knitr::opts_chunk$set(echo = TRUE)
#1. MaxQuant Search
#All raw files are processed together in a single run by MaxQuant v1.6.15.0 2 with default parameters except the following
#Raw data pane
#Load all raw data files of a single run.
#Select a sample file(s) and edit Set experiment to assign a unique ID. If you don´t assign a unique ID to each biological sample, MaxQuant will put them together in the output.
#Select a sample file and edit Set fractions to assign fraction value. If you don’t have a fractionation, set 1.
#Number of processors: 4 (depends on your computer)
#Group-specific parameters pane
#Type: Standard and Multiplicity: 1
#Modifications:
#a. Variable modifications: Oxidation(M); Acetyl (Protein N-term); Deamidation (NQ)
#b. Fixed modifications: Carbamidomethyl (C)
#Digestion: trypsin
#Instrument: Orbitrap
#Label-free quantification: LFQ (LFQ min. ratio count: 2)
#Global parameters pane
#Sequences:
#a. Add D:\Proteomics\HUMAN.fasta (download it from UNIPROT)
#b. Identifier rule: Uniprot identifier
#c. Min. peptide length: 6
#d. Max. peptide mass [Da]: 6000
#Protein quantification:
#a. Label min. ratio count: 1
#b. Peptides for quantification: Unique+razor
#c. Modifications used in protein quantification: Oxidation(M); Acetyl (Protein N-term); Deamidation (NQ)
#d. Discard unmodified counterpart peptides: FALSE
#Tables
#a. Write msScans tabls: TRUE
#MS/MS analyzer
#a. FTMS MS/MS match tolerance: 0.05 Da
#b. ITMS MS/MS match tolerance: 0.6 Da
#Identification:
#a. Match between runs: TRUE (optional)
#b. Find dependent peptides: FALSE
#c. Razor protein FDR: TRUE
#Label free quantification
#a. iBAQ: TRUE
#b. Separate LFQ in parameter groups: TRUE
#Folder locations
#a. Combine folder location: D:\results (optional)
#Match between runs: Peptides, which are present in several samples, but not identified via MS/MS in all of them, can still be identified via matching between runs. Setting TRUE will boosts number of identifications.
#Database searches are performed using the Andromeda search engine (a peptide search engine based on probabilistic scoring) with the UniProt-SwissProt human canonical database as a reference and a contaminants database of common laboratory contaminants. MaxQuant reports summed intensity for each protein, as well as it`s iBAQ and LFQ values.
#Proteins that share all identified peptides are combined into a single protein group. Peptides that match multiple protein groups (“razor” peptides) are assigned to the protein group with the most unique peptides. MaxQuant employs the MaxLFQ algorithm for label-free quantitation (LFQ). Quantification will be performed using razor and unique peptides, including those modified by acetylation (protein N-terminal), oxidation (Met) and deamidation (NQ).
#Quality Control of MaxQuant
#library("devtools")
#install_github("cbielow/PTXQC", build_vignettes=TRUE, dependencies=TRUE)
#set path for txt folder obtained from MaxQuant , you can get this folder inside combined folder (usually it generated wheen MaxQuant done)
library(PTXQC)
PTXQC::createReport("/Users/usri/Desktop/txt/")
#Open final report file report_v1.0.5_combined.pdf