script for calcuating various OR & output csv
This commit is contained in:
parent
a1cc7ee33d
commit
003b22ce3f
2 changed files with 117 additions and 305 deletions
412
scripts/af_or_calcs.R
Executable file → Normal file
412
scripts/af_or_calcs.R
Executable file → Normal file
|
|
@ -30,8 +30,8 @@ if(is.null(drug)|is.null(gene)) {
|
||||||
#options(scipen = 4)
|
#options(scipen = 4)
|
||||||
|
|
||||||
#%% variable assignment: input and output paths & filenames
|
#%% variable assignment: input and output paths & filenames
|
||||||
#drug = 'pyrazinamide'
|
drug = 'pyrazinamide'
|
||||||
#gene = 'pncA'
|
gene = 'pncA'
|
||||||
gene_match = paste0(gene,'_p.')
|
gene_match = paste0(gene,'_p.')
|
||||||
cat(gene_match)
|
cat(gene_match)
|
||||||
|
|
||||||
|
|
@ -165,51 +165,21 @@ gene_snps_unique = unique(gene_snps_or$mutation)
|
||||||
|
|
||||||
cat(paste0('Total no. of distinct comp snps to perform OR calcs: ', length(gene_snps_unique)))
|
cat(paste0('Total no. of distinct comp snps to perform OR calcs: ', length(gene_snps_unique)))
|
||||||
|
|
||||||
#=====================================
|
#===========================================================================================
|
||||||
#OR calcs using the following 4
|
#########################
|
||||||
#1) chisq.test
|
# custom chisq function:
|
||||||
#2) fisher
|
# To calculate OR
|
||||||
#3) modified chisq.test
|
#########################
|
||||||
#4) logistic
|
|
||||||
#5) adjusted logistic?
|
|
||||||
#6) kinship (separate script)
|
|
||||||
|
|
||||||
#======================================
|
|
||||||
# TEST FOR ONE
|
|
||||||
i = "pnca_p.ala134gly" # has a NA, should NOT exist
|
|
||||||
table(grepl(i,raw_data$all_muts_gene))
|
|
||||||
|
|
||||||
i = "pnca_p.trp68gly"
|
i = "pnca_p.trp68gly"
|
||||||
table(grepl(i,raw_data$all_muts_gene))
|
|
||||||
|
|
||||||
i = "pnca_p.his51asp"
|
|
||||||
table(grepl(i,raw_data$all_muts_gene))
|
|
||||||
|
|
||||||
# IV
|
|
||||||
mut = grepl(i,raw_data$all_muts_gene)
|
mut = grepl(i,raw_data$all_muts_gene)
|
||||||
|
mut = as.numeric(mut)
|
||||||
|
|
||||||
# DV
|
dst = raw_data[[drug]]
|
||||||
dst = raw_data[[drug]] #or raw_data[,drug]
|
|
||||||
|
|
||||||
table(mut, dst)
|
|
||||||
|
|
||||||
#===============================================
|
|
||||||
# calculating OR
|
|
||||||
|
|
||||||
#1) chisq : noy accurate for low counts
|
|
||||||
chisq.test(table(mut,dst))
|
|
||||||
chisq.test(table(mut,dst))$p.value
|
|
||||||
chisq.test(table(mut,dst))$statistic
|
|
||||||
|
|
||||||
t = chisq.test(table(mut,dst))$statistic; print(t)
|
|
||||||
names(t)
|
|
||||||
# remove suffix
|
|
||||||
#names(t2) = gsub(".X-squared", "", names(t))
|
|
||||||
|
|
||||||
#2) modified chisq OR: custom function
|
|
||||||
#x = as.numeric(mut)
|
#x = as.numeric(mut)
|
||||||
#y = dst
|
#y = dst
|
||||||
my_chisq_or = function(x,y){
|
|
||||||
|
mychisq_or = function(x,y){
