In ksong4/NetPhorce: Phosphoproteomics Network Analysis (NetPhorce)

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
library(DT)

Introduction

The following tutorials is based on a single condition experiment data.

1.0 NetPhorce loading

library(NetPhorce)
paste0("NetPhorce Version: ", packageVersion("NetPhorce"))

2.0 Loading One Condition Example

## Loading One Condition Data
data("oneConditionExample", package = "NetPhorce")
DT::datatable(oneConditionExample, 
              rownames = FALSE, 
              options = list(
                pageLength = 5, 
                scrollX = TRUE,
                rownames = FALSE,
                autoWidth = TRUE, 
                columnDefs = list(list(targets=c(7), width = "700px"),
                                  list(className = 'dt.center', targets = "_all"))
              )) 

3.0 Pre-processing the raw MaxQuant data

3.1 Identifying the Key Columns

## Identify the Key Columns
identifiedCols <- confirmColumnNames(rawMaxQuant = oneConditionExample,
                                     positionCol = "Position",
                                     reverseCol = "Reverse",
                                     localizationProbCol = "Localization prob",
                                     potentialContaminationCol = "Potential contaminant",
                                     aminoAcidCol = "Amino acid",
                                     uniqueIDCol = "Protein",
                                     seqWindowIDCol = "Sequence window",
                                     fastaIDCol = "Fasta headers")

3.2 Identifying the pattern for the intensity columns

## Identify the Intensity Columns with Condition, Time Point and Replication Information
intensityCols <- confirmIntensityColumns(rawMaxQuant = oneConditionExample,
                                         intensityPattern = "con_time_rep",
                                         verbose = TRUE)

4.0 Process the raw MaxQuant data

## Process the data based on the identified columns
netPhorceData <- processData(rawMaxQuant = oneConditionExample,
                             processedColNames = identifiedCols,
                             processedIntensity = intensityCols,
                             minReplication = 3,
                             minLocalProb = 0.75)

5.0 Validate the Kinases and Phosphatase data for the processed netPhorce data

## Validating the Kinase/Phosphatase Information
netPhorceData <- validateKinaseTable(netPhorceData = netPhorceData,
                                     defaultKinaseTable = TRUE,
                                     abbrev = "Ath")

6.0 Confirmation on the Regulation Thresholds for the netPhorce data

## Regulation Validation based on user inputs
netPhorceData <- regulationCheck(netPhorceData = netPhorceData,
                                 upReg = 0.25,
                                 downReg = 0.25,
                                 absMinThreshold = 0.1,
                                 qValueCutOff = 0.05,
                                 verbose = TRUE)

7.0 Network Anlaysis

## Network Analysis
netPhorceData <- networkAnalysis(netPhorceData = netPhorceData,
                               requestPlotData = TRUE)

8.0 Session Info

sessionInfo()

ksong4/NetPhorce documentation built on March 24, 2023, 12:51 p.m.