runTPP2D: Run complete TPP2D analysis

Description Usage Arguments Value Examples

View source: R/full_analysis.R

Description

Run complete TPP2D analysis

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
runTPP2D(
  df = NULL,
  configTable = NULL,
  data = NULL,
  idVar = "protein_id",
  intensityStr = "signal_sum_",
  fcStr = "rel_fc_",
  nonZeroCols = "qusm",
  geneNameVar = "gene_name",
  addCol = NULL,
  qualColName = "qupm",
  naStrs = c("NA", "n/d", "NaN"),
  concFactor = 1e+06,
  medianNormalizeFC = TRUE,
  filterContaminants = TRUE,
  recomputeSignalRatios = FALSE,
  minObs = 20,
  independentFiltering = FALSE,
  fcThres = 1.5,
  optim_fun_h0 = .min_RSS_h0,
  optim_fun_h1 = .min_RSS_h1_slope_pEC50,
  optim_fun_h1_2 = NULL,
  gr_fun_h0 = NULL,
  gr_fun_h1 = NULL,
  gr_fun_h1_2 = NULL,
  slopEC50 = TRUE,
  maxit = 750,
  BPPARAM = BiocParallel::SerialParam(progressbar = TRUE),
  B = 20,
  byMsExp = TRUE,
  alpha = 0.1
)

Arguments

df

tidy data_frame retrieved after import of a 2D-TPP dataset, potential filtering and addition of a column "nObs" containing the number of observations per protein

configTable

character string of a file path to a config table

data

possible list of datasets from different MS runs corresponding to a 2D-TPP dataset, circumvents loading datasets referencend in config table, default is NULL

idVar

character string indicating which data column provides the unique identifiers for each protein.

intensityStr

character string indicating which columns contain raw intensities measurements

fcStr

character string indicating which columns contain the actual fold change values. Those column names containing the suffix fcStr will be regarded as containing fold change values.

nonZeroCols

column like default qssm that should be imported and requested to be non-zero in analyzed data

geneNameVar

character string of the column name that describes the gene name of a given protein in the raw data files

addCol

character string indicating additional column to import

qualColName

character string indicating which column can be used for additional quality criteria when deciding between different non-unique protein identifiers.

naStrs

character vector indicating missing values in the data table. When reading data from file, this value will be passed on to the argument na.strings in function read.delim.

concFactor

numeric value that indicates how concentrations need to be adjusted to yield total unit e.g. default mmol - 1e6

medianNormalizeFC

perform median normalization (default: TRUE).

filterContaminants

logical variable indicating whether data should be filtered to exclude contaminants (default: TRUE).

recomputeSignalRatios

logical variable indicaiting whether signals should be recomputed from relative fold changes, recommended if Isobarquant was used for protein quantification

minObs

number of minimal observations per protein to include it in the analysis

independentFiltering

logical variable indicating whether independent filtering should be performed based on minimal fold changes per protein profile

fcThres

numeric value of minimal fold change (or inverse fold change) a protein has to show to be kept upon independent filtering

optim_fun_h0

optimization function that should be used for fitting the H0 model

optim_fun_h1

optimization function that should be used for fitting the H1 model

optim_fun_h1_2

optional additional optimization function that will be run with paramters retrieved from optim_fun_h1 and should be used for fitting the H1 model with the trimmed sum model, default is NULL

gr_fun_h0

optional gradient function for optim_fun_h0, default is NULL

gr_fun_h1

optional gradient function for optim_fun_h1, default is NULL

gr_fun_h1_2

optional gradient function for optim_fun_h1_2, default is NULL

slopEC50

logical flag indicating whether the h1 model is fitted with a linear model describing the shift od the pEC50 over temperatures

maxit

maximal number of iterations the optimization should be given, default is set to 500

BPPARAM

= BiocParallel::SerialParam(progressbar = TRUE),

B

numeric value indicating number of rounds of bootstraps that should be performed to estimate the null distribution

byMsExp

logical indicating whether bootstrapping should be performed within MS experiments

alpha

FDR level that should be controlled

Value

a tpp2dExperiment object

Examples

1
2
3
4
data("simulated_cell_extract_df")
runTPP2D(df = simulated_cell_extract_df %>% 
   filter(representative %in% 1:3),
   B = 1)

TPP2D documentation built on Nov. 8, 2020, 4:54 p.m.