| Title: | 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, Mehdi Mirzaie, Marc Baumann, Amir Ata Saei, Mohieddin Jafari (2022) <bioRxiv:10.1101/2022.11.09.515610>. |
| Authors: | Mohieddin Jafari [aut], Payman Nickchi [aut, cre] |
| Maintainer: | Payman Nickchi <[email protected]> |
| License: | GPL (>= 3) |
| Version: | 0.1.0 |
| Built: | 2024-11-15 06:55:52 UTC |
| Source: | CRAN |
A dataset with randomly selected proteins from UniProt.
exmplData1exmplData1
A list with 2 elements:
97 randomly selected Homo sapiens (Human) proteins randomly selected from UniProt.
45 randomly selected Homo sapiens (Human) proteins randomly selected from UniProt.
...
Proteins of rat hippocampus proteome.
exmplData2exmplData2
A dataframe with 209 rows and 2 columns.
UniProt accession code of proteins
Check with MJ
...
getTaxonomyName get a character vector of proteins with their UniProt accession code and returns
the exact taxonomy code.
getTaxonomyName(x)getTaxonomyName(x)
x |
A character vector with each entry presenting a protein UniProt accession code. |
The exact taxonomy name
getTaxonomyName(x = exmplData1$pl1)getTaxonomyName(x = exmplData1$pl1)
Ontology database for post-translational modification terms. For more details, see the reference.
data(mod_ont)data(mod_ont)
A data frame with 2102 rows and 3 variables
id
name
def
https://raw.githubusercontent.com/HUPO-PSI/psi-mod-CV/master/PSI-MOD.obo
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.
plotEnrichment(x, y = NULL, sig.level = 0.05, number.rep = NULL)plotEnrichment(x, y = NULL, sig.level = 0.05, number.rep = NULL)
x |
A data frame that contains singular enrichment results generated by |
y |
Default value is NULL. If provided by a singular enrichment results, the matching results of x and y are plotted. |
sig.level |
The significance level to select post-translational modification (based on their
corrected p-value). Note that |
number.rep |
Only plot PTM terms that occurred more than a specific number of times in UniProt database. This number is set by number.rep parameter. The default value is NULL. |
Plot.
## 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 = 100)## 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 = 100)
plotPSEA can be used to plot the results of protein set enrichment analysis (psea) for a set of proteins obtained from an experiment.
plotPSEA(x, y = NULL, sig.level = 0.05, number.rep = NULL)plotPSEA(x, y = NULL, sig.level = 0.05, number.rep = NULL)
x |
A data frame returned by |
y |
Default value is NULL. If provided by a protein set enrichment results, the matching results of x and y are plotted. |
sig.level |
The significance level applied on adjusted p-value by permutation to filter pathways for plotting. The default value is 0.05 |
number.rep |
Only plot PTM terms that occurred more than a specific number of times in UniProt. This number is set by number.rep parameter. The default value is NULL. |
Plot
# 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)# 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)
This function takes results generated by runPSEA. It plots running enrichment score of
ranked protein for each PTM.
plotRunningScore( x, nplot = length(x$psea.result), type = "l", lty = 1, lwd = 3, cex = 1.2, cex.axis = 1.2, cex.lab = 1.1, col = "blue" )plotRunningScore( x, nplot = length(x$psea.result), type = "l", lty = 1, lwd = 3, cex = 1.2, cex.axis = 1.2, cex.lab = 1.1, col = "blue" )
x |
A list of 6 generated by runPSEA function. |
nplot |
An integer that defines the number of running score plots to show. Default value is the number of enriched PTMs in x. |
type |
Type of line used in the plot. |
lty |
A list of 6 generated by runPSEA function. |
lwd |
line width |
cex |
Specify the size of the title text |
cex.axis |
Specify the size of the tick label |
cex.lab |
Specify the size of the axis label text |
col |
Color of running enrichment score line |
Plot
# 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)# 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)
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.
