PEIMAN2: Post-Translational Modification Enrichment, Integration, and Matching Analysis

Description

Functions and mined database from 'UniProt' focusing on post-translational modifications to do single enrichment analysis (SEA) and protein set enrichment analysis (PSEA). Payman Nickchi, Uladzislau Vadadokhau, Mehdi Mirzaie, Marc Baumann, Amir Ata Saei, Mohieddin Jafari (2025) doi:10.1002/pmic.202400238.

Author(s)

Maintainer: Payman Nickchi payman.nickchi@gmail.com

Authors:

• Mohieddin Jafari mohieddin.jafari@helsinki.fi

Example dataset1

Description

A dataset with randomly selected proteins from UniProt.

Usage

exmplData1

Format

A list with 2 elements:

pl1

97 randomly selected Homo sapiens (Human) proteins randomly selected from UniProt.

pl2

45 randomly selected Homo sapiens (Human) proteins randomly selected from UniProt.

...

Source

https://www.uniprot.org/

Example dataset 2

Description

A test dataset of proteins identified from rat hippocampus proteome using label-free thermal proteome profiling. The score for each protein corresponds to the SEQUEST HT engine score of one arbitrary peptide-spectrum match (PSM) associated with that protein. This dataset is provided to demonstrate how a ranked list of proteins can be used within the PEIMAN2 package.

Usage

exmplData2

Format

A data frame with 209 rows and 2 columns:

UniProtAC

UniProt accession code of proteins

Score

SEQUEST HT score of one associated PSM (used for demonstration purposes)

...

Details

Proteins of rat hippocampus proteome.

Source

https://pubmed.ncbi.nlm.nih.gov/33632781/

Return the exact taxonomy name for list of protein

Description

getTaxonomyName get a character vector of proteins with their UniProt accession code and returns the exact taxonomy code.

Usage

getTaxonomyName(x)

Arguments

Value

The exact taxonomy name

Examples

getTaxonomyName(x = exmplData1$pl1)

Database of protein modifications

Description

Ontology database for post-translational modification terms. For more details, see the reference.

Usage

data(mod_ont)

Format

A data frame with 2102 rows and 3 variables

Details

• id

• name

• def

Source

https://raw.githubusercontent.com/HUPO-PSI/psi-mod-CV/master/PSI-MOD.obo

Plot and match singular enrichment results

Description

This function can be used to plot results of singular enrichment analysis for one set of protein. It can also be used to integrate and match the results of two separate singular enrichment analysis and plot the common PTMs. For more details please see examples.

Usage

plotEnrichment(x, y = NULL, sig.level = 0.05, number.rep = NULL, plotit = TRUE)

Arguments

Value

Plot.

Examples

## Enrichment analysis for the first protein list
enrich1 <- runEnrichment(protein = exmplData1$pl1, os.name = 'Homo sapiens (Human)')
## Plot results for first protein list
plotEnrichment(x = enrich1)

## Enrichment analysis for the second protein list
enrich2 <- runEnrichment(protein = exmplData1$pl2, os.name = 'Homo sapiens (Human)')
## Plot results for second protein list
plotEnrichment(x = enrich2)

## Integrate and match the results of two separate singular enrichment analysis
plotEnrichment(x = enrich1, y = enrich2)
plotEnrichment(x = enrich1, y = enrich2, number.rep = 5)

Plot the results of protein set enrichment analysis (PSEA)

Description

plotPSEA can be used to plot the results of protein set enrichment analysis (psea) for a set of proteins obtained from an experiment.

Usage

plotPSEA(x, y = NULL, sig.level = 0.05, number.rep = NULL)

Arguments

Value

Plot

Examples

# We recommend at least nperm = 1000.
# The number of permutations was reduced to 10
# to accommodate CRAN policy on examples (run time <= 5 seconds).
psea_res <- runPSEA(protein = exmplData2, os.name = 'Rattus norvegicus (Rat)', nperm = 10)
plotPSEA(psea_res, sig.level = 0.05)

Plot running score plot for the results of psea

Description

This function takes results generated by runPSEA. It plots running enrichment score of ranked protein for each PTM.

Usage

plotRunningScore(
  x,
  nplot = length(x$psea.result),
  type = "l",
  lty = 1,
  lwd = 3,
  cex = 1.2,
  cex.axis = 1.2,
  cex.lab = 1.1,
  col = "blue"
)

Arguments

Value

Plot

Examples

# We recommend at least nperm = 1000.
# The number of permutations was reduced to 10
# to accommodate CRAN policy on examples (run time <= 5 seconds).
psea_res <- runPSEA(protein = exmplData2, os.name = 'Rattus norvegicus (Rat)', nperm = 10)
plotRunningScore(x = psea_res)

Translate PSEA results for Mass Spectrometry searching tools

Description

This function translates protein set enrihment analysis results and extracts the required information for mass spectometry searching tools. The subset of protein modifications is from https://raw.githubusercontent.com/HUPO-PSI/psi-mod-CV/master/PSI-MOD.obo.

