNA-seq data provide rich genetic and molecular information to gain insight into biological processes and disease mechanism. Our new methods substantially outperform the current statistical methods for co-expression network construction with microarray expression data or RNA-seq data based on overall gene expression levels.
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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.