zhilongjia

#! /usr/bin/Rscript

# This script is used for getting the period (days) needed for a manuscript to be 
# accepted after receievd in journals of the area of bioinformatics.

# ref: http://www.r-bloggers.com/bioinformatics-journals-time-from-submission-to-acceptance-revisited/
    
    
################################################################################
# Some bioinformatics journals

zhilongjia

# Mappings between GPL and Bioconductor microarry annotation packages
# 2015-09-21
library(GEOmetadb)
if(!file.exists('GEOmetadb.sqlite')) getSQLiteFile()
con <- dbConnect(SQLite(),'GEOmetadb.sqlite')
write.table( getBiocPlatformMap(con), file="GPL_Bioconductor.txt", sep="\t", quote=F, row.names=F)

# ref: http://www.bioconductor.org/packages/release/bioc/vignettes/GEOmetadb/inst/doc/GEOmetadb.html#mappings-between-gpl-and-bioconductor-microarry-annotation-packages

zhilongjia

# @knitr template_objects
# For package 'rpm'

# data

rmd.template <-
'\n
## Introduction
ADD_TEXT_HERE

zhilongjia

# visulising the correltion between two views of the same samples
# such as the first 4 features in mtcars as 1 view, the others as another view.
# as it not easy to implement using corrplot.
# the resulting figure
![clustering correlation](https://i.ibb.co/LRKsKCC/corrletion-hclust.png])

library(ComplexHeatmap)

data(mtcars)

zhilongjia

#! /usr/bin/bash

# parameter parsing
while getopts ":d:t:ch" opt; do
  case ${opt} in
    d )
      dir=$OPTARG
      ;;
    # s )
    #   target=$OPTARG

zhilongjia

## Bioconductor package download
library(dplyr)
pkname="cogena"
cogena_download_tabs <- readr::read_tsv(paste0("http://bioconductor.org/packages/stats/bioc/", pkname, "/", pkname, "_stats.tab") )
print("The total downloading number of cogena: ")  
dplyr::filter(cogena_download_tabs, Month=="all") %>% 
    select(Nb_of_downloads) %>% unlist(use.names = FALSE) %>% sum()

#####################################################
# Or via `BiocPkgTools` package