Cargando…

Leveraging expression from multiple tissues using sparse canonical correlation analysis and aggregate tests improves the power of transcriptome-wide association studies

Transcriptome-wide association studies (TWAS) test the association between traits and genetically predicted gene expression levels. The power of a TWAS depends in part on the strength of the correlation between a genetic predictor of gene expression and the causally relevant gene expression values....

Descripción completa

Detalles Bibliográficos
Autores principales:	Feng, Helian, Mancuso, Nicholas, Gusev, Alexander, Majumdar, Arunabha, Major, Megan, Pasaniuc, Bogdan, Kraft, Peter
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Public Library of Science 2021
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057593/ https://www.ncbi.nlm.nih.gov/pubmed/33831007 http://dx.doi.org/10.1371/journal.pgen.1008973

Ejemplares similares

Leveraging local ancestry to detect gene-gene interactions in genome-wide data
por: Aschard, Hugues, et al.
Publicado: (2015)

twas_sim, a Python-based tool for simulation and power analysis of transcriptome-wide association analysis
por: Wang, Xinran, et al.
Publicado: (2023)

Leveraging eQTLs to identify individual-level tissue of interest for a complex trait
por: Majumdar, Arunabha, et al.
Publicado: (2021)

Accurate estimation of SNP-heritability from biobank-scale data irrespective of genetic architecture
por: Hou, Kangcheng, et al.
Publicado: (2019)

Large-scale transcriptome-wide association study identifies new prostate cancer risk regions
por: Mancuso, Nicholas, et al.
Publicado: (2018)

Author Correction: Large-scale transcriptome-wide association study identifies new prostate cancer risk regions
por: Mancuso, Nicholas, et al.
Publicado: (2019)

A summary-statistics-based approach to examine the role of serotonin transporter promoter tandem repeat polymorphism in psychiatric phenotypes
por: Majumdar, Arunabha, et al.
Publicado: (2021)

Genome-wide sparse canonical correlation of gene expression with genotypes
por: Parkhomenko, Elena, et al.
Publicado: (2007)

Methods for fine-mapping with chromatin and expression data
por: Roytman, Megan, et al.
Publicado: (2018)

Robust sparse canonical correlation analysis
por: Wilms, Ines, et al.
Publicado: (2016)

Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights
por: Gusev, Alexander, et al.
Publicado: (2018)

Integrative analysis of Dupuytren's disease identifies novel risk locus and reveals a shared genetic etiology with BMI
por: Major, Megan, et al.
Publicado: (2019)

Grand Canonical Ensembles of Sparse Networks and Bayesian Inference
por: Bianconi, Ginestra
Publicado: (2022)

Possibilistic Estimation of Distributions to Leverage Sparse Data in Machine Learning
por: Tettamanzi, Andrea G. B., et al.
Publicado: (2020)

Group sparse canonical correlation analysis for genomic data integration
por: Lin, Dongdong, et al.
Publicado: (2013)

Leveraging omics data to boost the power of genome-wide association studies
por: Lin, Zhaotong, et al.
Publicado: (2022)

Leveraging pleiotropic association using sparse group variable selection in genomics data
por: Sutton, Matthew, et al.
Publicado: (2022)

Leveraging biological and statistical covariates improves the detection power in epigenome-wide association testing
por: Huang, Jinyan, et al.
Publicado: (2020)

Dispersion, sedimentation and aggregation of multi-walled carbon nanotubes as affected by single and binary mixed surfactants
por: Li, Helian, et al.
Publicado: (2019)

Sparse canonical correlation analysis for identifying, connecting and completing gene-expression networks
por: Waaijenborg, Sandra, et al.
Publicado: (2009)

Optimized design of single-cell RNA sequencing experiments for cell-type-specific eQTL analysis
por: Mandric, Igor, et al.
Publicado: (2020)

The Agile Leader: Leveraging the Power of Influence
por: Sochova, Zuzana
Publicado: (2020)

Sparse canonical methods for biological data integration: application to a cross-platform study
por: Lê Cao, Kim-Anh, et al.
Publicado: (2009)

Biomarker Discovery by Sparse Canonical Correlation Analysis of Complex Clinical Phenotypes of Tuberculosis and Malaria
por: Rousu, Juho, et al.
Publicado: (2013)

Sparse kernel canonical correlation analysis for discovery of nonlinear interactions in high-dimensional data
por: Yoshida, Kosuke, et al.
Publicado: (2017)

Sparse genetically defined neurons refine the canonical role of periaqueductal gray columnar organization
por: La-Vu, Mimi Q, et al.
Publicado: (2022)

Testing Equality of Multiple Population Means under Contaminated Normal Model Using the Density Power Divergence
por: Das, Jagannath, et al.
Publicado: (2022)

MicroRNA Target Recognition: Insights from Transcriptome-Wide Non-Canonical Interactions
por: Seok, Heeyoung, et al.
Publicado: (2016)

In situ formation of transcriptional modulators using non-canonical DNA i-motifs
por: Saha, Puja, et al.
Publicado: (2020)

Multivariate association between brain function and eating disorders using sparse canonical correlation analysis
por: Lee, Hyebin, et al.
Publicado: (2020)

Multi-Omics Data Fusion for Cancer Molecular Subtyping Using Sparse Canonical Correlation Analysis
por: Qi, Lin, et al.
Publicado: (2021)

Intelligent Epileptic Seizure Detection and Classification Model Using Optimal Deep Canonical Sparse Autoencoder
por: Hilal, Anwer Mustafa, et al.
Publicado: (2022)

Sparse canonical correlation to identify breast cancer related genes regulated by copy number aberrations
por: Dutta, Diptavo, et al.
Publicado: (2022)

Statistical power of transcriptome‐wide association studies
por: He, Ruoyu, et al.
Publicado: (2022)

Sparse self-attention aggregation networks for neural sequence slice interpolation
por: Wang, Zejin, et al.
Publicado: (2021)

Best practices for multi-ancestry, meta-analytic transcriptome-wide association studies: Lessons from the Global Biobank Meta-analysis Initiative
por: Bhattacharya, Arjun, et al.
Publicado: (2022)

A transcriptome-wide association study of high grade serous epithelial ovarian cancer identifies novel susceptibility genes and splice variants
por: Gusev, Alexander, et al.
Publicado: (2019)

Estimating multivariate similarity between neuroimaging datasets with sparse canonical correlation analysis: an application to perfusion imaging
por: Rosa, Maria J., et al.
Publicado: (2015)

Identifying Imaging Genetics Biomarkers of Alzheimer’s Disease by Multi-Task Sparse Canonical Correlation Analysis and Regression
por: Ke, Fengchun, et al.
Publicado: (2021)

Canon PowerShot digital field guide
por: Guncheon, Michael A
Publicado: (2008)

Cannot write session to /tmp/vufind_sessions/sess_o2c3170orvm7e4gbo4l7bs2dfh