vd4mmind

bioinformatics-for-beginners

MOOC:

Free

• https://www.rstudio.com/online-learning/
• Introductory classes at https://rafalab.github.io/pages/teaching.html

Paid: DataCamp (R or Python, not both to begin with)

vd4mmind

# ipak function: install and load multiple R packages.
# check to see if packages are installed. Install them if they are not, then load them into the R session.

ipak <- function(pkg){
    new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])]
    if (length(new.pkg)) 
        install.packages(new.pkg, dependencies = TRUE)
    sapply(pkg, require, character.only = TRUE)
}

vd4mmind

vd4mmind

Tool	Use	Link
Chip enrich	Functional enrichment of ChIP enriched regions	http://chip-enrich.med.umich.edu/chipMain.jsp
REDItools	RNA editing detection	https://www.ncbi.nlm.nih.gov/pubmed/23742983
Screw	Single-cell epigenomics workflow	https://github.com/Epigenomics-Screw/Screw
Google classroom	Handy teaching tool	https://classroom.google.com/h
Piazza QA platform	Free Q&A platform	https://piazza.com/
Latex slides	Easy to edit slides (best for teaching)	https://www.overleaf.com/gallery/tagged/presentation#.WXMl9tOGP6Y
Moodle	Create your own course	https://moodle.org/?lang=nn
MultiQC	NGS data QC tool	http://multiqc.info/

vd4mmind

# install the Rsamtools package if necessary
source("http://bioconductor.org/biocLite.R")
biocLite("Rsamtools")
 
# load the library
library(Rsamtools)

# specify the bam file you want to import
bamFile <- "test.bam"

vd4mmind

#how many regions to sample?
number <- 50000

#how many bp to add to start
span <- 4

#some necessary packages
#install if necessary
source("http://bioconductor.org/biocLite.R")
biocLite("BSgenome")

vd4mmind

Differential expression analysis with edgeR

This is a tutorial I have presented for the class Genomics and Systems Biology at the University of Chicago. In this course the students learn about study design, normalization, and statistical testing for genomic studies. This is meant to introduce them to how these ideas are implemented in practice. The specific example is a differential expression analysis with edgeR starting with a table of counts and ending with a list of differentially expressed genes.

Past versions:

• Tuesday, April 26, 2016

vd4mmind

## RNA-seq analysis with DESeq2
## Stephen Turner, @genetics_blog

# RNA-seq data from GSE52202
# http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse52202. All patients with
# ALS, 4 with C9 expansion ("exp"), 4 controls without expansion ("ctl")

# Import & pre-process ----------------------------------------------------

# Import data from featureCounts

vd4mmind

#! /usr/bin/perl

use strict;
use warnings;
use FileHandle;

#arg 0 - copy number calls produced by varscan "copyCaller" step
#arg 1 - segments of LOH, which give a reliable centering estimate (optional)

if(!$ARGV[0])

vd4mmind

# If you are trying to view VCF 4.2 files in IGV - you may run into issues. This function might help you.
# This script will:
# 1. Rename the file as version 4.1
# 2. Replace parentheses in the INFO lines (IGV doesn't like these!)

function vcf_downgrade() {
  outfile=${1/.bcf/}
  outfile=${outfile/.gz/}
  outfile=${outfile/.vcf/}
  bcftools view --max-alleles 2 -O v $1 | \