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Statistical methods and software for the analysis of highthroughput reverse genetic assays using flow cytometry readouts

Highthroughput cell-based assays with flow cytometric readout provide a powerful technique for identifying components of biologic pathways and their interactors. Interpretation of these large datasets requires effective computational methods. We present a new approach that includes data pre-processi...

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Detalles Bibliográficos
Autores principales: Hahne, Florian, Arlt, Dorit, Sauermann, Mamatha, Majety, Meher, Poustka, Annemarie, Wiemann, Stefan, Huber, Wolfgang
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1779598/
https://www.ncbi.nlm.nih.gov/pubmed/16916453
http://dx.doi.org/10.1186/gb-2006-7-8-r77
Descripción
Sumario:Highthroughput cell-based assays with flow cytometric readout provide a powerful technique for identifying components of biologic pathways and their interactors. Interpretation of these large datasets requires effective computational methods. We present a new approach that includes data pre-processing, visualization, quality assessment, and statistical inference. The software is freely available in the Bioconductor package prada. The method permits analysis of large screens to detect the effects of molecular interventions in cellular systems.