inst/ProstarApp/md/prostarPresentation.md

In Prostar: Provides a GUI for DAPAR

Data management

• Conversion: To import a tabulated (CSV, excel) file containing quantitative data and convert it into an MSnset structure.
• Loading: To open an Msnset structure that has been previously constructed.
• Exporting: To save a partially/completely processed dataset and to download the data analysis results.
• Demo data: Toy datasets are available to discover Prostar potential in the simplest way.

Data processing

• Filtering: To prune the protein or peptide list according to various criteria (number of missing values, character string matching).
• Normalization: To correct batch or group effects.
• Imputation: By taking into account the very nature of each missing value.
• Aggregation: For peptide-level datasets, it is possible to estimate protein abundances.
• Hypothesis testing: To compute the significance of each protein differential abundance.

Data mining

• Descriptive statistics: Available at any stage of the analysis, for data exploration and visualization.
• Differential analysis: To select a list of differentially abundant proteins with a controlled false discovery rate.
• Gene Ontology analysis: To map a protein list onto GO terms and test category enrichment.

Prostar documentation built on April 11, 2021, 6 p.m.