saving work before converting to a function

scripts/af_or_calcs.R

@@ -71,10 +71,6 @@ cat(paste0('Output file with full path:', outfile_af_or))
 #########################################################
 raw_data_all = read.csv(infile_master, stringsAsFactors = F)
 
-# building cols to extract
-dr_muts_col = paste0('dr_mutations_', drug)
-other_muts_col = paste0('other_mutations_', drug)
-
 cat('Extracting columns based on variables:\n'
       , drug
       , '\n'
@@ -217,22 +213,23 @@ pval_logistic = summary(model)$coefficients[2,4]
 print(paste0('logistic pval:', pval_logistic))
 
 #=====================================
-#OR calcs using the following 4
+# OR calcs using the following 4
-#1) chisq.test
+#1) logistic
-#2) fisher
+#2) custom chisq.test
-#3) modified chisq.test
+#3) fisher
-#4) logistic
+#4) chisq.test
-#5) adjusted logistic?
-#6) kinship (separate script)
 
+# adjusted logistic (NO good)
+# kinship (separate script)
 #======================================
 # TEST FOR a few muts: sapply and df
-#===============================================
+#======================================
 #snps <- gene_snps_unique[1:2]# reassign so you test with subset of muts
 snps <- gene_snps_unique 
-cat(paste0('Running calculations for:', length(snps), ' nssnps\n'
+cat(paste0('Running calculations for:'
-, 'gene: ', gene
+           , length(snps), ' nssnps\n'
-, '\ndrug: ', drug ))
+           , 'gene: ', gene
+           , '\ndrug: ', drug ))
 
 # DV: <drug> 0 or 1
 dst = raw_data[[drug]]