Script to allow gene set enrichment analysis of 10x genomics data in R I have 10x single cell RNA seq data. Which R package is best suited for analysis of the 10x data matrix. What is the script to prepare the data for downstream GSEA analysis.

I have already processed samples for single cell data (for multiple other purposes). my intention is to focus on subpopulations i.e. cell type x at different time points i.e. time 0, 1, 2 etc and compare the enriched gene pathways in this one cell type at different time points. there are three files that are used (at least in the R Seurat package) with the following file extensions: .mtx, .tsv (barcodes.tsv, genes.tsv and matrix.mtx). the R Seurat package merges these files to create a "Seurat object" which helps mainly with identifying individual diffl gene expression in each barcode cell 

I found a package for R: goseq that at least has been used for bulkRNA seq but I was hoping someone has used this package specifically for single cell RNA seq data, and what script has been used to merge the 3 files to create an object for analysis. pardon my terminology, but I am a novice to R and have experience primarily through package use.
Seruat will give you a list of genes which it thinks are upregulated in a particular cluster. Look at the functions that talk about marker genes - these functions basically do a DE analysis of the genes in one cluster compared to the others.

Then take that list and feed it to any standard GO analysis tool. Have a look at the topGO topKEGG and geneSetTest functions in the limma package, the GOStats package and the gsea. All should be suitable.  The GOSeq package is designed to compensate for gene length bias in RNA-seq experiments. As 10X only samples 3'-tags, there shouldn't be any gene-length bias in the data, so this shouldn't be an issue.