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powerNest: illuminating error in qPCR experiment design

PowerNest is a software tool enabling experimenters to explore the effect of sampling on noise propagation throughout qPCR assays. The sampling process is assumed to be comprised of a number of levels; the acquisition of a sample and the preparation of extracted material, reverse-transcription of the mRNA, and the qPCR itself. Given a small set of data, representative of a larger assay, the error at each stage of the experiment is profiled using a nested-ANOVA.

Armed with this information, PowerNest allows the experimenter to explore the effects of modifications to the experimental design on the expected total error of the assay. When given the financial cost of replicates at each level, PowerNest will calculate a cost-optimal sampling-plan, delivering an experiment design that will minimise processing error and maximise the statistical resolution of the assay.

powerNest 0.5.7 released

Version: 
0.5.7

This version contains minor UI tweaks to improve rendering on Windows platforms and an installer. Also improved handling of pre-allocated data.

Can now delete selections by right-clicking a node with the mouse.

Projects: 

e-Science Research

Speaker(s): 
Presentation Type: 
invited

We explain how e-Science is essential to providing the context in terms of methods, tools and infrastructure for the development of a virtual fly brain. We show examples of steering computational processes, managing knowledge in the spatial context of an organism and formulation of models in developmental biology.

Date and time: 
Monday, 21 September, 2009 - 14:00
Location: 
Fly Brain Behaviour Workshop, Oxford, UK
Projects: 

powerNest

Version: 
0.5

PowerNest (www.powernest.net) is a software tool enabling experimenters to explore the effect of sampling on noise propagation throughout qPCR assays. The sampling process is assumed to be comprised of a number of levels; the acquisition of a sample and the preparation of extracted material, reverse-transcription of the mRNA, and the qPCR itself. Given a small set of data, representative of a larger assay, the error at each stage of the experiment is profiled using a nested-ANOVA.

Projects: 

GeneE: Manage your microarray data more effectively

Speaker(s): 
Presentation Type: 
demo

A 20-minute demonstration on the benefits of using GeneE to manage and analyse data acquired in gene expression studies.

Date and time: 
Wednesday, 10 September, 2008 - 13:50
Location: 
Appleton Tower Demo Room 2, e-Science All Hands Meeting 2008, Edinburgh, UK
Projects: 

Microarrays in Minutes: Streamlining Gene Expression Data Analyses

Speaker(s): 
Presentation Type: 
talk

The main aim of this project is to provide biologists with a compact, efficient, and uncomplicated software platform for the robust analysis, intuitive representation, and reliable preservation of all data generated by high-throughput gene expression analysis techniques; such as quantitative real-time PCR (qPCR) or microarrays.

Date and time: 
Wednesday, 10 September, 2008 - 11:00
Location: 
e-Science All Hands Meeting 2008, Edinburgh, UK
Projects: 

Wrapping Tools to Automate Workflows for Gene Therapy in Cystic Fibrosis

NeSC Research Seminar Series
Speaker: 
Rob Kitchen

Currently, the analysis of gene expression data generated by microarray and real-time PCR experiments is a slow process, often taking several weeks to properly process data from a small number of patients. In anticipation of a new clinical trial expected to involve 200 patients it is necessary to improve the efficiency of these analyses, through automation, in order to return meaningful biological data on a much shorter time scale.

Date and time: 
Wednesday, 17 October, 2007 - 11:00
Length: 
45 minutes
Location: 
Cramond
Projects: 

Wrapping Tools to Automate Workflows for Gene Expression Analyses in Cystic Fibrosis

NeSC Research Seminar Series
Speaker: 
Rob Kitchen

Currently, the analysis of gene expression data generated by microarray and real-time PCR experiments is a slow process, often taking several weeks to properly process data from a small number of patients. In anticipation of a new clinical trial expected to involve 200 patients it is necessary to improve the efficiency of these analyses, through automation, in order to return meaningful biological data on a much shorter time scale.

Date and time: 
Tuesday, 4 September, 2007 - 14:00
Length: 
60 minutes
Location: 
Newhaven
Projects: