Description Usage Arguments Details Value Author(s) Examples
phindPTMs() uses modified peptide information to localize the PTMs in the full-length protein and returns flanking sequences for subsequent analyses.
1 | phindPTMs(data_table, reference_table)
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data_table |
a data table containing your experimentally acquired proteomic data. See "phindPTMs_Input_Example.csv" for an example. |
reference_table |
a data table containing full protein sequence information for the peptides in the data_table. This input can be created from any proteome database using the parseDB() function. See "Human_Uniprot_Parsed_Example.txt" for an example. |
input files must contain the following 6 columns (exactly as below - see "phindPTMs_Input_Example.csv"):
1) Identifier - unique identifier for each modified peptide
2) Protein_ID - protein accession ID
3) Peptide_Seq - peptide sequence detected in experiment
4) Total_Sites - total number of modified sites on peptide
5) PTM_Loc - (potential) locations of PTM sites. Multiple PTMs should be separated by a semi-colon (eg. "S9;S18")
6) PTM_Score - confidence scores of PTM localizations. Multiple scores should be separated by a semi-colon (eg. "98.56;99.84")
a data table with 8 columns:
1) Identifier - see above
2) Protein ID - see above
3) Pep_Loc - location of the PTMs in the identified peptide
4) Prot_Loc - location of the PTMs the full-length protein
5) PTM_Score - see above
6) Flank_Seq - flanking sequences extracted from PTMs
7) Ambiguity - ambiguity of PTMs based on input data
8) Prot_Seq - full-length protein from which motifs were extracted
Jacob M. Wozniak (jakewozniak@gmail.com)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | # Locate example files
examples.path = system.file("extdata", package = "PTMphinder")
ptm_data.path = paste(examples.path, "/phindPTMs_Input_Example.csv", sep="")
parsed_ref.path = paste(examples.path, "/Human_Uniprot_Parsed_Example.txt", sep="")
# Read in proteomic data example (or your own data)
ptm_data <- read.csv(ptm_data.path, header=TRUE, row.names = NULL, stringsAsFactors = FALSE)
# Read in parsed Uniprot database example (or one you created with parseDB above)
parsed_ref <- read.table(parsed_ref.path, header=FALSE, row.names=NULL, sep="\t")
# Locate PTMs within full-length proteins and extract neighboring motifs
phindPTMs_Example <- phindPTMs(ptm_data, parsed_ref)
# Create file name for phindPTMs output
fileName3 <- paste(examples.path, "/PTMs_phound_", Sys.Date(), ".txt", sep="")
# Write phindPTMs output to new file (will be found in the PTMphinder/extdata/ directory within R.framework)
write.table(phindPTMs_Example, fileName3, row.names=FALSE, append = FALSE, sep = "\t")
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