Cargando…

Construction and use of gene expression covariation matrix

BACKGROUND: One essential step in the massive analysis of transcriptomic profiles is the calculation of the correlation coefficient, a value used to select pairs of genes with similar or inverse transcriptional profiles across a large fraction of the biological conditions examined. Until now, the ch...

Descripción completa

Detalles Bibliográficos
Autores principales:	Hennetin, Jérôme, Pehkonen, Petri, Bellis, Michel
Formato:	Texto
Lenguaje:	English
Publicado:	BioMed Central 2009
Materias:	Methodology Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2720390/ https://www.ncbi.nlm.nih.gov/pubmed/19594909 http://dx.doi.org/10.1186/1471-2105-10-214

Ejemplares similares

Generation of Gene Ontology benchmark datasets with various types of positive signal
por: Törönen, Petri, et al.
Publicado: (2009)

Theme discovery from gene lists for identification and viewing of multiple functional groups
por: Pehkonen, Petri, et al.
Publicado: (2005)

RCMAT: a regularized covariance matrix approach to testing gene sets
por: Yates, Phillip D, et al.
Publicado: (2009)

Model errors in tree biomass estimates computed with an approximation to a missing covariance matrix
por: Magnussen, Steen, et al.
Publicado: (2015)

The application of sparse estimation of covariance matrix to quadratic discriminant analysis
por: Sun, Jiehuan, et al.
Publicado: (2015)

Case-control geographic clustering for residential histories accounting for risk factors and covariates
por: Jacquez, Geoffrey M, et al.
Publicado: (2006)

TAFFEL: Independent Enrichment Analysis of gene sets
por: Kurki, Mitja I, et al.
Publicado: (2011)

Using the half normal distribution to quantify covariate balance in cluster-randomized pragmatic trials
por: Huang, Jin, et al.
Publicado: (2021)

Construction of land-use change matrix and estimation of greenhouse gas inventory focusing on settlements in South Korea
por: Choi, Sol-E, et al.
Publicado: (2023)

Selecting Spatial Scale of Covariates in Regression Models of Environmental Exposures
por: Grant, Lauren P., et al.
Publicado: (2015)

Chromosomal Distribution of PcG Proteins during Drosophila Development
por: Nègre, Nicolas, et al.
Publicado: (2006)

An integrated strategy for efficient vector construction and multi-gene expression in Plasmodium falciparum
por: Wagner, Jeffrey C, et al.
Publicado: (2013)

A further critique of the analytic strategy of adjusting for covariates to identify biologic mediation
por: Kaufman, Jay S, et al.
Publicado: (2004)

Restricted maximum likelihood estimation of genetic principal components and smoothed covariance matrices
por: Meyer, Karin, et al.
Publicado: (2005)

A strategy to build and validate a prognostic biomarker model based on RT-qPCR gene expression and clinical covariates
por: Tournoud, Maud, et al.
Publicado: (2015)

Quantitative gene set analysis generalized for repeated measures, confounder adjustment, and continuous covariates
por: Turner, Jacob A., et al.
Publicado: (2015)

A simple procedure for the comparison of covariance matrices
por: Garcia, Carlos
Publicado: (2012)

Modelling animal movement as Brownian bridges with covariates
por: Kranstauber, Bart
Publicado: (2019)

Penalized Ordinal Regression Methods for Predicting Stage of Cancer in High-Dimensional Covariate Spaces
por: Gentry, Amanda Elswick, et al.
Publicado: (2015)

Individual level covariate adjusted conditional autoregressive (indiCAR) model for disease mapping
por: Huque, Md. Hamidul, et al.
Publicado: (2016)

Choosing an imbalance metric for covariate-constrained randomization in multiple-arm cluster-randomized trials
por: Ciolino, Jody D., et al.
Publicado: (2019)

Planning a method for covariate adjustment in individually randomised trials: a practical guide
por: Morris, Tim P., et al.
Publicado: (2022)

A comparison of covariate adjustment approaches under model misspecification in individually randomized trials
por: Tackney, Mia S., et al.
Publicado: (2023)

More efficient and inclusive time-to-event trials with covariate adjustment: a simulation study
por: Momal, Raphaëlle, et al.
Publicado: (2023)

The risks and rewards of covariate adjustment in randomized trials: an assessment of 12 outcomes from 8 studies
por: Kahan, Brennan C, et al.
Publicado: (2014)

The effect of covariate adjustment for baseline severity in acute stroke clinical trials with responder analysis outcomes
por: Garofolo, Kyra M, et al.
Publicado: (2013)

The covariant lattice construction
por: Schellekens, Adrian Norbert
Publicado: (1989)

Detection of suspicious interactions of spiking covariates in methylation data
por: Sieg, Miriam, et al.
Publicado: (2020)

Censcyt: censored covariates in differential abundance analysis in cytometry
por: Gerber, Reto, et al.
Publicado: (2021)

Incorporation of covariates in simultaneous localization of two linked loci using affected relative pairs
por: Chiu, Yen-Feng, et al.
Publicado: (2010)

Covariate balance in a Bayesian propensity score analysis of beta blocker therapy in heart failure patients
por: McCandless, Lawrence C, et al.
Publicado: (2009)

In search of induction and latency periods: Space-time interaction accounting for residential mobility, risk factors and covariates
por: Jacquez, Geoffrey M, et al.
Publicado: (2007)

Cyclical regression covariates remove the major confounding effect of cyclical developmental gene expression with strain-specific drug response in the malaria parasite Plasmodium falciparum
por: Foster, Gabriel J., et al.
Publicado: (2022)

Application of the common base method to regression and analysis of covariance (ANCOVA) in qPCR experiments and subsequent relative expression calculation
por: Ganger, Michael T., et al.
Publicado: (2020)

Enhanced construction of gene regulatory networks using hub gene information
por: Yu, Donghyeon, et al.
Publicado: (2017)

Covariance of maximum likelihood evolutionary distances between sequences aligned pairwise
por: Dessimoz, Christophe, et al.
Publicado: (2008)

Multidimensional mutual information methods for the analysis of covariation in multiple sequence alignments
por: Clark, Greg W, et al.
Publicado: (2014)

Incorporation of subject-level covariates in quantile normalization of miRNA data
por: Suyundikov, Anvar, et al.
Publicado: (2015)

Block Forests: random forests for blocks of clinical and omics covariate data
por: Hornung, Roman, et al.
Publicado: (2019)

Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data
por: Martin, Dietmar E, et al.
Publicado: (2004)

Cannot write session to /tmp/vufind_sessions/sess_uou2059jatb95qsegg7d145v24