|
||||||
tab = as.matrix(table(x,y))
|
tab = as.matrix(table(x,y))
|
||||||
a = tab[2,2]
|
a = tab[2,2]
|
||||||
if (a==0){ a<-0.5}
|
if (a==0){ a<-0.5}
|
||||||
|
|
@ -220,288 +190,130 @@ my_chisq_or = function(x,y){
|
||||||
d = tab[1,1]
|
d = tab[1,1]
|
||||||
if (d==0){ d<-0.5}
|
if (d==0){ d<-0.5}
|
||||||
(a/b)/(c/d)
|
(a/b)/(c/d)
|
||||||
|
|
||||||
}
|
}
|
||||||
my_chisq_or(mut, dst)
|
|
||||||
|
|
||||||
#3) fisher
|
or_mychisq = mychisq_or(dst, mut)
|
||||||
fisher.test(table(mut, dst))
|
print(paste0('mychisq OR:', or_mychisq ))
|
||||||
|
|
||||||
or_fisher = fisher.test(table(mut, dst))$estimate; print(or_fisher); cat(names(or_fisher))
|
|
||||||
pval_fisher = fisher.test(table(mut, dst))$p.value; print(pval_fisher) # the same one to be used for custom chisq_or
|
|
||||||
ci_lb_fisher = fisher.test(table(mut, dst))$conf.int[1]; print(ci_lb_fisher)
|
|
||||||
ci_ub_fisher = fisher.test(table(mut, dst))$conf.int[2]; print(ci_ub_fisher)
|
|
||||||
|
|
||||||
|
#=====================================
|
||||||
|
#OR calcs using the following 4
|
||||||
|
#1) chisq.test
|
||||||
|
#2) fisher
|
||||||
|
#3) modified chisq.test
|
||||||
#4) logistic
|
#4) logistic
|
||||||
summary(model<-glm(dst ~ mut
|
#5) adjusted logistic?
|
||||||
, family = binomial
|
#6) kinship (separate script)
|
||||||
#, control = glm.control(maxit = 1)
|
|
||||||
#, options(warn = 1)
|
|
||||||
))
|
|
||||||
or_logistic = exp(summary(model)$coefficients[2,1]); print(or_logistic)
|
|
||||||
pval_logistic = summary(model)$coefficients[2,4]; print(pval_logistic)
|
|
||||||
|
|
||||||
|
|
||||||
#5) logistic adjusted: sample id (# identical results as unadjusted)
|
|
||||||
#c = raw_data$id[grepl(i,raw_data$all_muts_gene)]
|
|
||||||
#sid = grepl(paste(c,collapse="|"), raw_data$id) # else warning that pattern length > 1
|
|
||||||
#table(sid)
|
|
||||||
#table(mut, dst, sid)
|
|
||||||
|
|
||||||
#summary(model2<-glm(dst ~ mut + sid
|
|
||||||
# , family = binomial
|
|
||||||
##, control = glm.control(maxit = 1)
|
|
||||||
##, options(warn = 1)
|
|
||||||
# ))
|
|
||||||
#or_logistic2 = exp(summary(model2)$coefficients[2,1]); print(or_logistic2)
|
|
||||||
#pval_logistic2 = summary(model2)$coefficients[2,4]; print(pval_logistic2)
|
|
||||||
|
|
||||||
|
#======================================
|
||||||
|
# TEST FOR a few muts: sapply and df
|
||||||
#===============================================
|
#===============================================
|
||||||
|
snps <- gene_snps_unique # reassign so you test with subset of muts
|
||||||
|
#snps <- gene_snps_unique[1:2]
|
||||||
|
cat(paste0('Running calculations for:', length(snps), ' nssnps\n'
|
||||||
|
, 'gene: ', gene
|
||||||
|
, '\ndrug: ', drug ))
|
||||||
|
|
||||||
######################
|
# DV: pyrazinamide 0 or 1
|
||||||
# AF and OR for all muts: sapply
|
dst = raw_data[[drug]]
|
||||||
######################