psea2mass(x, sig.level = 0.05, number.rep = NULL)psea2mass(x, sig.level = 0.05, number.rep = NULL)
x |
A list of psea results generated by |
sig.level |
The significance level to filter PTMs (applies on adjusted p-value). Default value is 0.05 |
number.rep |
Only consider PTM terms that occurred more than a specific number of times in UniProt. This number is set by number.rep parameter. The default value is NULL. |
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
# 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)# 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)
This dataframe lists the posttranslational modifications used in the UniProt knowledgebase (Swiss-Prot and TrEMBL). The columns in this dataframe are as follows:
data(ptmlist)data(ptmlist)
A data frame with 686 rows and 5 variables
ID Identifier (FT description)
AC Accession (PTM-xxxx)
KW Keyword
FT Feature key
DR Cross-reference to external databases
https://ftp.uniprot.org/pub/databases/uniprot/knowledgebase/complete/docs/ptmlist.txt
This function takes proteins with their UniProt accession code, runs singular enrichment (SEA) analysis, and returns enrichment results.
runEnrichment(protein, os.name, p.adj.method = "BH")runEnrichment(protein, os.name, p.adj.method = "BH")
protein |
A character vector with protein UniProt accession codes. |
os.name |
A character vector of length one with exact taxonomy name of species. If you do not know the
the exact taxonomy name of species you are working with, please read |
p.adj.method |
The adjustment method to correct for multiple testing. The default value is 'BH'.
Run/see |
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.
enrich1 <- runEnrichment(protein = exmplData1$pl1, os.name = 'Homo sapiens (Human)')enrich1 <- runEnrichment(protein = exmplData1$pl1, os.name = 'Homo sapiens (Human)')
This is the main function to run protein set enrichment analysis for a list of proteins and their score.
runPSEA( protein, os.name, pexponent = 1, nperm = 1000, p.adj.method = "fdr", sig.level = 0.05, minSize = 1 )runPSEA( protein, os.name, pexponent = 1, nperm = 1000, p.adj.method = "fdr", sig.level = 0.05, minSize = 1 )
protein |
A dataframe with two columns. Frist column should be protein accession code, second column is the score. |
os.name |
A character vector of length one with exact taxonomy name of species. If you do not know the
the exact taxonomy name of species you are working with, please read |
pexponent |
Enrichment weighting exponent, p. For values of p < 1, one can detect incoherent patterns in a set of protein. If one expects a small number of proteins to be coherent in a large set, then p > 1 is a good choice. |
nperm |
Number of permutation to estimate false discovery rate (FDR). Default value is 1000. |
p.adj.method |
The adjustment method to correct pvalues for multiple testing in enrichment. Run p.adjust.methods() to get a list of possible methods. |
sig.level |
The significance level to filter PTM (applies on adjusted p-value) |
minSize |
PTMs with the number of proteins below this threshold are excluded. |
Returns a list of 6: 1: A dataframe with protein set enrichment analysis (PSEA) results. Every row corresponds to a post-translational modification (PTM) pathway.
PTM: PTM keyword
pval: p-value for singular enrichment analysis
pvaladj: adjusted p-value
FreqinUniProt: The frequency of PTM in UniProt
FreqinList: 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)
size: Number of proteins with the PTM
Enrichment: Whether the proteins in the pathway have been enriched in the list.
AC: Uniprot accession code (AC) of proteins with each PTM.
leadingEdge:
# 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)# 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)
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.
sea2mass(x, sig.level = 0.05, number.rep = NULL)sea2mass(x, sig.level = 0.05, number.rep = NULL)
x |
A dataframe of single enrichment analysis results generated by |
sig.level |
The significance level to filter pathways (applies on adjusted p-value). Default value is 0.05. |
number.rep |
Only consider PTM terms that occurred more than a specific number of times in UniProt. This number is set by number.rep parameter. The default value is NULL. |
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
enrich1 <- runEnrichment(protein = exmplData1$pl1, os.name = 'Homo sapiens (Human)') MS <- sea2mass(x = enrich1, sig.level = 0.05)enrich1 <- runEnrichment(protein = exmplData1$pl1, os.name = 'Homo sapiens (Human)') MS <- sea2mass(x = enrich1, sig.level = 0.05)