what do you mean by UPGMA ?

Ali Mohammed Yaseen Al Hashemi , an Unweighted Pair Group Method with Arithmetic Mean, as a clustering analysis method.

Although the clustering methods depend on the proximities, I would recommend you to consider both of them separately at the beginning.

On the one hand, we have the proximities. Given your dataset, I would recommend you to use a proximity measure that is common to find in other works with binomial data, for example Jaccard, Lance and Williams, Yule's Y or even the Euclid distance. In the end, the proximity is measuring how "close/far away" are your observations/variables with respect to one another in your dataset. Intuitively, you are extracting the information of similarity/dissimilarity among your data, and therefore, your proximity/dissimilarity measure should try to take into account what is in your data. For example, with high-correlated interval data, I will recommend using Mahalanobis and, I will not trust any Euclid distance. But, in your case, I recommend you to use several proximities/dissimilarities and compare the results among them.

On the other hand, with respect to the clustering method. UPGMA is ok. In the end, UPGMA is taking into account your proximities/dissimilarities measures independently of how the original data was. Nonetheless, I recommend trying different pairs of proximities/dissimilarities - clustering method. Given that you are working with a Hierarchical one, I recommend you these pairs (among many others):

Jaccard - Ward clustering method

Y's Yule - Simply linkage

Y's Yule - Complete Linkage.

These two last cases work in opposite ways, therefore may provide you with useful insights. I hope I was helpful. Clustering is quite tricky.