|
|
||||||
print(table(dst)); print(table(mut)) # must exist
|
|
||||||
#dst = raw_data[[drug]] #or raw_data[,drug]
|
|
||||||
|
|
||||||
# af
|
# initialise an empty df
|
||||||
afs = sapply(gene_snps_unique,function(m){
|
ors_df = data.frame()
|
||||||
mut = grepl(m,raw_data$all_muts_gene)
|
|
||||||
mean(mut)
|
|
||||||
})
|
|
||||||
|
|
||||||
#afs
|
x = sapply(snps,function(m){
|
||||||
head(afs)
|
|
||||||
|
|
||||||
#1) chi square: original
|
|
||||||
statistic_chi = sapply(gene_snps_unique,function(m){
|
|
||||||
mut = grepl(m,raw_data$all_muts_gene)
|
|
||||||
chisq.test(mut,dst)$statistic
|
|
||||||
|
|
||||||
})
|
|
||||||
|
|
||||||
# statistic_chi: has suffix added of '.X-squared'
|
|
||||||
stat_chi = statistic_chi
|
|
||||||
|
|
||||||
# remove suffix
|
|
||||||
names(stat_chi) = gsub(".X-squared", "", names(statistic_chi))
|
|
||||||
|
|
||||||
if (names(stat_chi)!= names(statistic_chi) && stat_chi == statistic_chi){
|
|
||||||
cat('Sanity check passed: suffix removed correctly\n\n'
|
|
||||||
, 'names with suffix:', head(names(statistic_chi)), '\n\n'
|
|
||||||
, 'names without suffix:', head(names(stat_chi)), '\n\n'
|
|
||||||
, 'values in var with suffix:', head(statistic_chi),'\n'
|
|
||||||
, 'values in var without suffix:', head(stat_chi)
|
|
||||||
)
|
|
||||||
}else{
|
|
||||||
print('FAIL: suffix removal unsuccessful! Please Debug')
|
|
||||||
}
|
|
||||||
|
|
||||||
## pval
|
|
||||||
pvals_chi = sapply(gene_snps_unique,function(m){
|
|
||||||
mut = grepl(m,raw_data$all_muts_gene)
|
mut = grepl(m,raw_data$all_muts_gene)
|
||||||
chisq.test(mut,dst)$p.value
|
mut = as.numeric(mut)
|
||||||
})
|
cat(paste0('Running mutation:', m, '\n'))
|
||||||
|
|
||||||
#pvals_chi
|
model<-glm(dst ~ mut, family = binomial)
|
||||||
head(pvals_chi)
|
|
||||||
|
|
||||||
#2) chi square: custom
|
|
||||||
ors_chi_cus = sapply(gene_snps_unique,function(m){
|
|
||||||
mut = grepl(m,raw_data$all_muts_gene)
|
|
||||||
my_chisq_or(mut,dst)
|
|
||||||
})
|
|
||||||
|
|
||||||
#ors_chi_cus
|
|
||||||
head(ors_chi_cus)
|
|
||||||
|
|
||||||
## pval:fisher (use the same one for custom chi sqaure)
|
|
||||||
pvals_fisher = sapply(gene_snps_unique,function(m){
|
|
||||||
mut = grepl(m,raw_data$all_muts_gene)
|
|
||||||
fisher.test(mut,dst)$p.value
|
|
||||||
})
|
|
||||||
|
|
||||||
#pvals_fisher
|
|
||||||
head(pvals_fisher)
|
|
||||||
|
|
||||||
#3) fisher
|
|
||||||
odds_ratio_fisher = sapply(gene_snps_unique,function(m){
|
|
||||||
mut = grepl(m,raw_data$all_muts_gene)
|
|
||||||
fisher.test(mut,dst)$estimate;
|
|
||||||
})
|
|
||||||
|
|
||||||
#ors_fisher
|
|
||||||
head(odds_ratio_fisher)
|
|
||||||
|
|
||||||
# statistic_chi: has suffix added of '.X-squared'
|
|
||||||
head(odds_ratio_fisher)
|
|
||||||
|
|
||||||
# remove suffix
|
|
||||||
ors_fisher = odds_ratio_fisher
|
|
||||||
names(ors_fisher) = gsub(".odds ratio", "", names(odds_ratio_fisher))
