Description Usage Arguments Details Methods (by generic) Slots Examples
Details about Proteins class.
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object |
Proteins-class object |
seed |
an integer for |
Class holding the information about the proteins and peptides
show
: Show method for a Proteins object
simulate
: Simulates the number of peptides per protein
(if not provided) and ionization efficiencies of each peptide.
nProt
number of proteins
fdrPeptide
FDR of peptide identifications
fdrMatching
FDR of peptide to spectrum or LC-MS feature matching
propChanging
proportion of proteins that are changed between the different phenotype groups. At this point it is independent of phenotype groups. It shoud, however, depend on phenotype.
changingProtIdx
index indicating which proteins are changing
nPep
number of peptides
lambda
parameter of Poisson distribution controlling the number of peptides per protein during the simulation
meanIoinizationIntensity
a numeric value of mean peptide intensity
noise
measurement noise. So far one value for all. May be in the future convert to signal/noise ratio.
pepCounts
integer vector with number of peptides per each protein
protNames
character vector with generated protein names
pepNames
character vector with generacted peptide names
ionizationEff
numeric vector with simulated ionization efficiencies for the peptides
missThreshAbsolute
soft threshold in absolute intensity. It has precedence over missThreshQuantile.
missThreshQuantile
quantile to determine soft threshold value.
missThreshSharpness
parameter controlling the sharpness of the thresholding step function. The suggested interval for the sharpness values is [2,100]. At 2 it approximates linear (not necessarily the best setting). At 100 it is almost a step-function. The suggested values are >5.
features
data.frame containing peptide and protein names
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