View source: R/estimate_incorporation.R
estimate_incorporation | R Documentation |
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.
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
)
psm_input |
|
peptide_input |
|
crap_fasta |
|
master_protein_col |
|
protein_col |
|
sequence_col |
|
modifications_col |
|
abundance_col_L |
|
abundance_col_H |
|
mix |
|
outdir |
|
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.
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
.
## 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)
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