Fuzzy cMeans clustering of RNAseq data using mFuzz
Note this is part 4 of a series on clustering RNAseq data. Check out part one on hierarcical clustering here ; part two on K-means clustering here ; and part three on fuzzy c-means clustering here.
Clustering is a useful data reduction technique for RNAseq experiments. In previous posts, we discussed the usefulness of hard clustering techniques such as hierarcical clustering and K-means clustering. These techniques will partition all genes into co-expression clusters.