A Quantitation tool for Proteomics Experiments #Quantitative proteomics analyzer #Quantitation tool #Downstream statistical analysis #Quantitative proteomics #Proteomics #Statistical analysis
Inferno can perform various downstream statistical analysis, normalization, data reduction, and hypothesis testing steps on quantitative proteomics data. The graphical interface, written in C#, provides a convenient way to visualize the data during the analysis process. All algorithms are implemented in R and the connectivity between R and .NET is achieved using StatconnDCOM server.
Inferno can group experiment runs using "Factors" based on treatment conditions (fixed effects), run blocks, LC columns (random effects) etc. Statistical properties of the data can be explored using the extensive plotting functions in Inferno.
Techniques for missing value imputation, removal of technical variations, inferring protein level information for bottom-up proteomics experiments, and hypothesis testing methods are implemented.
Significance tests like ANOVA can be performed using multi-level models taking into account the fixed and random effects or non-parametric methods such as Mann-Whitney test, Kruskal-Walis test etc.
Give Inferno a try to fully assess its quantitative proteomics data management capabilities!
System requirements
- NET framework 2.0
- R for Windows 2.10.1
- statconnDCOM
Inferno 1.0
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- Windows All
- file size:
- 3.9 MB
- filename:
- InfernoSetup.exe
- main category:
- Science / CAD
- developer:
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