  We study the supercluster shape properties of the recently compiled SDSS
cluster catalog using an approach based on differential geometry. We detect
superclusters by applying the percolation algorithm to observed cluster
populations, extended out to $z_{\rm max}\leq 0.23$ in order to avoid selection
biases. We utilize a set of shapefinders in order to study the morphological
features of superclusters with $\geq 8$ cluster members and find that
filamentary morphology is the dominant supercluster shape feature, in agreement
with previous studies.
