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

被引：14

作者：

Hahne, Florian ^{[1
]}

Arlt, Dorit

Sauermann, Mamatha

Majety, Meher

Poustka, Annemarie

Wiemann, Stefan

Huber, Wolfgang

机构：

[1] German Canc Res Ctr, Div Mol Genome Anal, INF 580, D-69120 Heidelberg, Germany

[2] EMBL, European Bioinformat Inst, Cambridge CB10 1SD, England

来源：

GENOME BIOLOGY | 2006年 / 7卷 / 08期

关键词：

D O I：

10.1186/gb-2006-7-8-r77

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

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.

引用

页数：12

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