Tools for LiP peptide and protein significance analysis. Provides functions for summarization, estimation of LiP peptide abundance, and detection of changes across conditions. Utilizes functionality across the MSstats family of packages.
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library(MSstatsLiP)
# Calculate proteolytic resistance ratios and perform differential analysis
Accessibility <- calculateProteolyticResistance(
MSstatsLiP_Summarized,
fasta_file,
differential_analysis = TRUE
)
# Plot proteolytic resistance results as a barcode along the protein sequence
ResistanceBarcodePlotLiP(
Accessibility,
fasta_file,
which.prot = "P16622",
which.condition = "F1",
differential_analysis = TRUE,
which.comp = "F1 vs F2",
address = FALSE
)
Input: Summarized LiP-MS and TrP-MS datasets (MSstatsLiP_Summarized) and a FASTA file (fasta_file).
Output: Proteolytic resistance ratios and sequence-aligned barcode plots.
library(MSstatsLiP)
# Convert raw Spectronaut data to MSstatsLiP format
msstats_data <- SpectronauttoMSstatsLiPFormat(
raw_lip,
fasta_file,
raw_prot
)
# Summarize the preprocessed data
MSstatsLiP_Summarized <- dataSummarizationLiP(
msstats_data,
normalization.LiP = "equalizeMedians"
)
# Perform group comparison modeling
MSstatsLiP_model <- groupComparisonLiP(MSstatsLiP_Summarized)
Input: Raw Spectronaut LiP and TrP datasets, and a FASTA file. Output: Preprocessed, summarized, and modeled LiP-MS and TrP-MS datasets.
SpectronauttoMSstatsLiPFormat.calculateProteolyticResistance and groupComparisonLiP.ResistanceBarcodePlotLiP.MSstats directly.limma, edgeR, or DESeq2.PG.ProteinAccessions, PEP.GroupingKey, EG.Qvalue, and F.PeakArea.dataSummarizationLiP.calculateProteolyticResistance.ResistanceBarcodePlotLiP.ResistanceBarcodePlotLiP.ResistanceBarcodePlotLiP.calculateTrypticity.unique(msstats_data[["LiP"]]$Condition) %in% unique(msstats_data[["TrP"]]$Condition).rm() and gc() if needed.MSstats for standard proteomics without limited proteolysis.limma for general linear modeling of expression data.还没有评价。欢迎分享你的使用感受。
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