View get_all_clin.R
# This code will get all clinical indexed data from TCGA
library(TCGAbiolinks)
library(data.table)
clinical <- TCGAbiolinks:::getGDCprojects()$project_id %>%
regexPipes::grep("TCGA",value=T) %>%
sort %>%
plyr::alply(1,GDCquery_clinic, .progress = "text") %>%
rbindlist
readr::write_csv(clinical,path = paste0("all_clin_indexed.csv"))
View maf_legacy.R
query.maf.hg19 <- GDCquery(project = "TCGA-COAD",
data.category = "Simple nucleotide variation",
data.type = "Simple somatic mutation",
access = "open",
legacy = TRUE)
# Check maf availables
knitr::kable(getResults(query.maf.hg19)[,c("created_datetime","file_name")])
query.maf.hg19 <- GDCquery(project = "TCGA-COAD",
data.category = "Simple nucleotide variation",
View bkup_dotfiles_configs.md

backup dotfiles

  • Following will copy all of dot ~/. files and directories (including its contents) directly underneath home directory.
  • To avoid copying cache and other local configs, e.g., that of web browser, java apps, etc., preferably query directory size tool under entire home $HOME/, using ncdu $HOME of similar tool.
  • Exclude all those large directories using rsync --exclude=.local --exclude=.cache format
  • Avoid rsync password, ssh keys, .bash_history, etc. if you are uploading to github, etc.
  • rsync home dotfiles and configs as follows:
# in your local machine
View msigdf_clusterprofiler.R
## devtools::install_github("stephenturner/msigdf")
library(msigdf)
library(dplyr)
library(clusterProfiler)
c2 <- msigdf.human %>%
filter(collection == "c2") %>% select(geneset, entrez) %>% as.data.frame
data(geneList)
de <- names(geneList)[1:100]
View human_mouse_1to1_orthologs.csv
human mouse
A1BG A1bg
A1CF A1cf
A2LD1 A2ld1
A2M A2m
A4GALT A4galt
A4GNT A4gnt
AAAS Aaas
AACS Aacs
AADAC Aadac
View natural_sort_vcf.sh
chmod a+x vcfsort.sh
vcfsort.sh trio.trim.vep.vcf.gz