Hierarchical/nested condition variables in MSstatsTMT

[Stephanie Huang]

Hi MSstats Team!

I was wondering if there is a feature in MSstatsTMT or a way to input an argument in the linear mixed-effects models package (lme4 or lmerTest) to deal with hierarchical/nested variables.

I have a main experimental manipulation, but I also want to look at other subject variables, such as LitterID and Sex, without splitting them into independent groups.

Main experimental manipulation

Housing Condition: Environmental Enrichment (EE) or Standard Housing (SH)

Subject Variables

LitterID: S426, S328, S423, S329, S332, etc

Sex: Female (F) vs Male (M)

Age: 80 - 110 days (continuous)

Confounding Variables

Cohort (collection point in year): 3a, 3b, 4 

For example, in my annotation file, I have currently split my conditions into small independent groups in order to examine my main experimental manipulation (Housing) plus a subject variable (in this case, LitterID).


I was wondering if there is a way to nest these variables hierarchically? And also, is there a way to deal with subject versus confounding variables?

Thank you!
Stephanie

[vitek...@gmail.com]

Hi Stephanie,

Thank you for reaching out. We'd need to know more about your experimental layout and the structure of the hierarchy to advise. For example,  at which level is the treatment applied (e.g., is it litter?) At what level do you collect the measurements (i.e., are the measurements per litter, or per animal within a litter?). Sex and Age are fixed factors (as opposed to random factors), so they are probably crossed (as opposed to nested). Also, I am not quite sure of the meaning of a Cohort. Finally, since this is TMT, how are the measurements allocated to TMT plexes?

Could you describe the experiment in more details? I will do my best to comment. Please feel free to send a personal email.

Thank you for using MSstats

Sincerely

Olga

[Stephanie Huang]

Hi Olga,

Thank you so much for getting back to me!
That would be much appreciated! I'll send you an email with some more details on the experimental setup.

Best wishes!
Stephanie