OmicsPipe on the Amazon Cloud (AWS EC2) Tutorial¶

OmicsPipe on AWS uses a custom StarCluster image, created with docker.io (which installs docker.io, environment-modules, and easybuild on an AWS EC2 cluster). All you have to do is get the docker image, upload your data, launch the Amazon cluster and run a single command to analyze all of your data according to published, best-practice methods.

Step 1: Create an AWS Account¶

Create an AWS account by following the instructions at Amazon-AWS
Note your AWS ACCESS KEY ID, AWS SECRET ACCESS KEY and AWS USER ID

Step 2 (Mac or Linux): Install StarCluster and download config/plugins¶

Install StarCluster on your machine following the StarCluster instructions
Download the template Omics Pipe StarCluster configuration file (config) and three plugin files (sge.py, sgeconfig.py, omicspipe_config_prebuilt.py) from Omics Pipe Bitbucket
Move downloaded config file to ~/.starcluster/config
Move downloaded plugin files to the ~/.starcluster/plugins/ folder.
Go on to configure StarCluster by following directions below in Step 3.

Step 2 (Windows): Load the the OmicsPipe on AWS docker image on your machine¶

Download docker.io following the instructions for your operating system at Get-Docker

From inside the Docker environment, run the command:

docker run -i -t omicspipe/aws_readymade /bin/bash

Note

If you want to share a file from your local computer with the docker container, follow the instructions for Docker Folder Sharing, put your desired file within the shared folder and run the command below (this is recommended for saving your /.starcluster/config file from the next step:

docker run -it --volumes-from NameofSharedDataFolder omicspipe/aws_readymade /bin/bash

If you are on a local Ubuntu installation, skip this step and install the StarCluster client directly.
If you are using Windows, it might be necessary to update your BIOS to enable virtualization before installing Docker

Step 3: Configure StarCluster¶

After running the omicspipe/aws_readymade Docker container, run the command below to edit the StarCluster configuration file:
```
    nano ~/.starcluster/config

Or if you prefer vim::

    vim ~/.starcluster/config
```
Enter your “AWS ACCESS KEY ID”, “AWS SECRET ACCESS KEY”, and “AWS USER ID”
Change the AWS REGION NAME and AWS REGION HOST variables if you do not live in the AWS us-west region to the appropriate region AWS Regions.
Select your desired pre-configured cluster by editing the “DEFAULT_TEMPLATE” variable or creating a custom cluster. The default is a test cluster with 5 c3.large nodes.
Save the edited file (Instructions for Nano and for Vim)

Create your starcluster SSH key by running the command:

starcluster createkey omicspipe -o ~/.ssh/omicspipe.rsa

To remove a key from the AWS registry, run the command:
```
starcluster removekey omicspipe
```
For more information on editing the StarCluster configuration file, see the StarCluster website.

Step 4: Create AWS Volumes¶

Create AWS volumes to store the raw data and results of your analyses. From within the Docker environment, run:

starcluster createvolume --name=data -i ami-52112317 -d -s <volume size in GB> us-west-1a

starcluster createvolume --name=results -i ami-52112317 -d -s <volume size in GB> us-west-1a

Specify the <volume size in GB> as a number large enough to accomodate all of your raw data and ~4x that size for your results folder
Change us-west-1b to your region as described in AWS Regions.

Make a volume from the provided snapshot of reference databases (currently only supports H. sapiens)

Go to the AWS-Console

Click on the EC2 option

Click on Volumes

Click on “Create Volume”

Set availability zone

In Snapshot ID search for “omicspipe_db” and click on the resulting Snapshot ID

Click Create

From the Volumes tab, note the “VOLUME_ID” of the database snapshot

Edit your StarCluster configuration file to add your volume IDs. Run the command below and edit the VOLUME_ID variables for data, results, and database:

nano ~/.starcluster/config

Edit the fields below:

[volume results]
VOLUME_ID =
MOUNT_PATH = /data/results

[volume data]
VOLUME_ID =
MOUNT_PATH = /data/data

[volume database]
VOLUME_ID =
MOUNT_PATH = /data/database

Save your StarCluster configuration file to ~/.starcluster/config

Step 5: Launch the Cluster¶

From the Docker container, run the command below to start a new cluster with the name “mypipe”:
```
starcluster start mypipe
```
SSH into the cluster by running the command below:
```
starcluster sshmaster mypipe
```

Step 6: Upload data to the cluster¶

Now that you are in your cluster, you can use it like any other cluster. Before running omics pipe on your own data (you can skip this step if you are running the test data, you will want to upload your data, unless it is already present in your attached data volume. There are several options to upload your data:

Upload data from your local machine or cluster using StarCluster put:
```
starcluster put mypipe <myfile> /data/raw
```

Retrieve a file from an FTP server:

scp <localfile>username@tohostname:<remotefile>

Get a file from an S3 bucket with S3cmd:

s3cmd get s3://BUCKET/OBJECT LOCAL_FILE

Use Webmin to transfer files from your local system to the cluster (recommended for small files only, like parameter files).
- In the AWS Management Console go to “Security Groups”
- Select the “StarCluster-0_95_5” group associated with your cluster’s name
- On the Inbound tab click on “Edit”
- Click on “Add Rule” and a new “Custom TCP Rule” will apear. On “Port Range” enter “10000” and on “Source” select “My IP”
- Hit “Save”
- Selct Instances in the AWS managemnt console and note the “Public IP” of your instance
- In a Web browser, enter https://the_public_ip:10000. Type in the Login info when prompted: user: root password: sulab
- This will take a few seconds to load, and once it does, you can navigate your cluster’s file structure with the tabs on the left
- To upload a file from your local file system, click “upload” and specify the directory /data/data to upload your data.

