Kallisto and Sleuth¶

Kallisto: https://liorpachter.wordpress.com/2015/05/10/near-optimal-rna-seq-quantification-with-kallisto/ and http://pachterlab.github.io/kallisto/starting.html

Sleuth: https://liorpachter.wordpress.com/2015/08/17/a-sleuth-for-rna-seq/

Step 1: Launch and AMI. For this exercise, we will use a c4.2xlarge We need to mount snap-9b14b2f3 This has to be minimum of 100Gb and mounted at /dev/xvdf

ssh -i ~/Downloads/?????.pem ubuntu@ec2-???-???-???-???.compute-1.amazonaws.com

Update Software

sudo apt-get update

Install updates

sudo apt-get -y upgrade

Install other software Note that you can install a large amount of software from the Ubuntu “App Store” using a single command. Some of this software we will not use for this tutorial, but...

sudo apt-get -y install build-essential tmux git gcc make cmake g++ python-dev libhdf5-dev \
unzip default-jre libcurl4-openssl-dev libxml2-dev libssl-dev zlib1g-dev python-pip samtools bowtie ncbi-blast+

Mount hard drive The EBS volume we asked for is not automatically mounted - we need to do that.

sudo mount /dev/xvdf /mnt
sudo chown -R ubuntu:ubuntu /mnt
df -h

INSTALL KALLISTO

cd $HOME
git clone https://github.com/pachterlab/kallisto.git
cd kallisto/ && mkdir build
cd build
cmake ..
make
sudo make install

RUN KALLISTO: Kallisto maps to a refernece transcriptome. See https://twitter.com/PeroMHC/status/633621603759165440 and discussion.

mkdir -p /mnt/kallisto/results/ && cd /mnt/kallisto
tmux new -s kallisto

curl -LO ftp://ftp.ensembl.org/pub/release-75/fasta/drosophila_melanogaster/cdna/Drosophila_melanogaster.BDGP5.75.cdna.all.fa.gz

kallisto index -i dros Drosophila_melanogaster.BDGP5.75.cdna.all.fa.gz


samples[1]=ORE_wt_rep1
samples[2]=ORE_wt_rep2
samples[3]=ORE_sdE3_rep1
samples[4]=ORE_sdE3_rep2
samples[5]=SAM_wt_rep1
samples[6]=SAM_wt_rep2
samples[7]=SAM_sdE3_rep1
samples[8]=SAM_sdE3_rep2
samples[9]=HYB_wt_rep1
samples[10]=HYB_wt_rep2
samples[11]=HYB_sdE3_rep1
samples[12]=HYB_sdE3_rep2


for i in 1 2 3 4 5 6 7 8 9 10 11 12
do
    sample=${samples[${i}]}
    mkdir -p results/${sample}/kallisto
    kallisto quant -i dros --threads=4 --bootstrap-samples=100 \
    --output-dir=results/${sample}/kallisto \
    /mnt/drosophila/cleaned_reads/${sample}_1.fastq \
    /mnt/drosophila/cleaned_reads/${sample}_2.fastq
done

Download data from EC2 to laptop: Make directory on your laptop.. mkdir ~/Downloads/sleuth/ for the MAC people.

scp -r -i your.pem ubuntu@ec2-xx-x-xxx-xxx.compute-1.amazonaws.com:/mnt/kallisto/results ~/Downloads/sleuth/

SETUP EXPERIMENT DETAILS

nano ~/Downloads/kallisto

#paste in this stuff

name reads condition wt
HYB_sdE3_rep1 1471455 HYB no
HYB_sdE3_rep2 2645196 HYB no
HYB_wt_rep1 2309621 HYB yes
HYB_wt_rep2 2060634 HYB yes
SAM_sdE3_rep1 3181035 SAM no
SAM_sdE3_rep2 2209716 SAM no
SAM_wt_rep1 1992638 SAM yes
SAM_wt_rep2 1989071 SAM yes
ORE_sdE3_rep1 2627739 ORE no
ORE_sdE3_rep2 2418833 ORE no
ORE_wt_rep1 2250607 ORE yes
ORE_wt_rep2 3313590 ORE yes

LAUNCH SLEUTH

#to Launch into RStudio
source("http://bioconductor.org/biocLite.R")
biocLite("rhdf5")
biocLite("biomaRt")
install.packages('devtools')
devtools::install_github('pachterlab/sleuth')
library("sleuth")

#Change project dir in R

base_dir <- "~/Downloads/sleuth"
sample_id <- dir(file.path(base_dir,"results"))
kal_dirs <- sapply(sample_id, function(id) file.path(base_dir, "results", id, "kallisto"))
s2c <- read.table(file.path(base_dir,"experiment.info"), header = TRUE, stringsAsFactors=FALSE)
s2c <- dplyr::select(s2c, sample = name, reads, condition, wt)
so <- sleuth_prep(kal_dirs, s2c, ~ wt)
so <- sleuth_fit(so)
so <- sleuth_test(so, which_beta = 'wtyes')

mart <- biomaRt::useMart(biomart = "ensembl", dataset = "dmelanogaster_gene_ensembl")
t2g <- biomaRt::getBM(attributes = c("ensembl_transcript_id", "ensembl_gene_id",
    "external_gene_name"), mart = mart)
t2g <- dplyr::rename(t2g, target_id = ensembl_transcript_id,
     ens_gene = ensembl_gene_id, ext_gene = external_gene_name)
so <- sleuth_prep(kal_dirs, s2c, ~ wt, target_mapping = t2g)
so <- sleuth_fit(so)
so <- sleuth_test(so, which_beta = 'wtyes')
sleuth_live(so)

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