PSM2Pep: Interim peptide tables

In qzhang503/proteoQ: Processing and Informatic Analysis of Mass Spectrometrirc Data

Interim peptide tables

Description

PSM2Pep summarizes PSMs to

Usage

PSM2Pep(
  method_psm_pep = c("median", "mean", "weighted_mean", "top_3_mean", "lfq_max",
    "lfq_top_2_sum", "lfq_top_3_sum", "lfq_all"),
  lfq_ret_tol = 60L,
  rm_allna = FALSE,
  type_sd = c("log2_R", "N_log2_R", "Z_log2_R"),
  ...
)

Arguments

method_psm_pep	Character string; the method to summarize the log2FC and the intensity of PSMs by peptide entries. The log10-intensity of reporter ions at the PSMs levels will be the weight when summarizing log2FC with various "top_n" statistics or "weighted_mean". The choices of summary statistics for LFQ are depreciated at the users' levels.
lfq_ret_tol	The tolerance of retention time (in seconds) for the aggregation of LFQ data.
rm_allna	Logical; if TRUE, removes data rows that are exclusively NA across ratio columns of log2_R126 etc. The setting also applies to log2_R000 in LFQ.
type_sd	Character string; the type of log2Ratios for SD calculations. The value is one log2_R, N_log2_R or Z_log2_R.
...	filter_: Variable argument statements for the filtration of data rows. See also normPSM.

Details

In general, fields other than log2FC and intensity are summarized with median statistics. One exception is with pep_expect in Mascot or PEP in MaxQuant where geometric mean is applied.

Value

Tables under Peptide folder for each TMT experiment and LC/MS series: TMTset1_LCMSinj1_Peptide_N.txt etc.

See Also

Metadata
load_expts for metadata preparation and a reduced working example in data normalization

Data normalization
normPSM for extended examples in PSM data normalization
PSM2Pep for extended examples in PSM to peptide summarization
mergePep for extended examples in peptide data merging
standPep for extended examples in peptide data normalization
Pep2Prn for extended examples in peptide to protein summarization
standPrn for extended examples in protein data normalization.
purgePSM and purgePep for extended examples in data purging
pepHist and prnHist for extended examples in histogram visualization.
extract_raws and extract_psm_raws for extracting MS file names

Variable arguments of filter_...
contain_str, contain_chars_in, not_contain_str, not_contain_chars_in, start_with_str, end_with_str, start_with_chars_in and ends_with_chars_in for data subsetting by character strings

Missing values
pepImp and prnImp for missing value imputation

Informatics
pepSig and prnSig for significance tests
pepVol and prnVol for volcano plot visualization
prnGSPA for gene set enrichment analysis by protein significance pVals
gspaMap for mapping GSPA to volcano plot visualization
prnGSPAHM for heat map and network visualization of GSPA results
prnGSVA for gene set variance analysis
prnGSEA for data preparation for online GSEA.
pepMDS and prnMDS for MDS visualization
pepPCA and prnPCA for PCA visualization
pepLDA and prnLDA for LDA visualization
pepHM and prnHM for heat map visualization
pepCorr_logFC, prnCorr_logFC, pepCorr_logInt and prnCorr_logInt for correlation plots
anal_prnTrend and plot_prnTrend for trend analysis and visualization
anal_pepNMF, anal_prnNMF, plot_pepNMFCon, plot_prnNMFCon, plot_pepNMFCoef, plot_prnNMFCoef and plot_metaNMF for NMF analysis and visualization

Custom databases
Uni2Entrez for lookups between UniProt accessions and Entrez IDs
Ref2Entrez for lookups among RefSeq accessions, gene names and Entrez IDs
prepGO for gene ontology
prepMSig for molecular signatures
prepString and anal_prnString for STRING-DB

Column keys in PSM, peptide and protein outputs
system.file("extdata", "psm_keys.txt", package = "proteoQ")
system.file("extdata", "peptide_keys.txt", package = "proteoQ")
system.file("extdata", "protein_keys.txt", package = "proteoQ")

Examples

# ===================================
# PSMs to peptides
# ===================================

## !!!require the brief working example in `?load_expts`

# default median statistics
PSM2Pep()

# mean statistics
PSM2Pep(method_psm_pep = mean)  

## Not run: 
# cut-offs in precursor intensity
# (error if `pep_tot_int` are all NAs)
PSM2Pep(filter_ms1int = rlang::exprs(pep_tot_int >= 1E4)) 

# cut-offs in precursor intensity by percentiles
PSM2Pep(filter_ms1int = rlang::exprs(
  pep_tot_int >= quantile(pep_tot_int, probs = .05, na.rm = TRUE), 
  pep_tot_int <= quantile(pep_tot_int, probs = .99, na.rm = TRUE), 
))
## End(Not run)

qzhang503/proteoQ documentation built on Dec. 14, 2024, 12:27 p.m.