I am using MetaboAnalystR version 4.2.0. Before the filtering step, the mSet object was correctly registered in the environment as a 'List of 6'. After I used this FilterVariable function (like this: mSet <- FilterVariable(mSetObj = mSet, qc.filter= "F", var.filter = "iqr", var.cutoff = 10), I received the message: " Feature filtering based on Interquantile Range - removed 29 based on the cutoff." indicating that the filtering process successfully completed. However, in the environment somewhat mSet object is set to values of 2. And I couldnot proceed to my pipeline. Although filtering appears successful, the mSet object in the environment was corrupted (or overwritten). Instead of retaining its complex structure, it was reset to a simple numeric value (2). As a result, I can no longer proceed with the pipeline, as subsequent functions (like Normalization) throw errors. Could you explain why I keep getting this error? Without using this function, everything appears to be working perfectly. Thank you very much for your time.
I am using MetaboAnalystR version 4.2.0. Before the filtering step, the mSet object was correctly registered in the environment as a 'List of 6'. After I used this FilterVariable function (like this: mSet <- FilterVariable(mSetObj = mSet, qc.filter= "F", var.filter = "iqr", var.cutoff = 10), I received the message: " Feature filtering based on
Interquantile Range- removed 29 based on the cutoff." indicating that the filtering process successfully completed. However, in the environment somewhat mSet object is set to values of 2. And I couldnot proceed to my pipeline. Although filtering appears successful, the mSet object in the environment was corrupted (or overwritten). Instead of retaining its complex structure, it was reset to a simple numeric value (2). As a result, I can no longer proceed with the pipeline, as subsequent functions (like Normalization) throw errors. Could you explain why I keep getting this error? Without using this function, everything appears to be working perfectly. Thank you very much for your time.