Software Developed In house

Bioinformatics tools we have developed in house to address specific data analysis or reporting needs.  The packages themselves are open source and freely available; internally they can be accessed via a graphical user interface provided by a local GenePattern server. The tools available can be found at http://bio.proteome.org.au or Plotting Gene Ontology  (ZIP 694.1KB) (The PloGO link points to a zip file) and Bioconductor Package

Technique

Software or Workflow

Tool / availability

Publication

SWATH

  • SwathXtend Method of library merging and data analysis tool

Bioconductor package

Wu et al, MCP 2016; SwathXtend library merging module takes a seed library and one or more add-on libraries and generating an extended assay library ready to be used for SWATH extraction

BioPlex

  • Bioplex data normalization and analysis methodology

R Recipes

Breen et al, Scientific Reports 2016 and Cytokine 2015

TMT

  • TMTPrePro R package for analysis of TMT data

Internal tool

Mirzaei et al, Methods Mol Biol, to appear

iTRAQ

  • Data analysis methodology and package

Internal tool

Pascovici et al, JPR 2015

Label Free

  • SCRAppy suite of scripts for analysis of label free data

Internal tool

Nielson et al, Methods Mol Biol 2013

GO

  • PloGO R package for GO annotation and abundance plotting and enrichment analysis

Internal tool

Package available

Pascovici et al, Proteomics 2012

 

 

Areas of expertise/strength

  • Statistical and machine-learning based data analysis of a wide variety of novel proteomic techniques (SWATH, immunoassays, protein arrays, labelled isobaric, label free)
  • Data analysis capability in areas such as GLM,  hierarchical designs, linear and mixed models, classification, machine learning and statistical significance analysis
  • Experiment design for proteomics, block design
  • Screening for cytokine, chemokines, interleukins and hormones for high through put diagnostics and clinical analysis with in-depth Bio-Plex┬« analysis
  • Agricultural plant proteomics with an emphasis on stress responses to drought, disease or pathogens
  • Deriving insights from close collaborations with biologists, analytical chemists, clinicians and various other researchers