Usage

psea2mass(x, sig.level = 0.05, number.rep = NULL)

Arguments

Value

A database of subset of protein modifications:

• id: a unique identification for each subset of protein modifications, PSI-MOD.

• name: the name of modification.

• def: definition of PSI-MOD definition

Examples

# We recommend at least nperm = 1000.
# The number of permutations was reduced to 10
# to accommodate CRAN policy on examples (run time <= 5 seconds).
psea_res <- runPSEA(protein = exmplData2, os.name = 'Rattus norvegicus (Rat)', nperm = 10)
MS <- psea2mass(x = psea_res, sig.level = 0.05)

Controlled vocabulary for post-translational modifications (PTM) terms

Description

This dataframe lists the posttranslational modifications used in the UniProt knowledgebase (Swiss-Prot and TrEMBL). The columns in this dataframe are as follows:

Usage

data(ptmlist)

Format

A data frame with 686 rows and 5 variables

Details

• ID Identifier (FT description)

• AC Accession (PTM-xxxx)

• KW Keyword

• FT Feature key

• DR Cross-reference to external databases

Source

https://ftp.uniprot.org/pub/databases/uniprot/knowledgebase/complete/docs/ptmlist.txt

Run singular enrichment analysis (SEA) for a given list of protein

Description

This function takes proteins with their UniProt accession code, runs singular enrichment (SEA) analysis, and returns enrichment results.

Usage

runEnrichment(protein, os.name, blist = NULL, p.adj.method = "BH")

Arguments

Value

The result is a dataframe with the following columns:

• PTM: Post-translational modification (PTM) keyword

• FreqinUniprot: The total number of proteins in UniProt with this PTM.

• FreqinList: The total number of proteins in the given list with this PTM.

• Sample: Number of proteins in the given list.

• Population: Total number of proteins in the current version of PEIMAN database with this PTM.

• pvalue: The p-value obtained from hypergeometric test (enrichment analysis).

• corrected pvalue: Adjusted p-value to correct for multiple testing.

• AC: Uniprot accession code (AC) of proteins with each PTM.

Examples

enrich1 <- runEnrichment(protein = exmplData1$pl1, os.name = 'Homo sapiens (Human)')

Run Protein Set Enrichment Analysis (PSEA)

Description

This is the main function to run protein set enrichment analysis for a list of proteins and their score.

Usage

runPSEA(
  protein,
  os.name,
  blist = NULL,
  pexponent = 1,
  nperm = 1000,
  p.adj.method = "fdr",
  sig.level = 0.05,
  minSize = 1
)

Arguments

Value

Returns a list of 6: 1: A dataframe with protein set enrichment analysis (PSEA) results. Every row corresponds to a post-translational modification (PTM) keyword.

• PTM: PTM keyword

• pval: p-value obtained from singular enrichment analysis (SEA).

• pvaladj: adjusted p-value. This column is the adjusted pvalues with p.adj.method methods calculated in SEA method.

• FreqinPopulation: The frequency of PTM in UniProt.

• FreqinSample: The frequency of PTM in the given list.

• ES: enrichment score.

• NES: enrichmnt score normalized to mean enrichment of random samples of the same size.

• nMoreExtreme: number of times the permuted sample resulted in a profile with a larger ES value than abs(ES) of the sample.

• size: Number of proteins in the list having this specific PTM.

• Enrichment: Indicates if the proteins with the specific protein have been enriched in the list or not. NES positive is considered as enriched.

• AC: Uniprot accession code (AC) of proteins with the specific PTM.

• leadingEdge: the leading edge proteins are the proteins that show up in the ranked list at or before the point where the enrichment score (ES) reaches its maximum deviation from zero.

Examples

# We recommend at least nperm = 1000.
# The number of permutations was reduced to 10
# to accommodate CRAN policy on examples (run time <= 5 seconds).
psea_res <- runPSEA(protein = exmplData2, os.name = 'Rattus norvegicus (Rat)', nperm = 10)

Translate SEA results for Mass Spectrometry searching tools

Description

This function translates singular enrichment analysis results and extracts the required information for mass spectometry searching tools. The subset of protein modifications is from https://raw.githubusercontent.com/HUPO-PSI/psi-mod-CV/master/PSI-MOD.obo.

Usage

sea2mass(x, sig.level = 0.05, number.rep = NULL)

Arguments

Value

A database of subset of protein modifications:

• id: a unique identification for each subset of protein modifications, PSI-MOD.

• name: the name of modification.

• def: definition of PSI-MOD definition

Examples

enrich1 <- runEnrichment(protein = exmplData1$pl1, os.name = 'Homo sapiens (Human)')
MS      <- sea2mass(x = enrich1, sig.level = 0.05)