estimate_incorporation: Estimate SILAC (2-plex) incorporation rate from PD output

In CambridgeCentreForProteomics/camprotR: Processing, analysing and visualising CCP proteomics data

Estimate SILAC (2-plex) incorporation rate from PD output

Description

SILAC (2-plex) incorporation can be estimated using the PSM and peptide groups PD outputs, and summarised at the peptide or protein level.

This function takes the PSM.txt and PeptideGroups.txt files as inputs and outputs 3 plots and a .tsv file into the designated output directory.

Usage

estimate_incorporation(
  psm_input,
  peptide_input,
  crap_fasta,
  master_protein_col = "Master.Protein.Accessions",
  protein_col = "Protein.Accessions",
  sequence_col = "Sequence",
  modifications_col = "Modifications",
  abundance_col_L = "^Abundances.Grouped.(F\\d*.)?Light$",
  abundance_col_H = "^Abundances.Grouped.(F\\d*.)?Heavy$",
  mix = 0,
  outdir = NULL
)

Arguments

psm_input	string or data.frame. File path to PSM-level PD output or the PSM-level PD output data.frame created using read.delim.
peptide_input	string or data.frame. File path to peptide-level PD output or the peptide-level PD output data.frame created using read.delim.
crap_fasta	string. File path to cRAP fasta used for PD search
master_protein_col	string. Name of column containing master protein accessions.
protein_col	string. Name of column containing all protein accessions.
sequence_col	string. Name of column containing peptide sequences.
modifications_col	string. Name of column containing peptide modifications.
abundance_col_L	string. Name of column containing light peptide intensity data, or a regex matching the names of multiple abundance columns.
abundance_col_H	string. Name of column containing heavy peptide intensity data, or a regex matching the names of multiple abundance columns.
mix	numeric. If Light material has been spiked in, what is the abundance relative to the Heavy material? Default is mix = 0 e.g. no Light spike in. If they are equal, mix = 1.
outdir	NULL or string. If not NULL, file path for directory to save the plots and summary table.

Details

Peptide sequencing/mass shift identification In SILAC, the peptide identity of ions can be established through MS2 fragmentation ('peptide sequencing') or by mass shift (within tolerance limits) relative to a sequenced peptide.

For 2-plex SILAC experiments, ideally, the correlation between Heavy and Light peptide intensities is the same regardless of whether Light or Heavy peptides are identified by mass shift or sequencing. If e.g Light peptide intensities are not well correlated when they are identified by mass shift, this may indicate that the mass shift identifications are erroneously picking up ghost peptides', which will make incorporation estimation difficult.

Mixing Heavy and Light material for incorporation rate testing To get around the issue of 'ghost peptides', one can spike in Light material (at cell or protein extract-level) to the Heavy material being analysed.

Value

By default returns a list with 3 ggplots (HL correlation, peptide-level incorporation, protein-level incorporation) and 1 summary table. If outdir is not NULL then the plots and table will be saved into outdir.

Examples

## Not run: 
# input as file paths
estimate_incorporation(
  psm_input = "data-raw/Molm_13_P4_PSMs.txt",
  peptide_input = "data-raw/Molm_13_P4_PeptideGroups.txt",
  crap_fasta = "inst/extdata/cRAP_20190401.fasta.gz",
  mix = 1,
  outdir = "Molm_13_incorporation/"
)

# input as data.frames
estimate_incorporation(
  psm_input = read.delim("data-raw/Molm_13_P4_PSMs.txt"),
  peptide_input = read.delim("data-raw/Molm_13_P4_PeptideGroups.txt"),
  crap_fasta = "inst/extdata/cRAP_20190401.fasta.gz",
  mix = 1,
  outdir = "Molm_13_incorporation/"
)

## End(Not run)

CambridgeCentreForProteomics/camprotR documentation built on Jan. 27, 2023, 8:36 p.m.