The extra-cellular RNA processing toolkit (exceRpt) was designed to handle the variable contamination and often poor quality data obtained from low input smallRNA-seq samples such as those obtained from extra-cellular preparations. However the tool is perfectly capable of processing data from more standard cellular/tissue samples.

view exceRpt on Github


Deep integration of RNAseq and mass-spec proteomics data. Exploits transcript-level expression estimates from RNA-seq to set prior likelihoods and enable protein isoform abundances to be directly estimated from LC–MS/MS. The approach respects the observation that most genes appear to express a dominant isoform in a given cell type or tissue.

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The Kitchen Laboratory specialises in computational biology, functional genomics, and non-invasive diagnostics. We apply state-of-the-art statistical/machine-learning approaches and leverage the massive power and flexibility of cloud-computing to define novel biomarkers of cardiovascular disease, type 2 diabetes, neurodegenerative diseases, and various cancers.

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