|
|
||||||
|
|
||||||
if (names(ors_fisher)!= names(odds_ratio_fisher) && ors_fisher == odds_ratio_fisher){
|
|
||||||
cat('Sanity check passed: suffix removed correctly\n\n'
|
|
||||||
, 'names with suffix:', head(names(odds_ratio_fisher)), '\n\n'
|
|
||||||
, 'names without suffix:', head(names(ors_fisher)), '\n\n'
|
|
||||||
, 'values in var with suffix:', head(odds_ratio_fisher),'\n'
|
|
||||||
, 'values in var without suffix:', head(ors_fisher)
|
|
||||||
)
|
|
||||||
}else{
|
|
||||||
print('FAIL: suffix removal unsuccessful! Please Debug')
|
|
||||||
}
|
|
||||||
|
|
||||||
|
|
||||||
## fisher ci (lower)
|
|
||||||
ci_lb_fisher = sapply(gene_snps_unique, function(m){
|
|
||||||
mut = grepl(m,raw_data$all_muts_gene)
|
|
||||||
low_ci = fisher.test(table(mut, dst))$conf.int[1]
|
|
||||||
|
|
||||||
})
|
#-------------------
|
||||||
|
# allele frequency
|
||||||
#ci_lb_fisher
|
#-------------------
|
||||||
head(ci_lb_fisher)
|
afs = mean(mut)
|
||||||
|
|
||||||
## fisher ci (upper)
|
#-------------------
|
||||||
ci_ub_fisher = sapply(gene_snps_unique, function(m){
|
# logistic model
|
||||||
mut = grepl(m,raw_data$all_muts_gene)
|
#-------------------
|
||||||
up_ci = fisher.test(table(mut, dst))$conf.int[2]
|
beta_logistic = summary(model)$coefficients[2,1]
|
||||||
|
|
||||||
})
|
|
||||||
|
|
||||||
#ci_ub_fisher
|
|
||||||
head(ci_ub_fisher)
|
|
||||||
|
|
||||||
#4) logistic or
|
|
||||||
ors_logistic = sapply(gene_snps_unique,function(m){
|
|
||||||
mut = grepl(m,raw_data$all_muts_gene)
|
|
||||||
#print(table(dst, mut))
|
|
||||||
model<-glm(dst ~ mut , family = binomial)
|
|
||||||
or_logistic = exp(summary(model)$coefficients[2,1])
|
or_logistic = exp(summary(model)$coefficients[2,1])
|
||||||
#pval_logistic = summary(model)$coefficients[2,4]
|
#print(paste0('logistic OR:', or_logistic))
|
||||||
})
|
|
||||||
|
|
||||||
#ors_logistic
|
|
||||||
head(ors_logistic)
|
|
||||||
|
|
||||||
## logistic p-value
|
|
||||||
pvals_logistic = sapply(gene_snps_unique,function(m){
|
|
||||||
mut = grepl(m,raw_data$all_muts_gene)
|
|
||||||
#print(table(dst, mut))
|
|
||||||
model<-glm(dst ~ mut , family = binomial)
|
|
||||||
pval_logistic = summary(model)$coefficients[2,4]
|
pval_logistic = summary(model)$coefficients[2,4]
|
||||||
|
#print(paste0('logistic pval:', pval_logistic))
|
||||||
|
|
||||||
|
se_logistic = summary(model)$coefficients[2,2]
|
||||||
|
#print(paste0('logistic SE:', se_logistic))
|
||||||
|
|
||||||
|
zval_logistic = summary(model)$coefficients[2,3]
|
||||||
|
#print(paste0('logistic zval:', zval_logistic))
|
||||||
|
|
||||||
|
ci_mod = exp(confint(model))[2,]
|
||||||
|
#print(paste0('logistic CI:', ci_mod))
|
||||||
|
|
||||||
|
ci_lower_logistic = ci_mod[["2.5 %"]]
|
||||||
|
ci_upper_logistic = ci_mod[["97.5 %"]]
|
||||||
|
|
||||||
|
#-------------------
|
||||||
|
# custom_chisq and fisher: OR p-value and CI
|
