MakeCorrHuman: MakeCorrHuman

In CaronLab/MHCIatlas: Package to reproduce data analysis and further explore the data depicted by Kubiniok et al. 2021 in 'Global Analysis of the Mammalian MHC class I Immunopeptidome at the Organism-Wide Scale'.

Description

Compute correlations between tissue dependent intensities of proteins and the tissue dependent number of MHCI peptides

Usage

MakeCorrHuman(
  df_human,
  Donors = c("all"),
  deconvolute_byHLAGene = FALSE,
  pValue_Threshold = 0.05,
  rsq_Threshold = 0.4,
  runAnalCorrHuman = TRUE
)

Arguments

df_human	Input MHCI tissue draft from GetHumanMHCIdata
Donors	Vector with names of donors for which correlations are to be computed, Default: c("all")
deconvolute_byHLAGene	Logical, can be used to deconvolute by allele instead of by donor (not recommended), Default: FALSE
pValue_Threshold	Maximum pValue at which a correlation will be considered significant, Default: 0.05
rsq_Threshold	Min RSQ value at which protein is considered significantly correlation, both pValue and RSQ values have to be better or equal than threshold values, Default: 0.4
runAnalCorrHuman	Logical, directly runs the function AnalCorrHuman to retrieve significantly correlating proteins, Default: TRUE

Details

Running this function for all donors might take a while (around 15 minutes). Default pValue threshold is higher than for mouse since by default a pValue smaller the set value must be found in at least two donors/alleles Human protein expression data were retrieved from: Wang et al.; Mol Syst Biol. 2019 Feb 18;15(2); PMID: 30777892 https://www.embopress.org/doi/full/10.15252/msb.20188503

Value

List of dataframes with results

See Also

group_by,summarise,setops lm reexports

Examples

## Not run: 
corrs_h<-MakeCorrHuman(df_human,Donors=c('AUT01-DN11'))

## End(Not run)

CaronLab/MHCIatlas documentation built on March 10, 2021, 12:38 a.m.