R/chmi.03_phen.argument_aims.R

In mvazquezs/chmitools: Package to manage & obtain results of the CHMI Study

#------------------------------
# chmi.03_phen.argument_aims.R
#------------------------------


### argument to update 'data_type', 'aim_ab_data'---------------------------------------------------

chmi.03_phen.argument_aims <- function(dat, data_type, aim_data)
{	
### argument 'aim_data'
	if (data_type == 'ab_data' & aim_data == 'aim_1') {
	# aim_1
		dat <- chmi.phen.argument_ab_aim1(dat)

	} else if (data_type == 'ab_data' & aim_data == 'aim_2') {
	# aim_2
		dat <- chmi.phen.argument_ab_aim2(dat)

 	} else if (data_type == 'ab_data' & aim_data == 'aim_3') {
	# aim_3
		dat <- chmi.phen.argument_ab_aim3(dat)

	} else if (data_type == 'ab_data' & aim_data == 'aim_4') {
	# aim_4
		dat <- chmi.phen.argument_ab_aim4(dat)
				
	} else if (data_type == 'pbmc_data' & aim_data == 'aim_1') {
	# pbmc
		dat <- chmi.phen.argument_pbmc(dat)
	
	}

### return
	return(dat)
}



### update 'ab_chmi' by 'aim_1'---------------------------------------------------------------------

chmi.phen.argument_ab_aim1 <- function(dat)
{
### filter 'dat' & modify by 'aim1'
  dat <- dat %>%
    filter(status	!= 'naive' | dataset != 'T2')
		

### return
	return(dat)
}



### update 'ab_chmi' by 'aim_2'---------------------------------------------------------------------

chmi.phen.argument_ab_aim2 <- function(dat)
{
### filter 'dat' & modify by 'aim2'
	dat <- dat %>%
    filter(dataset == 'T2') %>%
    mutate(
    	vaccine = factor(
      	ifelse(immune_status == 'naive', 'placebo', immune_status),
      	levels = c('placebo', 'semi_immune', 'vaccinated_3200', 'vaccinated_12800', 'vaccinated_51200')))


### returns
 	return(dat)
}



### update 'ab_chmi' by 'aim_3'---------------------------------------------------------------------

chmi.phen.argument_ab_aim3 <- function(dat)
{
### filter 'dat' & modify by 'aim3'
	 dat <- dat %>%
    filter(dataset == 'L1') %>%
		mutate(
			gr_hbs = factor(
				ifelse(status == 'naive', 'naive', hb_status), levels = c('naive', 'AA', 'AS')),
      gr2_hbs = factor(
      	ifelse(gr_hbs == 'naive', 'naive', 'A_'), levels = c('naive', 'A_')))


### returns
 	return(dat)
}



### update 'ab_chmi' by 'aim_4'---------------------------------------------------------------------

chmi.phen.argument_ab_aim4 <- function(dat)
{
### filter 'dat' & modify by 'aim4'
  dat <- dat

### return
  return(dat)
}



### update 'pbmc_chmi'------------------------------------------------------------------------------

chmi.phen.argument_pbmc <- function(dat)
{
### filter 'dat' & modify by 'aim1'
  dat <- dat %>%
    mutate(
    	fact_marker = factor(
    		ifelse(str_detect(ct_marker, 'total'), 'no_marker',
   	  	ifelse(c(is.na(ct_value) & cell_population  %in% c('vbc_cd10', 'pb_gc', 'mzb')), 'na_marker',
				'marker')), 
				levels = c('no_marker', 'na_marker', 'marker')))


### return
	return(dat)
}