Import proteomics data from Mascot
import_proteomics_mascot(
file,
sheet = 1,
ann_lib = c("org.Hs.eg.db", "org.Mm.eg.db", "org.Rn.eg.db"),
curation_txt = NULL,
accession_from = NULL,
accession_to = NULL,
xref_df = NULL,
measurements = c("totalIntensity", "numSpectra"),
accession_colname = "accession",
delim = "[/]",
try_list = c("SYMBOL2EG", "ACCNUM2EG", "UNIPROT2EG", "ENSEMBLPROT2EG", "ALIAS2EG"),
verbose = FALSE,
...
)
character
path to a file containing proteomics data
integer
or character
name of worksheet when file
is an Excel xlsx
formatted file.
character
passed to genejam::freshenGenes3()
, see
documentation for alternate methods of passing one or more annotation
libraries.
data.frame
whose first column should match the
sample column headers found in the PD abundance columns, and
subsequent columns contain associated sample annotations.
If curation_txt
is not supplied, then values will be split into
columns by _
underscore or " "
whitespace characters.
character
vectors, that help manual
curation from one accession number to another, intended when an
accession number is not recognized by the Bioconductor annotation
library, and a newer accession would be recognized. No gene left
behind.
data.frame
that contains accession numbers in the
first column, and annotation columns in additional columns, specifically
using "SYMBOL", "ENTREZID", "GENENAME"
as replacements for
output from genejam::freshenGenes3()
.
logical
indicating whether to print verbose output.
additional arguments are passed to jamba::readOpenxlsx()
.
SummarizedExperiment
object
Other jam import functions:
coverage_matrix2nmat()
,
deepTools_matrix2nmat()
,
frequency_matrix2nmat()
,
import_lipotype_csv()
,
import_metabolomics_niehs()
,
import_nanostring_csv()
,
import_nanostring_rcc()
,
import_nanostring_rlf()
,
import_proteomics_PD()
,
import_salmon_quant()
,
process_metab_compounds_file()
# TODO: replace with smaller test data in the appropriate format
mascot_file <- file.path(path.expand("~/Projects/Hu/hu_msprot_turboid"),
"Lackford_all_090822.xlsx")
protein_df <- jamba::readOpenxlsx(mascot_file, sheet=1)[[1]];
se <- import_proteomics_mascot;