In BioData-PT/D-cellerate: D-Cellerate

knitr::opts_chunk$set(echo = TRUE, fig.align = "center")

Load required packages

library(knitr)
library(Seurat)
library(Matrix)
#require("stringr")

Import Data

#-- import.params

dim(mat)

This data set contains r dim(mat)[1] genes and r dim(mat)[2] cells.

Filter

#-- filter.params

dim(sobj)

The filtered data set contains r dim(sobj)[1] genes and r dim(sobj)[2] cells.

Normalize

#-- normalize.params

Variable genes

#-- vargenes.params

PCA

#-- pca.params

dim1 <- 1; dim2 <- 2; dim3 <- 3

Clustering

#-- cluster.params

#-- cluster.renamed.params

Dimensional Reduction

#-- tsne.params

DimPlot(sobj, reduction = "tsne", label = TRUE)

Marker Gene Identification

#-- marker.params
marker.params$genes <- strsplit(stringr::str_replace_all(marker.params$genes, 
                                                         "c\\(|[^[A-Za-z0-9,]]", ""), ",")[[1]] # parse genes 
marker.params$top.marker.genes <- strsplit(stringr::str_replace_all(marker.params$top.marker.genes, 
                                                         "c\\(|[^[A-Za-z0-9,-]]", ""), ",")[[1]] # parse genes