||||||
|
#-------------------
|
||||||
|
or_mychisq = mychisq_or(dst, mut)
|
||||||
|
#print(paste0('mychisq OR:', or_mychisq))
|
||||||
|
|
||||||
|
odds_fisher = fisher.test(table(dst, mut))$estimate
|
||||||
|
or_fisher = odds_fisher[[1]]
|
||||||
|
|
||||||
|
pval_fisher = fisher.test(table(dst, mut))$p.value
|
||||||
|
|
||||||
|
ci_lower_fisher = fisher.test(table(dst, mut))$conf.int[1]
|
||||||
|
ci_upper_fisher = fisher.test(table(dst, mut))$conf.int[2]
|
||||||
|
|
||||||
|
#-------------------
|
||||||
|
# chi sq estimates
|
||||||
|
#-------------------
|
||||||
|
estimate_chisq = chisq.test(table(dst, mut))$statistic; estimate_chisq
|
||||||
|
est_chisq = estimate_chisq[[1]]; print(est_chisq)
|
||||||
|
|
||||||
|
pval_chisq = chisq.test(table(dst, mut))$p.value
|
||||||
|
|
||||||
|
# build a row to append to df
|
||||||
|
row = data.frame(mutation = m
|
||||||
|
, af = afs
|
||||||
|
, beta_logistic = beta_logistic
|
||||||
|
, or_logistic = or_logistic
|
||||||
|
, pval_logistic = pval_logistic
|
||||||
|
, se_logistic = se_logistic
|
||||||
|
, zval_logistic = zval_logistic
|
||||||
|
, ci_low_logistic = ci_lower_logistic
|
||||||
|
, ci_hi_logistic = ci_upper_logistic
|
||||||
|
, or_mychisq = or_mychisq
|
||||||
|
, or_fisher = or_fisher
|
||||||
|
, pval_fisher = pval_fisher
|
||||||
|
, ci_low_fisher= ci_lower_fisher
|
||||||
|
, ci_hi_fisher = ci_upper_fisher
|
||||||
|
, est_chisq = est_chisq
|
||||||
|
, pval_chisq = pval_chisq
|
||||||
|
)
|
||||||
|
#print(row)
|
||||||
|
|
||||||
|
ors_df <<- rbind(ors_df, row)
|
||||||
|
|
||||||
})
|
})
|
||||||
|
|
||||||
#pvals_logistic
|
#%%======================================================
|
||||||
head(pvals_logistic)
|
# Writing file with calculated ORs and AFs
|
||||||
|
|
||||||
#=============================================
|
|
||||||
|
|
||||||
# check ..(hmmm) perhaps separate script)
|
|
||||||
#afs['pnca_p.trp68gly']
|
|
||||||
#afs['pnca_p.gln10pro']
|
|
||||||
#afs['pnca_p.leu4ser']
|
|
||||||
#
|
|
||||||
#plot(density(log(ors_logistic)))
|
|
||||||
#plot(-log10(pvals))
|
|
||||||
#hist(log(ors)
|
|
||||||
# , breaks = 100)
|
|
||||||
|
|
||||||
# sanity check: if names are equal (just for 3 vars)
|
|
||||||
all(sapply(list(names(afs)
|
|
||||||
, names(pvals_chi)
|
|
||||||
, names(statistic_chi) # should return False
|
|
||||||
, names(ors_chi_cus)), function (x) x == names(ors_logistic)))
|
|
||||||
|
|
||||||
#compare(names(afs)
|
|
||||||
# , names(pvals_chi)
|
|
||||||
# , names(statistic_chi) #TEST: should return False, but DOESN'T
|
|
||||||
# , names(ors_chi_cus)
|
|
||||||
# , names(stat_chi))$result
|
|
||||||
|
|
||||||
#=============== Now with all vars
|
|
||||||
|
|
||||||
# sanity check: names for all vars
|
|
||||||
#c = compare( names(afs)
|
|
||||||
# , names(stat_chi)
|
|
||||||
# , names(statistic_chi) #TEST: should return False, but DOESN'T
|
