# How to specify which one is Covariates (control for)?

**URL:** <https://forum.biobakery.org/t/how-to-specify-which-one-is-covariates-control-for/5539>\
**Category:** MaAsLin\
**Created:** [June 26, 2023, 2:38am UTC](https://forum.biobakery.org/t/how-to-specify-which-one-is-covariates-control-for/5539 "2023-06-26T02:38:30Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![APeh](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.biobakery.org/apeh/32/2226_2.png) [@APeh](https://forum.biobakery.org/u/APeh)\
**Post date:** [June 26, 2023, 2:38am UTC](https://forum.biobakery.org/t/how-to-specify-which-one-is-covariates-control-for/5539/1 "2023-06-26T02:38:30Z")

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I am new to MaAslin2, and wish to learn more.  
I have microbiome data that I which to find specific taxa that are significantly related to the factor A, B and C (Location is categorical; Factor A, B and C is continuous variable). However, because the microbiome is also environmentally driven, I would like to remove the environmental effect. So I have data similar to the attached table below. My question is: do I need to specifically remove the environmental effect (Location), if yes, how should I do this? I am using the code below (as I want to look at significant microbiome related to all the factor A, B and C):  
fit\_data= Maaslin2(  
input\_data = df\_input\_data,  
input\_metadata = df\_input\_metadata,  
output = “result”)

Thank you.

![image](https://canada1.discourse-cdn.com/flex027/uploads/biobakery/original/2X/b/be2c30df22aed40ba5a49a1348487e4136336e5d.png)

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**Author:** ![nearinj](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.biobakery.org/nearinj/32/2135_2.png) [@nearinj](https://forum.biobakery.org/u/nearinj)\
**Post date:** [June 26, 2023, 2:48pm UTC](https://forum.biobakery.org/t/how-to-specify-which-one-is-covariates-control-for/5539/2 "2023-06-26T14:48:39Z")

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Hi @APeh ,

First of all thanks for taking interest in our tool. I would suggest checking out the tutorial found here: [MaAsLin2 · biobakery/biobakery Wiki · GitHub](https://github.com/biobakery/biobakery/wiki/maaslin2) and the user manual found here: [GitHub - biobakery/Maaslin2: MaAsLin2: Microbiome Multivariate Association with Linear Models](https://github.com/biobakery/Maaslin2).

To answer your question I would suggest implementing a model with fixed effects for all three factors and your location.

Fixed effects can be specified using the `fixed_effects`

Cheers,  
Jacob Nearing