When migrating a repo from bitbucket to github, I like to take a simple and straightforward approach:
git remote set-url origin [email protected]:USERNAME/REPONAME.git
This example assumes that a remote branch named origin points to bitbucket, and you are resetting
that URL to now point to github. Then you can git push to github.
| curl -O -L https://github.com/iontorrent/TS/archive/TorrentSuite_5.2.2-sp1.tar.gz |
| #!/bin/bash | |
| #PBS -N name | |
| #PBS -l nodes=1:ppn=1,mem=10gb,walltime=6:00:00 | |
| #PBS -m n | |
| #PBS -j oe | |
| #PBS -r n | |
| module load R/3.3.2 gcc/4.9.2 | |
| module load pandoc/1.13.1 |
| mini <- matrix(rnorm(4000*50), nrow=4000, ncol=50) | |
| system.time(M <- cor(t(mini), t(mini), method='pearson')) | |
| fastcorr <- function(x) { | |
| # fast correlation between rows of x | |
| # from http://stackoverflow.com/questions/18964837/fast-correlation-in-r-using-c-and-parallelization | |
| if (!is.matrix(x)) x <- as.matrix(x) | |
| x <- x - rowMeans(x) | |
| x <- x/sqrt(rowSums(x^2)) | |
| tcrossprod(x) |
| library(tidyverse) | |
| library(Seurat) | |
| # Find specific markers for each cell type | |
| celltypes <- # list of cell types (unique ident labels of Seurat object) | |
| obj <- # Seurat object | |
| specific_markers <- NULL | |
| # First we do all pairwise comparisons and retain any markers that | |
| # are even somewhat higher in the cell type of interest |
| #!/bin/sh | |
| # works on a machine running CentOS 7.7 | |
| # no error checking and this requires manual intervention. This script just gives | |
| # an overview of the process. | |
| # | |
| # https://github.com/rust-lang/cargo/issues/713 was helpful... | |
| mkdir -p apps/mosh | |
| cd apps/mosh |
| # Intalling leafcutter on a CentOS 6.5 machine | |
| # This machine has glibc 2.12 and leafcutter needs glibc 2.14 | |
| module purge | |
| module load gcc/4.9.2 | |
| # Install glibc 2.14 | |
| mkdir $HOME/apps/glibc_install | |
| cd $HOME/apps/glibc_install | |
| wget http://ftp.gnu.org/gnu/glibc/glibc-2.14.tar.gz | |
| tar zxvf glibc-2.14.tar.gz |
| library(tidyverse) | |
| library(biomaRt) | |
| genes <- # FILL ME IN ... Should be a vector of gene names | |
| markers <- # FILL ME IN ... Should be a data.frame with at least one column called mgi_symbol | |
| ensembl <- useMart("ensembl", dataset="mmusculus_gene_ensembl") # Mouse | |
| # GO:0009986 is cell surface | |
| go_cellsurf <- "GO:0009986" | |
| gene.data <- getBM(attributes=c("mgi_symbol", "ensembl_gene_id", "go_id"), |
| library(tidyverse) | |
| library(Seurat) | |
| library(doParallel) | |
| # Find specific markers for each cell type | |
| n.cores <- 10 | |
| registerDoParallel(cores=n.cores) | |
| celltypes <- # list of cell types (unique ident labels of Seurat object) | |
| obj <- # Seurat object |
| read10x <- function(dir) { | |
| names <- c("barcodes.tsv", "features.tsv", "matrix.mtx") | |
| for (i in 1:length(names)) { | |
| R.utils::gunzip(paste0(dir, "/", names[i], ".gz")) | |
| } | |
| file.copy(paste0(dir, "/features.tsv"), paste0(dir, "/genes.tsv")) | |
| mat <- Seurat::Read10X(dir) | |
| file.remove(paste0(dir, "/genes.tsv")) | |
| for (i in 1:length(names)) { | |
| R.utils::gzip(paste0(dir, "/", names[i])) |