| ```{r} | |
| library(GEOquery) | |
| library(tidyverse) | |
| meta<- getGEO(GEO= "GSE185507",GSEMatrix=FALSE) | |
| ``` | |
| ```{r} | |
| meta@gsms$GSM5616943@header$characteristics_ch1 | |
| ``` |
| ```{r} | |
| TAAs<- c("MSLN", "EGFR", "ERBB2", "CEACAM5", "NECTIN4", "EPCAM", "MUC16", "MUC1", "CD276", | |
| "FOLH1", "DLL3", "VTCN1", "PROM1", "PVR", "CLDN6", "MET", "FOLR1", "TNFRSF10B", "TACSTD2") | |
| ``` | |
| ```{r} | |
| TCGAExprsAndPheno2 <- function(gene_vector, cancer_types = "all", expression_type = "TPM"){ | |
| library(recount3) | |
| ## Get all possible projects |
| > library(dplyr) | |
| > cars %>% | |
| as_tibble %>% | |
| mutate(case_code = case_when( | |
| speed == 4 & dist == 2 ~ "this", | |
| dist > 6 & dist == 10 ~ "is", | |
| speed >=10 & dist >= 18 ~ "awesome")) | |
| # A tibble: 50 × 3 |
| library(tidyverse) | |
| df_students <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-05-07/student_teacher_ratio.csv") | |
| df_world_tile <- readr::read_csv("https://gist.githubusercontent.com/maartenzam/787498bbc07ae06b637447dbd430ea0a/raw/9a9dafafb44d8990f85243a9c7ca349acd3a0d07/worldtilegrid.csv") %>% | |
| mutate( | |
| ## Namibias two-digit country code is handled as `NA` - let us fix that | |
| alpha.2 = if_else(name == "Namibia", "NA", alpha.2), | |
| ## We are going to split "Americas" into "North America" and "Sout America" | |
| region = if_else(region == "Americas", sub.region, region), |
| install.packages(c("tidyverse", "janitor", "readxl")) | |
| library(tidyverse) | |
| library(janitor) | |
| library(readxl) | |
| convert_MDS_to_Prism<- function(infile_path, sheet_range, outfile_path){ | |
| if (!file.exists(infile_path)){ | |
| stop("the input file does not exist, please check your file name!") | |
| } |
other databases: https://twitter.com/tangming2005/status/1470513427080699905
GSEA has a geneset https://www.gsea-msigdb.org/gsea/msigdb/cards/GOCC_CELL_SURFACE.html use https://cran.r-project.org/web/packages/msigdbr/vignettes/msigdbr-intro.html to get it
library(msigdbr)
cell_surface_proteins<- msigdbr(species = "Homo sapiens", category = "C5") %>%
filter(gs_name == "GOCC_CELL_SURFACE") %>%
pull(human_gene_symbol)
| --[[ | |
| ## Modulefile in lua syntax | |
| ## Author: Samir Amin | |
| ## Read about Lmod | |
| ## https://lmod.readthedocs.io/en/latest/015_writing_modules.html | |
| ## https://lmod.readthedocs.io/en/latest/050_lua_modulefiles.html | |
| ## https://lmod.readthedocs.io/en/latest/020_advanced.html | |
| --]] |
| Note, bed file is 0-based, and R is 1 based. when import bed file to | |
| R, the GRanges will add 1 in the start. | |
| cat test.bed | |
| chr1 1 14 | |
| chr1 14 20 | |
| chr1 30 38 | |
| ```{r} |
| library(Seurat) | |
| library(aplot) | |
| library(tidyverse) | |
| cluster_dot_plot<- function(obj, features, annotation){ | |
| p<- DotPlot(object = obj, features = features) | |
| df<- p$data | |
| df<- left_join(df, annotation, by =c("id" = "seurat_clusters")) %>% | |
| mutate(id = paste0(annotation, "_", id)) | |
| (defun new-copyright () | |
| "Generate new copyright string." | |
| (format-time-string "Copyright %Y Michael M. Hoffman <[email protected]>")) | |
| (define-auto-insert 'python-mode | |
| `( | |
| "Description: " | |
| "#!/usr/bin/env python3.6" \n | |
| "\"\"\"" (setq basename (buffer-file-basename)) ": " str \n | |
| "\"\"\"" \n \n |