Biowulf High Performance Computing at the NIH
Hail on Biowulf

Hail is an open-source, scalable framework for exploring and analyzing genomic data. See https://hail.is/docs/0.2/index.html for more information.

Documentation
Important Notes

Interactive job
Interactive jobs should be used for debugging, graphics, or applications that cannot be run as batch jobs.

Allocate an interactive session and run the program. Sample session:

[user@biowulf]$ sinteractive -c 16 --mem 40g
salloc.exe: Pending job allocation 46116226
salloc.exe: job 46116226 queued and waiting for resources
salloc.exe: job 46116226 has been allocated resources
salloc.exe: Granted job allocation 46116226
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3144 are ready for job

[user@cn3144 ]$ module load hail
[+] Loading hail  0.2.3 on cn3344 
[+] Loading singularity  on cn3344 

[user@cn3144]$ wget ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/release/\
20100804/ALL.2of4intersection.20100804.sites.vcf.gz
[user@cn3144 ]$ ipython
Python 3.6.7 (default, Oct 25 2018, 09:16:13) 
Type 'copyright', 'credits' or 'license' for more information
IPython 7.1.1 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import hail as hl

In [2]: hl.init()                                                                                            
using hail jar at /usr/local/lib/python3.6/dist-packages/hail/hail-all-spark.jar
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Running on Apache Spark version 2.2.2
SparkUI available at http://10.2.9.172:4040
Welcome to
     __  __     <>__
    / /_/ /__  __/ /
   / __  / _ `/ / /
  /_/ /_/\_,_/_/_/   version 0.2-a2eaf89baa0c
LOGGING: writing to /spin1/scratch/teacher/hail-20181129-1008-0.2-a2eaf89baa0c.log

In [4]: hl.import_vcf('ALL.2of4intersection.20100804.sites.vcf.gz',force_bgz=True).write('sample.vds')                                                                                  
[Stage 1:===============================>                          (7 + 6) / 13]2018-11-29 15:10:40 Hail: INFO: Coerced sorted dataset
[Stage 2:===========================================>             (10 + 3) / 13]2018-11-29 15:11:47 Hail: INFO: wrote 25488488 items in 13 partitions to sample.vds

[user@cn3144 ]$ exit
salloc.exe: Relinquishing job allocation 46116226

Run hail with jupyter notebook:

[user@biowulf ]$sinteractive -c 16 --mem 40g --tunnel
salloc.exe: Pending job allocation 46116226
salloc.exe: job 46116226 queued and waiting for resources
salloc.exe: job 46116226 has been allocated resources
salloc.exe: Granted job allocation 46116226
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3144 are ready for job
Created 1 generic SSH tunnel(s) from this compute node to                  
biowulf for your use at port numbers defined                               
in the $PORTn ($PORT1, ...) environment variables.                         
                                                                           
                                                                           
Please create a SSH tunnel from your workstation to these ports on biowulf.
On Linux/MacOS, open a terminal and run:                                   
                                                                           
    ssh  -L 33327:localhost:33327 biowulf.nih.gov                          
                                                                           
For Windows instructions, see https://hpc.nih.gov/docs/tunneling          
[user@cn3144]$ module load hail
[user@cn3144]$ wget ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/release/\
20100804/ALL.2of4intersection.20100804.sites.vcf.gz
[user@cn3144]$ jupyter notebook --ip localhost --port $PORT1 --no-browser
[I 17:11:40.505 NotebookApp] Serving notebooks from local directory
[I 17:11:40.505 NotebookApp] Jupyter Notebook 6.4.10 is running at:
[I 17:11:40.505 NotebookApp] http://localhost:37859/?token=xxxxxxxx
[I 17:11:40.506 NotebookApp]  or http://127.0.0.1:37859/?token=xxxxxxx
[I 17:11:40.506 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 17:11:40.512 NotebookApp]

    To access the notebook, open this file in a browser:
        file:///home/apptest1/.local/share/jupyter/runtime/nbserver-29841-open.html
    Or copy and paste one of these URLs:
        http://localhost:37859/?token=xxxxxxx
     or http://127.0.0.1:37859/?token=xxxxxxx

Then you can open a browser from your computer to connect to the jupyter notebook:

hail_jupyter

Batch job
Most jobs should be run as batch jobs.

Create a python script (e.g. hail-script.py). For example:

import hail as hl
mt = hl.balding_nichols_model(n_populations=3,
                              n_samples=500,
                              n_variants=500_000,
                              n_partitions=32)
mt = mt.annotate_cols(drinks_coffee = hl.rand_bool(0.33))
gwas = hl.linear_regression_rows(y=mt.drinks_coffee,
                                 x=mt.GT.n_alt_alleles(),
                                 covariates=[1.0])
gwas.order_by(gwas.p_value).show(25)

Create a batch input file (e.g. hail.sh). For example:

#!/bin/bash
module load hail
python3 hail-script.py 

Submit this job using the Slurm sbatch command.

sbatch -c 16 --mem 40g hail.sh
Swarm of Jobs
A swarm of jobs is an easy way to submit a set of independent commands requiring identical resources.

Create a swarmfile (e.g. hail.swarm). For example:

python3 hail1.py
python3 hail2.py
python3 hail3.py

Submit this job using the swarm command.

swarm -f hail.swarm -g 30 -t 16 --module hail
where
-g # Number of Gigabytes of memory required for each process (1 line in the swarm command file)
-t # Number of threads/CPUs required for each process (1 line in the swarm command file).
--module hail Loads the hail module for each subjob in the swarm