Label-free data analysis pipeline for optimal identification and quantitation
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Latest commit f77f55a Jul 17, 2018


The synapter package provides functionality to re-analyse MSe label-free proteomics data acquired on a Waters Synapt Series mass spectrometer (and probably any Waters instrument). It allows to combine acquisitions that have been optimised for better identification (typically using ion mobility separation - HDMSe) and quantitation accuracy. It also allows to transfer identifications across multiple runs to reduce missing data across an experiment.

The official release is the Bioconductor version, available here. The github page is a useful resource that gives access to all vignettes and manuals.


synapter is available from the Bioconductor repository. The package and its dependencies can be installed with

if (!require("BiocManager"))


synapter comes with plenty of documentation. Have a start with the package documentation page ?synapter and the vignette

 vignette("synapter", package="synapter")

See also the synapter Bioconductor page for on-line access to the vignette and the reference manual.

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PLGS processing

The raw data files produced must first be processed by Water's PLGS software to produce synapter input files. This is described in details in the vignette. Additional information with lots of screenshots can be found in these slides.