|
||||||
# , names(pvals_chi)
|
|
||||||
# , names(ors_chi_cus)
|
|
||||||
# , names(pvals_fisher)
|
|
||||||
# , names(ors_fisher)
|
|
||||||
# , names(ci_lb_fisher)
|
|
||||||
# , names(ci_ub_fisher)
|
|
||||||
# , names(ors_logistic)
|
|
||||||
# , names(pvals_logistic))$result; c
|
|
||||||
|
|
||||||
if (all( sapply( list(names(afs)
|
|
||||||
, names(stat_chi)
|
|
||||||
#, names(statistic_chi) # TEST should return FALSE if included
|
|
||||||
, names(pvals_chi)
|
|
||||||
, names(ors_chi_cus)
|
|
||||||
, names(pvals_fisher)
|
|
||||||
, names(ors_fisher)
|
|
||||||
, names(ci_lb_fisher)
|
|
||||||
, names(ci_ub_fisher)
|
|
||||||
, names(pvals_logistic) ), function (x) x == names(ors_logistic)))
|
|
||||||
){
|
|
||||||
cat('PASS: names match: proceed with combining into a single df')
|
|
||||||
} else {
|
|
||||||
cat('FAIL: names mismatch')
|
|
||||||
}
|
|
||||||
|
|
||||||
# combine ors, pvals and afs
|
|
||||||
cat('Combining calculated params into a df: ors, pvals and afs')
|
|
||||||
|
|
||||||
comb_AF_and_OR = data.frame(afs
|
|
||||||
, stat_chi
|
|
||||||
, pvals_chi
|
|
||||||
, ors_chi_cus
|
|
||||||
, pvals_fisher
|
|
||||||
, ors_fisher
|
|
||||||
, ci_lb_fisher
|
|
||||||
, ci_ub_fisher
|
|
||||||
, pvals_logistic
|
|
||||||
, ors_logistic)
|
|
||||||
|
|
||||||
cat('No. of rows in comb_AF_and_OR: ', nrow(comb_AF_and_OR)
|
|
||||||
, '\nNo. of cols in comb_AF_and_OR: ', ncol(comb_AF_and_OR))
|
|
||||||
|
|
||||||
cat('Rownames == mutation: ', head(rownames(comb_AF_and_OR)))
|
|
||||||
|
|
||||||
# add rownames of comb_AF_and_OR as an extra column 'mutation' to allow merging based on this column
|
|
||||||
comb_AF_and_OR$mutation = rownames(comb_AF_and_OR)
|
|
||||||
|
|
||||||
# sanity check
|
|
||||||
if (table(rownames(comb_AF_and_OR) == comb_AF_and_OR$mutation)){
|
|
||||||
cat('PASS: rownames and mutaion col values match')
|
|
||||||
}else{
|
|
||||||
cat('FAIL: rownames and mutation col values mismatch')
|
|
||||||
}
|
|
||||||
#########################################################
|
|
||||||
# write file out: pnca_AF_OR
|
|
||||||
#########################################################
|
|
||||||
cat(paste0('writing output file: '
|
cat(paste0('writing output file: '
|
||||||
, '\nFilename: ', outfile))
|
, '\nFilename: ', out_filename))
|
||||||
|
|
||||||
write.csv(comb_AF_and_OR, outfile
|
write.csv(ors_df, outfile
|
||||||
, row.names = F)
|
, row.names = F)
|
||||||
|
|
||||||
cat(paste0('Finished writing:'
|
cat(paste0('Finished writing:'
|
||||||
, out_filename
|
, outfile
|
||||||
, '\nNo. of rows: ', nrow(comb_AF_and_OR)
|
, '\nNo. of rows: ', nrow(ors_df)
|
||||||
, '\nNo. of cols: ', ncol(comb_AF_and_OR)))
|
, '\nNo. of cols: ', ncol(ors_df)))
|
||||||
#************************************************
|
#************************************************
|
||||||
cat('\n======================================================================\n')
