A dummy example for testing
cat DATA.tsv
ID head1 head2 head3 head4
1 25.5 1364.0 22.5 13.2
2 10.1 215.56 1.15 22.2
cat LIST.TXT
ID
#! /bin/bash | |
set -e | |
set -u | |
set -o pipefail | |
#### Author: Ming Tang (Tommy) | |
#### Date 09/29/2016 | |
#### I got the idea from this stackOverflow post http://stackoverflow.com/questions/11098189/awk-extract-columns-from-file-based-on-header-selected-from-2nd-file |
A dummy example for testing
cat DATA.tsv
ID head1 head2 head3 head4
1 25.5 1364.0 22.5 13.2
2 10.1 215.56 1.15 22.2
cat LIST.TXT
ID
### Define intronic, exonic and intergenic regions | |
```{r} | |
library(AnnotationHub) | |
library(dplyr) ## for %>% | |
ah = AnnotationHub() | |
possibleDates(ah) | |
AnnotationHub::query(ah, c("gtf", "Homo_sapiens", "GRCh37")) | |
GRCh37.gtf<- ah[['AH10684']] |
```r | |
library(TxDb.Hsapiens.UCSC.hg19.knownGene) | |
UCSC.hg19<- TxDb.Hsapiens.UCSC.hg19.knownGene | |
hg19.genes<- genes(UCSC.hg19) | |
transcriptsBy(UCSC.hg19, "gene") | |
library("org.Hs.eg.db") | |
## note that dplyr and AnnotationDbi both have a function called select | |
## use dplyr::select when use dplyr |
export VEP_PATH=$HOME/vep
export VEP_DATA=$HOME/.vep
mkdir $VEP_PATH $VEP_DATA; cd $VEP_PATH
curl -LO https://github.com/Ensembl/ensembl-tools/archive/release/86.tar.gz
/usr/local/Cellar/gnu-tar/1.29_1/bin/tar -zxf 86.tar.gz --starting-file variant_effect_predictor --transform='s|.*/|./|g'
rsync -zvh rsync://ftp.ensembl.org/ensembl/pub/release-86/variation/VEP/homo_sapiens_vep_86_GRCh37.tar.gz $VEP_DATA
#!/bin/sh | |
## orginal from https://gist.github.com/lazywei/12bc1669dc7739dccef1 | |
## author Ming Tang (Tommy) | |
## 2016-11-20 | |
set -e | |
set -u | |
set -o pipefail |
#!/bin/bash | |
# Script for installing tmux on systems where you don't have root access. | |
# tmux will be installed in $HOME/local/bin. | |
# It's assumed that wget and a C/C++ compiler are installed. | |
# original from https://gist.github.com/smsharma/0003b61a571cab63ad80 | |
# exit on error | |
set -e |
From David Robinson:
<script async src="//platform.twitter.com/widgets.js" charset="utf-8"></script>A tidyverse approach to ROC curves #rstats pic.twitter.com/buizc7U9ns
— David Robinson (@drob) November 29, 2016
library(tidyverse)
theme_set(theme_minimal())
rGREAT is an R client written by the same author of ComplexHeatmap
for the web GREAT Tool
#library(devtools)
#install_github("jokergoo/rGREAT")
library(rGREAT)
colors = structure(circlize::rand_color(4), names = c("a", "b", "c", "d"))
discrete_mat = matrix(sample(letters[1:4], 100, replace = TRUE), 10, 10)
cell_fun = function(j, i, x, y, width, height, fill) {
grid.rect(x = x *0.6, y = y, width = width * 0.6, height = height,
gp = gpar(col = "grey", fill = fill))
}