Introduction Technological and computational advances in genomics and interactomics have made it possible to identify how disease mutations perturb protein–protein
Introduction NicheNet, a method that predicts ligand–target links between interacting cells by combining their expression data with prior knowledge on
Introduction RUVseq can conduct a differential expression (DE) analysis that controls for “unwanted variation”, e.g., batch, library preparation, and other
Introduction Whether it is single-cell RNA sequencing or bulk RNA sequencing, we need to perform differential gene expression analysis and
Introduction Somethimes we need to replace multiple contents of vector in R , like I want to replace a to
Introduction By performing a pan-cancer analysis of single myeloid cells , authors found that some mutations were correlated with the
Introduction In this paper, by performing a pan-cancer analysis of single myeloid cells from 210 patients across 15 human cancer
# set a color for each cancer type library(RColorBrewer) cancer_color <- data.frame(“type”=sort(unique(readRDS(“CCLE_heterogeneity_Rfiles/CCLE_metadata.RDS”) $cancer_type_trunc)), “color”= c(brewer.pal(12, “Set3”)[c(1:6,8,7,10:11)], “maroon”,”gray93″, “yellow2”, “goldenrod1”, “slateblue2”),stringsAsFactors
Introduction In this paper, single-cell 10X RNA sequencing was performed on a mixture of a variety of known cell lines
Introduction Do not require additional dependencies, follow this comparison table to merge to switch between ensemble ID and gene symbol