Progenesis Stats
Category Proteomics>Mass Spectrometry Analysis/Tools
Abstract Progenesis Stats is an advanced, easy-to-use 'statistical analysis' tool for further interrogation of proteomics data.
The unique approach of Progenesis LC-MS (see G6G Abstract Number 20368), Progenesis MALDI (an additional product from this manufacturer) and Progenesis SameSpots (an additional product from this manufacturer) produces results with No missing values, so you can confidently apply both univariate and multivariate statistical techniques for a complete exploration of your protein expression data.
This advanced tool solves the statistics headache for proteomics researchers.
The latest version of Progenesis Stats seamlessly integrates with the Progenesis LC-MS, Progenesis MALDI and Progenesis SameSpots workflows.
What this means for your proteomics data analysis --
Principal Components Analysis (PCA) - This is an unsupervised technique (i.e. it does Not use any knowledge of the groupings of the data) which provides a simplified graphical representation of the multidimensional data.
It is useful for determining if samples have the groupings expected or if there are any outliers in the data. Examining the PCA plot is a useful Quality Control check before further analysis of your data.
Correlation Analysis - Proteins or peptides are grouped by their 'expression patterns' using correlation analysis and hierarchical clustering.
This unsupervised, multivariate analysis provides a true snapshot of protein activity across an experiment and identifies features in the same biological processes and pathways that may characterize disease states.
The results are shown in an interactive dendrogram tree where similar expression profiles cluster together.
Data can be explored at the group level on the dendrogram, and the corresponding 'expression profiles' update on-the-fly.
Power Analysis - The power of a statistical test can be defined as the probability that it will find a significant expression change where it exists.
It depends on the sample size and can calculate the effect of running a different number of replicates.
A generally accepted power threshold is 80%. A power analysis can be performed on a pilot study and the number of replicates required to achieve the target power of 80% can be calculated.
False Discovery Rate and Q-values - The q-value tells us the expected proportion of false positives if that feature’s p-value is chosen as the significance threshold. This provides greater power for finding truly significant features.
Classify significant features using tags - Groups of proteins or peptides can be classified using the new color coded tags which gives exceptional flexibility when you are surveying your data.
This highly effective and visual approach helps you to determine which features are interesting and therefore warrant further investigation.
Display interesting results on your images - If you are using Progenesis Stats to view 2D results analyzed by Progenesis SameSpots, you can highlight spots on the gel image which you have tagged, or which cluster in the correlation analysis.
This allows you to quickly pinpoint which spots on the gel image have similar behavior patterns, and see the actual locations of the spots on the gel and print or save this image.
Advanced Statistical Analysis features/capabilities include: Multivariate statistical analysis of selected features (spots, proteins or peptides) from Progenesis SameSpots and Progenesis LC-MS.
Data Table --
- a) Calculation and display of ANOVA p-values;
- b) Calculation and display of q-values for indication of False Discovery Rate (FDR);
- c) Feature(s) shown in expression profile view;
- d) Selected feature(s) highlighted on PCA plot;
- e) Selected feature(s) highlighted on Correlation Analysis dendrogram view;
- f) Calculation and display of feature power; and g) Color coding of data in the table by cluster.
Feature Tags --
- a) Color coded tags to assist with data exploration;
- b) Right click on highlighted group of features to tag;
- c) Add name label to spot tag; and
- d) Filter spot list by tags.
Tag editing --
- a) Features can be tagged multiple times; and
- b) Feature tags are maintained throughout the workflow.
Image View* --
- a) Display of the whole image with selected features highlighted; and
- b) Color coded display of features which cluster in the correlation analysis.
- *Currently only available for the analysis of 2D image analysis data from Progenesis SameSpots.
Principal Components Analysis (PCA) --
- a) Calculate principal components based on all features;
- b) Visualization of samples and features score and as loading plots on the PCA graph with samples and features highlighted for visual confirmation of clustering;
- c) Color coded display of features which cluster in the correlation analysis;
- d) Selection of principal components to display on the axis; and
- e) Zoom functionality.
Correlation Analysis --
- a) Correlation analysis and visualization of feature expression;
- b) Visualization of the clustered features showing correlation expression profiles;
- c) Hierarchical clustering of features based on expression profile data and visualization with an interactive dendrogram;
- d) Multiple selections of dendrogram nodes for expression profile comparison;
- e) Multiple group selection on the dendrogram by setting the click and drag "pruning threshold" for expression profile comparison; and f) Zoom functionality.
Power Analysis --
- a) Post hoc, per feature power calculations; and
- b) Prediction of required replicates for 80% power per spot based on measured data.
System Requirements
Contact manufacturer.
Manufacturer
- Nonlinear Dynamics Ltd.
- Keel House
- Garth Heads
- Newcastle upon Tyne
- NE1 2JE
- UK
- Tel: +44(0)191 230 2121
- info@nonlinear.com
- Nonlinear USA Inc
- 4819 Emperor Blvd
- Suite 400
- Durham
- NC 27703
- USA
- Tel: 919 313 4556
Manufacturer Web Site Progenesis Stats
Price Contact manufacturer.
G6G Abstract Number 20369
G6G Manufacturer Number 104017