Input-format.md

@@ -49,8 +49,8 @@ ID | Sex | Age | LDL-C | HDL-C |  HDL-D | HDL-TG | ..........
 ### 4) Phenotypes summary file
 
 This is a csv file with columns separated by commas and a header line. This file aims at describing the role of each variable contained in the phenotypes file. For each selected variable, the user must provide a label and a binary indicator for classification as confounding factors (i.e. variables systematically included as covariates), outcome (i.e. each single variable that will be treated as a primary outcome) and candidate covariates (i.e. variables that will be assessed by CMS for inclusion as a covariate).  
-`Note that variables classified as confounding factor cannot be used as either outome or covariate, and such combination will be flagged as an error.`  
-By default, all variables in "Covariates" column will be included as covariates in each outcome analysis. The "Excluded" column give the opportunity to exclude specific variables from covariates for a given outcome. These variables must be separated by ";" without any spaces. If no variables need to be excluded, simply let the column empty. In the example, we exclude all "HDL" variable when analysing one of them.  
+`Note that variables classified as confounding factor cannot be used as either outcome or covariate, and such combination will be flagged as an error.`  
+By default, all variables in "Covariates" column will be included as covariates in each outcome analysis. The "Excluded" column give the opportunity to exclude specific variables from covariates for a given outcome. These variables must be separated by semicolon without any spaces. If no variables need to be excluded, simply let the column empty. In the example, we exclude all "HDL" variable when analyzing one of them.  
 
 Example: