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CNV_detection/data
DataVis
RNAseq-R @ c0ce27f
cruk-autumn-school-2017 @ 5262d58
differential.ChIP-seq.data
gene_annotation
hic_workshop_2017
intro
microbial-genomics
molecular_data_integration
rna_structure_probing
scRNA.seq.course @ 458088a
.bashrc
.gitignore
.gitmodules
DifferentialExpression
LICENSE
README.md
lecture_notes.pdf

README.md

NGSchool2017 materials

Materials prepared by the instructors of the #NGSchool2017.

You can sync all data using (don't do it during workshops!):

rsync -avz --exclude="*.git/" USERNAME@192.168.1.111:/ngschool/2017 ~/ngschool
# and type your password

Table of Contents

Dependencies

In order to run workshop examples in your own laptop, you'll need to install all below prerequesities.
Note, the installation instructions are meant for Ubuntu 16.04. Everything should be done in below order, it may take a few hours (especially compilation of R packages is lengthy...) and around 15-20GB of hard-drive space.

bioconda & docker

# install conda ie. in /ngschool/src/miniconda2
wget https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh
chmod +x Miniconda2-latest-Linux-x86_64.sh
./Miniconda2-latest-Linux-x86_64.sh

# configure bioconda channels
(conda config --add channels r)
conda config --add channels defaults
conda config --add channels conda-forge
conda config --add channels bioconda

# install dependencies - AVOID INSTALLING r-base, as it'll mess up with native R installation
conda install bwa htslib samtools spades quast trimmomatic fastqc gmap blat blast qualimap star busco tophat bowtie2 gawk igv seqtk glimmer exonerate muscle fasttree mcl trimal augustus homer bedtools bbmap gffutils

# non-bioconda
sudo apt install docker.io varna blast2 macs
sudo groupadd docker
sudo usermod -aG docker $USER

R, Bioconductor and other R packages

# R - need to add R repo first
echo "deb https://www.stats.bris.ac.uk/R/bin/linux/ubuntu $(lsb_release -c | xargs | cut -f2 -d' ')/" | sudo tee -a /etc/apt/sources.list
sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E084DAB9
sudo apt-get update && sudo apt upgrade && sudo apt install libcurl4-openssl-dev libxml2-dev libcairo2-dev libxt-dev libssl-dev
sudo apt install r-base r-base-dev

# install R packages for all users
sudo R | tee -a /tmp/r.log
install.packages("plotly"); install.packages("ggplot2")
source("https://bioconductor.org/biocLite.R") # bioconductor
biocLite('BiocInstaller'); biocLite("ATACseqQC"); biocLite("Diffbifnd"); biocLite("affyPLM"); biocLite("arrayMvout"); biocLite("arrayQualityMetrics"); biocLite("gcrma"); biocLite("hgu133acdf"); biocLite("hgu133a.db"); biocLite("hgu133plus2.db"); biocLite("simpleaffy")
biocLite("RNAprobR"); biocLite("affy"); biocLite("biomaRt"); biocLite("geneplotter"); biocLite("gplots"); biocLite("limma"); biocLite("sva"); biocLite("Rsamtools"); biocLite("ChIPseeker"); 
biocLite("BSgenome.Hsapiens.UCSC.hg19") # large

## scRNA-seq - you may use it through docker image (but it's huuuuuge!)
install.packages("mvoutlier"); install.packages("statmod"); install.packages("pheatmap"); install.packages("ROCR")
source("https://bioconductor.org/biocLite.R")
biocLite('scater'); biocLite('scran'); biocLite("RUVSeq"); biocLite("pcaMethods"); biocLite("SC3")
biocLite("M3Drop"); biocLite("TSCAN"); biocLite("monocle"); biocLite("destiny");
biocLite("edgeR"); biocLite("DESeq2"); biocLite("MAST"); biocLite("MultiAssayExperiment"); biocLite("SummarizedExperiment")
install.packages("devtools");
devtools::install_github("hemberg-lab/scRNA.seq.funcs"); devtools::install_github("JustinaZ/pcaReduce"); devtools::install_github('satijalab/seurat')
devtools::install_github('jw156605/SLICER'); devtools::install_github("hms-dbmi/scde", build_vignettes = FALSE)

8/09/2017 UPDATE

sudo R | tee -a /tmp/r.log # tgambin & kkedzierska
install.packages("data.table");
source("https://bioconductor.org/biocLite.R")
biocLite('parallel'); biocLite('RCurl'); biocLite('gdata'); biocLite('Hmisc'); biocLite('matrixStats'); biocLite('DNAcopy'); biocLite('GenomicRanges'); biocLite('Rsubread'); biocLite('WES.1KG.WUGSC'); biocLite('CODEX'); biocLite("ChIPseeker");

10/09/2017 UPDATE

sudo R | tee -a /tmp/r.log # Differential chip-seq analysis
source("https://bioconductor.org/biocLite.R")
biocLite("csaw"); biocLite("GenomicRanges"); biocLite("GenomicAlignments"); biocLite("GenomicFeatures"); biocLite("edgeR"); biocLite("TxDb.Mmusculus.UCSC.mm10.knownGene"); biocLite("org.Mm.eg.db")
install.packages("ProjectTemplate")

Manual installation

Running exercises

Working in your own laptop

Copy workshop materials locally ie. rsync -av --exclude="*.git/" /media/$USER/USB_MOUNT_DIR ~/ngschool/2017, enter NGSchoool directory cd ~/ngschool/2017 and you are ready to work. Make sure, you have installed all prerequesities before!

Working in remote NGSchool server

Login to the server with your credentials, sync workshop materials to your home directory rsync -av --exclude '*.git/' /ngschool/2017 ~/ngschool, enter your personal NGSchoool directory cd ~/ngschool/2017 and you are ready to work.

Make sure to import local variable in each new window

# NOTE: you may need to change `/ngschool/2017` directory
# if you cloned the repository to another location
source /ngschool/2017/.bashrc

Working in VirtualBox

First, get VM image and create VM in VirtualBox using this image. Then run VM (u: ngschool p: ngschool), enter NGSchoool directory cd /ngschool/2017 and you are ready to work.

Cloning the repository

This has to be done only if you wish to explore materials before the school. Otherwise, ignore below.
To clone repo, use git clone --recursive https://github.com/NGSchoolEU/2017.git
Below, we're providing links to data not included in this repository.

Materials not included in github repo

You can get below using wget -nc -r -np HTTP

Note, you can also sync all data using:

rsync -avz --exclude="*.git/" USERNAME@192.168.1.111:/ngschool/2017 ~/ngschool
# and type your password

Introduction

All exercises are in: http://compbio.fmph.uniba.sk/temp/ngschool2017/

De novo assembly

Hi-C

Get ONE of below files:

Microbial genomics

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