Controls / cases counts inverted when using binary model

[GACGAMA]

Hello!

I've finished analyzing a large cohort using 0/1 numerical values for control/case status respectively. Then I went to my vcf to count the distributions of variants for each group. But what I saw was the contrary of what I expected, I found things that seemed enriched in controls instead of case. Is that the expected order for the enrichment?

I observed that when looking for the percentage comparing controls and cases, the results are both ways - some seemed enriched for controls (most of them) and some for cases, so I'm not sure how to interpret this

Should I repeat by inversing 0/1 as case/control respectively to find things enriched in cases?

One example:

gene_step	gene	Cases_Sum_nHet	Control_Sum_nHet	Total X more in controls
MUC4_ODMS_WGS_WES_MUC4_synonymous	MUC4	261	2829	10.83908046
METTL1_ODMS_WGS_METTL1_promoter_CAGE	METTL1	4	0	0

To count, I summed the genotype calls for each group (case and control) and summarized it for each gene-category pair. As you can see, I have a lot more total Heterozygous calls for controls in one example and cases in another