Calculates the proteome coverage for each samples and for all samples combined. In other words t he fraction of detected proteins to all proteins in the proteome is calculated.

qc_proteome_coverage(
  data,
  sample,
  protein_id,
  organism_id,
  plot = TRUE,
  interactive = FALSE
)

Arguments

data

a data frame that contains at least sample names and protein ID's.

sample

a character column in the data data frame that contains the sample name.

protein_id

a character or numeric column in the data data frame that contains protein identifiers such as UniProt accessions.

organism_id

a numeric value that specifies a NCBI taxonomy identifier (TaxId) of the organism used. Human: 9606, S. cerevisiae: 559292, E. coli: 83333.

plot

a logical value that specifies whether the result should be plotted.

interactive

a logical value that indicates whether the plot should be interactive (default is FALSE).

Value

A bar plot showing the percentage of of the proteome detected and undetected in total and for each sample. If plot = FALSE a data frame containing the numbers is returned.

Examples

# \donttest{ # Create example data proteome <- data.frame(id = 1:4518) data <- data.frame( sample = c(rep("A", 101), rep("B", 1000), rep("C", 1000)), protein_id = c(proteome$id[1:100], proteome$id[1:1000], proteome$id[1000:2000]) ) # Calculate proteome coverage qc_proteome_coverage( data = data, sample = sample, protein_id = protein_id, organism_id = 83333, plot = FALSE )
#> # A tibble: 8 × 3 #> sample type percentage #> <fct> <fct> <dbl> #> 1 A proteins_detected 2.21 #> 2 A proteins_undetected 97.8 #> 3 B proteins_detected 22.1 #> 4 B proteins_undetected 77.9 #> 5 C proteins_detected 22.1 #> 6 C proteins_undetected 77.9 #> 7 Total proteins_detected 44.3 #> 8 Total proteins_undetected 55.7
# Plot proteome coverage qc_proteome_coverage( data = data, sample = sample, protein_id = protein_id, organism_id = 83333, plot = TRUE )
# }