Computational protocol: Proteomics Analysis with a Nano Random Forest Approach Reveals Novel Functional Interactions Regulated by SMC Complexes on Mitotic Chromosomes*

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Protocol publication

[…] Proteins were separated into high- and low-molecular weight fractions by SDS-PAGE, in-gel digested using trypsin (), and separated into 30 fractions each using strong cation-exchange chromatography (SCX). The individual SCX fractions were desalted using StageTips () and analyzed by liquid chromatography-MS on an LTQ-Orbitrap (Thermo Fisher Scientific) coupled to high-performance liquid chromatography via a nanoelectrospray ion source. The six most intense ions of each full mass spectrum acquired in the Orbitrap analyzer were fragmented and analyzed in the linear-ion trap. The MS data were analyzed using MaxQuant 1.4.0.3 for generating peak lists, searching peptides, and protein identification (), using the UniProt Gallus gallus protein database (release 2013_07 containing 17598 entries) and our in-house chicken database as a reference (supplemental Table S1). The precursor mass tolerance was set to 20 parts per million (ppm) for the first search and 6 ppm for the main search. Fragment ions were searched with a mass tolerance of 20 ppm. A minimum of 2 razors (unique) peptides and a false-discovery rate (FDR) of 1% were required for protein quantification. The MS proteomics data and all parameters used in MaxQuant were deposited in the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository under the data set identifier PXD003427 (, ). The annotated spectra are able to be accessed in MS-viewer (http://prospector2.ucsf.edu/prospector/cgi-bin/msform.cgi?form=msviewer) with the search key rekeqln3ua (). [...] NanoRF analysis is based on the supervised algorithm Random Forests (http://stat-www.berkeley.edu/users/breiman/RandomForests) and the R RandomForest package (http://cran.r-project.org/web/packages/randomForest/). The nanoRF tool package is available from the Github repository (https://github.com/EarnshawLab/nanoRF). The missing values were replaced by the median SILAC value of the experiment. We assessed the classification/fractionation quality by receiver operating characteristic (ROC)-curve analysis and the Matthews correlation coefficient (MCC). […]

Pipeline specifications

Software tools MaxQuant, MS-Viewer, randomforest
Databases ProteomeXchange
Applications Miscellaneous, MS-based untargeted proteomics
Diseases Substance-Related Disorders