ArticleGenome biology2006
Statistical methods and software for the analysis of highthroughput reverse genetic assays using flow cytometry readouts.
Article in Genome biology, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- HSV-1 cellular model reveals links between aggresome formation and early step of Alzheimer's disease.Translational psychiatry · 2023Review
- Computational analysis of high-throughput flow cytometry data.Expert opinion on drug discovery · 2012Review
- A computational framework to emulate the human perspective in flow cytometric data analysis.PloS one · 2012Article
- How to understand the cell by breaking it: network analysis of gene perturbation screens.PLoS computational biology · 2010Article
- Scalable analysis of flow cytometry data using R/Bioconductor.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2009Article
- Bridging the Divide between Manual Gating and Bioinformatics with the Bioconductor Package flowFlowJo.Advances in bioinformatics · 2009Article
- A survey of flow cytometry data analysis methods.Advances in bioinformatics · 2009Article
- COPI complex is a regulator of lipid homeostasis.PLoS biology · 2008Article
- Functional studies on transfected cell microarray analysed by linear regression modelling.Nucleic acids research · 2008Article
- Analysis of cell-based RNAi screens.Genome biology · 2006Article
- Statistical methods and software for the analysis of highthroughput reverse genetic assays using flow cytometry readouts.Genome biology · 2006Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.