|
cat('\n======================================================================\n')
|
||||||
rm(out_filename)
|
|
||||||
cat('End of script: calculated AF, OR, pvalues and saved file')
|
cat('End of script: calculated AF, OR, pvalues and saved file')
|
||||||
|
|
||||||
#########################################################
|
|
||||||
# 3: Merge meta data file + calculated num params
|
|
||||||
#########################################################
|
|
||||||
#df1 = gene_metadata
|
|
||||||
#df2 = comb_AF_and_OR
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
# COMMENT: will do the combining with the other OR and AF (in python)
|
|
||||||
|
|
|
||||||
|
|
@ -167,7 +167,7 @@ cat(paste0('Total no. of distinct comp snps to perform OR calcs: ', length(gene_
|
||||||
#x = as.numeric(mut)
|
#x = as.numeric(mut)
|
||||||
#y = dst
|
#y = dst
|
||||||
|
|
||||||
custom_chisq_or = function(x,y){
|
mychisq_or = function(x,y){
|
||||||
tab = as.matrix(table(x,y))
|
tab = as.matrix(table(x,y))
|
||||||
a = tab[2,2]
|
a = tab[2,2]
|
||||||
if (a==0){ a<-0.5}
|
if (a==0){ a<-0.5}
|
||||||
|
|
@ -232,7 +232,7 @@ pval_fisher = fisher.test(table(mut, dst))$p.value; print(paste0('pval fisher:',
|
||||||
|
|
||||||
|
|
||||||
#3) custom chisq
|
#3) custom chisq
|
||||||
or_mychisq = custom_chisq_or(mut,dst)
|
or_mychisq = mychisq_or(mut,dst)
|
||||||
|
|
||||||
#4) logistic
|
#4) logistic
|
||||||
summary(model<-glm(dst ~ mut, family = binomial))
|
summary(model<-glm(dst ~ mut, family = binomial))
|
||||||
|
|
@ -277,7 +277,7 @@ snps
|
||||||
# custom chisq
|
# custom chisq
|
||||||
ors = sapply(snps,function(m){
|
ors = sapply(snps,function(m){
|
||||||
mut = grepl(m,raw_data$all_muts_gene)
|
mut = grepl(m,raw_data$all_muts_gene)
|
||||||
custom_chisq_or(mut,dst)
|
mychisq_or(mut,dst)
|
||||||
})
|
})
|
||||||
head(ors)
|
head(ors)
|
||||||
|
|
||||||
|
|
@ -423,7 +423,7 @@ x = sapply(snps,function(m){
|
||||||
ci_upper_logistic = ci_mod[["97.5 %"]]
|
ci_upper_logistic = ci_mod[["97.5 %"]]
|
||||||
|
|
||||||
# custom_chisq and fisher: OR p-value and CI
|
# custom_chisq and fisher: OR p-value and CI
|
||||||
or_mychisq = custom_chisq_or(dst, mut)
|
or_mychisq = mychisq_or(dst, mut)
|
||||||
|
|
||||||
or_fisher = fisher.test(dst, mut)$estimate
|
or_fisher = fisher.test(dst, mut)$estimate
|
||||||
or_fisher = or_fisher[[1]]
|
or_fisher = or_fisher[[1]]
|
||||||
|
|
@ -523,7 +523,7 @@ for (i in snps){
|
||||||
#=====================
|
#=====================
|
||||||
# custom chi square
|
# custom chi square
|
||||||
#=====================
|
#=====================
|
||||||
or_mychisq = custom_chisq_or(mut,dst)
|
or_mychisq = mychisq_or(mut,dst)
|
||||||
|
|
||||||
#=====================
|
#=====================
|
||||||
# chi square
|
# chi square
|
||||||
|
|
|
||||||
Loading…
Add table
Add a link
Reference in a new issue