Step 7: Run the test pipelines¶

Once you have successfully started the cluster, you may run Omics Pipe with the following commands for the different pipelines. *Note: Small .fastq files are provided on the instance for the tests below to demonstrate the functionality of the pipelines, but they may not generate meaningful results. Larger test files can be uploaded to the cluster by following the instructions in the documentation above.

RNA-seq Count Based Pipeline

omics_pipe RNAseq_count_based /root/src/omics-pipe/tests/test_params_RNAseq_counts_AWS.yaml

RNA-seq Tuxedo Pipeline

omics_pipe RNAseq_Tuxedo /root/src/omics-pipe/tests/test_params_RNAseq_Tuxedo_AWS.yaml

Whole Exome Sequencing:

omics_pipe WES_GATK /root/src/omics-pipe/tests/test_params_WES_GATK_AWS.yaml

ChIP-seq Homer

omics_pipe ChIPseq_HOMER /root/src/omics-pipe/tests/test_params_ChIPseq_HOMER_AWS.yaml

Step 8: Run the pipelines with your own data¶

Tutorial

Installing extra software¶

Both the GATK and MuTect software are used by OmicsPipe, but they require licenses from The Broad Institute and cannot be distributed with the OmicsPipe software. GATK and MuTect are free to download after accepting the license agreement.

To install GATK:

Download GATK
Upload the GenomeAnalysisTK.jar file to the /root/.local/easybuild/software/gatk/3.2-2 using either Webmin or StarCluster put

Make the jar file executable by running the command:

chmod +x /root/.local/easybuild/software/gatk/3.2-2/GenomeAnalysisTK.jar

To install MuTect:

Download MuTect
Upload the muTect-1.1.4.jar file to the /root/.local/easybuild/software/mutect/1.1.4 using either Webmin or StarCluster put

Make the jar file executable by running the command:

chmod +x /root/.local/easybuild/software/mutect/1.1.4/muTect-1.1.4.jar

Adding software that OmicsPipe was not built with might require a little more configuration, but OmicsPipe is designed as a foundation to which new software can be added. New software can obviously be added in any manner that the user prefers, but to follow the structure that was used to build OmicsPipe, please refer to the “custombuild” scripts.

Important

If you configure software that you think extends the functionality of OmicsPipe, please create a pull request on our Bitbucket page.

To build your own docker image¶

Download docker.io following the instructions at Get-Docker

Run the command:

docker build -t <Repository Name> https://bitbucket.org/sulab/omics_pipe/downloads/Dockerfile_AWS_prebuiltAMI_public

This will store the dockercluster image in the Repository Name of your choice.

There is also an AWS_custombuild Dockerfile, which can be used to build an Amazon Machine Image from scratch

Add storage > 1TB to the cluster using LVM (for advanced users)¶

Within StarCluster create x new volumes by running:

nvolumes=2 #number of volumes
vsize=1000 #in gb
instance=`curl -s http://169.254.169.254/latest/meta-data/instance-id`
akey=<AWS KEY>
skey=<AWS SECRET KEY>
region=us-west-1
zone=us-west-1a

for x in $(seq 1 $nvolumes)
do
  ec2-create-volume \
      --aws-access-key $akey \
      --aws-secret-key $skey \
      --size $vsize \
      --region $region \
      --availability-zone $zone
done > /tmp/vols.txt

Attach the volumes to the head node:

i=0
for vol in $(awk '{print $2}' /tmp/vols.txt)
do
      i=$(( i + 1 ))
      ec2-attach-volume $vol \
      -O $akey \
      -W $skey \
      -i $instance \
      --region $region \
      -d /dev/sdh${i}
done > /tmp/attach.txt

Mark the EBS volumes as physical volumes:

for i in $(find /dev/xvdh*)
do
     pvcreate $i
done

Create a volume group:
```
vgcreate vg /dev/xvdh*
```
Create a logical volume:
```
lvcreate -l100%VG -n lv vg
```
Create the file system:
```
mkfs -t xfs /dev/vg/lv
```

Mount the file system:
```
mount /dev/vg/lv /data/data_large
```

Create mount point and mount the device:

mkdir /data/data_large
mount /dev/md0 /data/data_large

Add new mountpoint to /etc/exports:

for x in $(qconf -sh | tail -n +2)
do
      echo '/data/data_large' ${x}'(async,no_root_squash,no_subtree_check,rw)' >> /etc/exports
done

Reload /etc/exports:
```
exportfs -a
```

Mount the new folder on all nodes:

for x in $(qconf -sh | tail -n +2)
do
      ssh $x 'mkdir /data/data_large'
      ssh $x 'mount -t nfs master:/data/data_large /data/data_large'
done

How to increase volume size?

Create and attach EBS volumes as described in steps 1. & 2. and then create the additional physical volumes:
```
for i in $(cat /tmp/attach.txt  | cut -f 4 | sed 's/[^0-9]*//g')
do
       pvcreate /dev/xvdh${i}
done
```

Add new volumes to the volume group:

for i in $(cat /tmp/attach.txt  | cut -f 4 | sed 's/[^0-9]*//g')
do
       vgextend vg /dev/xvdh${i}
done

lvextend -l100%VG /dev/mapper/vg-lv

Grow the file system to the new size:
```
xfs_growfs /data/data_large
```

Add storage > 1TB to the cluster using RAID 0 (for advanced users)¶