Pathway level analysis of single-cell gene expression I'm looking for single-cell specific methods to construct (using gene expression data) new features that express pathway "level" or "activity", and then use these for clustering cells.

One example for bulk RNA-seq is PLAGE, implemented in the GSVA R package.

I have found only one method for single-cell RNA-seq that comes close: pagoda in the scde R package. This performs PCAs for each pathway, using its genes.

A very similar question is Classification (supervised learning) of expression data on pathway level, on bulk/microarray data.
Package Hipathia allows you to compute a value of "activity" for each pathway and each cell, so that the matrix of gene expression is transformed into a matrix of pathway activity. You can use this matrix for further analysis, cell differentiation and clustering. You can also compute functional activity matrices in the same way.