apmsWAPP-package: Pre- and Postprocessing for AP-MS data analysis

In apmsWAPP: Pre- and Postprocessing for AP-MS data analysis based on spectral counts

Description

The package apmsWAPP provides a complete workflow for the analysis of AP-MS data, based on replicate single-bait purifications including negative controls.
It comprises the three main parts of pre-processing, scoring and postprocessing of interaction proteins:
For pre-processing, five different normalization methods and a filtering procedure is provided.
For scoring protein-protein-interactions, either the method of SAINT or a two-stage-poisson model (TSPM) adapted to AP-MS data can be chosen.
For postprocessing, the user can choose between the permutation-based approach of Westfall&Young (applicable to both, SAINT and TSPM) and the adjustment procedure of Benjamini-Hochberg (applicable to TSPM). Postprocessing results in the generation of p-values for each interaction candidate, allowing to control the number of false-positive interactions.

Details

Package:	apmsWAPP
Type:	Package
Version:	1.0
Date:	2013-03-14
License:	LGPL-3

The two main function calls are: saint_permF (framework based on SAINT) and tspm_apms (framework based on TSPM).
Note: saint_permF can only be executed in a linux environment and SAINT must be installed accordingly. tspm_apms is applicable in a windows and a linux environment.

Author(s)

Martina Fischer ([e-mail])

References

Fischer M, Zilkenat S, Gerlach R, Wagner S, Renard BY. Pre- and Post-Processing Workflow for Affinity Purification Mass Spectrometry Data. Journal of Proteome Research 2014.

Choi H, Larsen B, Lin Z-Y, et al. SAINT: probabilistic scoring of affinity purification-mass spectrometry data. Nature Methods 2011.

Auer PL, Doerge RW. A two-stage Poisson model for testing RNA-Seq data. Statistical Applications in Genetics and Molecular Biology 2011.

apmsWAPP documentation built on May 2, 2019, 3:23 a.m.