Bioinformatics at APAF
The bioinformatics group was established to support researchers with their data analysis needs and to help them derive experimental insights from their proteomics results. We provide software and tools to support the variety of services provided by the other APAF groups, and have in-depth experience with a variety of commercial and academic projects, with particular areas of strength being cytokine analysis, plant proteomics, and statistical and machine learning based approaches to the analysis of novel proteomic techniques such as SWATH, labelled isobaric techniques, cytokines and label free shotgun proteomics. We have had recent commercial experience in the area of cancer diagnostic tests and agriculturally important plants disease, have participated in national collaborative cross-platform research initiatives, and have engaged in numerous research academic collaborations.
- Available software and services by core technology
- Software tools and workflows developed in-house
- Custom analyses services and case studies
- SWATHXtend - (NEW) APAF developed software to extend peptide assay libraries for improved SWATH analysis
- SWATHXtend Workflow - How the Software works
- iTRAQ typical output from a std analysis - iTRAQ requires some consultation with APAF staff for experimental design and here we show an example of the possible result
Analyse your mascot proteomic results further here
Gene ontology annotation package: PloGO - an R package for summarizing gene ontology annotation and abundance. PloGO is a simple open source R package for plotting gene ontology annotation in a manner similar to other gene ontology plotting tools (e.g. Wego). However, it was designed to incorporate information about abundance in addition to annotation, to handle multiple files and to allow for a targeted collection ofcategories of interest. PloGO was motivated by the analysis of multi-condition label free proteomics experiments, and relies on functionality provided by the GOstats and biomaRt R packages. Now accepted for publication.
PloGO: Plotting Gene Ontology annotation and abundance in multi-condition proteomic experiments: Dana Pascovici, Tim Keighley, Mehdi Mirzaei, Paul A. Haynes and Brett Cooke (proteomics technical brief – accepted, Nov 2011).
Link here to get required PloGO (R version 2.12) bioinformatics package with the documentation. This is a zip file. A newer version compatible with R (version 3.0.1) is now available of PloGO (PloGO version 2.0 R V3.0.1).
We also link to the ExPASy Proteomics Server.