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SAFEGUI: resampling-based tests of categorical significance in gene expression data made easy

Summary: A large number of websites and applications perform significance testing for gene categories/pathways in microarray data. Many of these packages fail to account for expression correlation between transcripts, with a resultant inflation in Type I error. Array permutation and other resampling...

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Detalles Bibliográficos
Autores principales: Gatti, Daniel M., Sypa, Myroslav, Rusyn, Ivan, Wright, Fred A., Barry, William T.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2642635/
https://www.ncbi.nlm.nih.gov/pubmed/19098030
http://dx.doi.org/10.1093/bioinformatics/btn655
Descripción
Sumario:Summary: A large number of websites and applications perform significance testing for gene categories/pathways in microarray data. Many of these packages fail to account for expression correlation between transcripts, with a resultant inflation in Type I error. Array permutation and other resampling-based approaches have been proposed as solutions to this problem. SAFEGUI provides a user-friendly graphical interface for the assessment of categorical significance in microarray studies, while properly accounting for the effects of correlations among genes. SAFEGUI incorporates both permutation and more recently proposed bootstrap algorithms that are demonstrated to be more powerful in detecting differential expression across categories of genes. Availability: http://cebc.unc.edu/software/ Contact: fwright@bios.unc.edu; dmgatti@email.unc.edu