oganm

library(XLConnect)
library(magrittr)
library(dplyr)

# mouse rna seq data download Zeisel et al. download------
dir.create('data-raw/ZeiselMouse', showWarnings=FALSE)
download.file(url= 'http://storage.googleapis.com/linnarsson-lab-www-blobs/blobs/cortex/expression_mRNA_17-Aug-2014.txt', 
destfile='data-raw/ZeiselMouse/mouseRNASeq_Zeisel 2015.txt')
download.file(url = 'http://science.sciencemag.org/highwire/filestream/628248/field_highwire_adjunct_files/1/aaa1934_TableS1.xlsx',
              destfile = 'data-raw/ZeiselMouse/markerGenes.xlsx')

pimentel

suppressPackageStartupMessages({
  library('Biobase')
  library('DESeq2')
  library('sleuth')
})

base_dir <- "~/Downloads/cuffdiff2_data_kallisto_results"

sample_id <- dir(file.path(base_dir,"results"))

stephenturner

stephenturner

danielecook

# ~/.bashrc: executed by bash(1) for non-login shells.
# see /usr/share/doc/bash/examples/startup-files (in the package bash-doc)
# for examples

function bam_chromosomes() {
    # Fetch chromosomes from a bam file
    samtools view -H $1 | \
    grep -Po 'SN:(.*)\t' | \
    cut -c 4-1000
}

danielecook

/**
 * Returns formatted pubmed citation.
 *
 * @param {id} Pubmed identifier.
 * @return Formatted pubmed citation.
 * @customfunction
 */
function pubmed(id) {
  // Special thanks to http://www.alexhadik.com/blog/2014/6/12/create-pubmed-citations-automatically-using-pubmed-api
  var content =  UrlFetchApp.fetch("http://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?db=pubmed&id=" + id + "&retmode=json")

jroetman

D3 V4.

Hit the pull data button to pull in the testData.json file.

Drag a rectangle around an area of interest to zoom in.

If anyone is interested in a more general version (to take in custom data), or would like me to correct something, leave a comment on the gist.

Update Dec 29th 2017

• Mashed things together to make it work with v4

slowkow

#!/usr/bin/env bash
# bigWigRegions
# Kamil Slowikowski
#
# Depends on bigWigToBedGraph: http://hgdownload.cse.ucsc.edu/admin/exe/

if [[ $# -ne 2 ]]; then
    echo "bigWigRegions - Print bigWig data for each region in a bed file."
    echo -e "usage:\n   bigWigRegions in.bigWig in.bed > out.bedGraph"
    echo "   bigWigRegions in.bigWig <(zcat in.bed.gz) > out.bedGraph"

mblondel

"""
Multiclass SVMs (Crammer-Singer formulation).

A pure Python re-implementation of:

Large-scale Multiclass Support Vector Machine Training via Euclidean Projection onto the Simplex.
Mathieu Blondel, Akinori Fujino, and Naonori Ueda.
ICPR 2014.
http://www.mblondel.org/publications/mblondel-icpr2014.pdf
"""

sterding

## data input (number of reads mapped to each category)
total=100
rRNA=5 # mapped to nuclear rRNA regions
mtRNA=7  # mapped to mitochondria genome
# for the rest of above, then we divide into different category, like http://www.biomedcentral.com/1741-7007/8/149 did.
intergenic=48 
introns=12
exons=30
upstream=3
downstream=6