Description:
vdw 0.4.1
# Varify Data Warehouse Development Guide[](https://travis-ci.org/cbmi/varify-data-warehouse) [](https://coveralls.io/r/cbmi/varify-data-warehouse)## Need some help?Join our chat room and speak with our dev team: http://www.hipchat.com/gZcKr0p3y## DependenciesListed are the download links to each dependency, however most OSes have apackage manager or binaries that can be easily installed. Most of the belowlinks describe alternate download and install methods.On Mac OS X, [Homebrew](http://mxcl.github.com/homebrew/) is the recommendedway to install most of these libraries.- [Python 2.6+](http://python.org/download/releases/2.6.9/)- [Redis 2.6+](http://redis.io/download)- [PostgreSQL 9.2+](http://www.postgresql.org/download/)- [Memcached](http://memcached.org)## Setup & InstallDistribute, Pip and virtualenv are required. To check if you have them:```bashwhich pip easy_install virtualenv```If nothing prints out, install the libraries corresponding to the commandsbelow:_Watch out for sudo! The root user `$PATH` most likely does not include`/usr/local/bin`. If you did not install Python through your distro's packagemanager, use the absolute path to the new Python binary to prevent installingthe above libraries with the wrong version (like Python 2.4 on CentOS 5),e.g. `/usr/local/bin/python2.7`._```bashcurl http://python-distribute.org/distribute_setup.py | pythoncurl https://raw.github.com/pypa/pip/master/contrib/get-pip.py | pythonpip install virtualenv```Create your virtualenv:```bashvirtualenv vdw-envcd vdw-env. bin/activate```Clone the repo:```bashgit clone https://github.com/cbmi/varify-data-warehouse.gitcd varify-data-warehouse```Install the requirements:```bashpip install -r requirements.txt```Under Mac OS X 10.8 or later, with XCode 5.1 or later, the following may be necessary in order for pip to install requirements:```bashexport CFLAGS=-Qunused-arguments```[Start the postgres server](http://www.postgresql.org/docs/9.2/static/server-start.html). This *may* look something like:```initdb /usr/local/var/postgres -E utf8pg_ctl -D /usr/local/var/postgres -l /usr/local/var/postgres/server.log start```Create the varify database, you might first want to make sure you are a user```createuser --user postgres -s -r yourusernamecreatedb varify```Start memcached```bashmemcached -d```Start redis```redis-server /usr/local/etc/redis.conf```If you are on a Mac, you will need to start postfix to allow SMTP:```sudo postfix start```Initialize the Django and Varify schemas```./bin/manage.py syncdb./bin/manage.py migrate```Then either start the built-in Django server:```bash./bin/manage.py runserver```or run a `uwsgi` process:```bashuwsgi --ini server/uwsgi/local.ini --protocol http --socket 127.0.0.1:8000 --check-static _site```## Local Settings`local_settings.py` is intentionally not versioned (via `.gitignore`). It shouldcontain any environment-specific settings and/or sensitive settings such aspasswords, the `SECRET_KEY` and other information that should not be in versioncontrol. Defining `local_settings.py` is not mandatory but will warn if it doesnot exist.## PipelineThe following describes the steps to execute the loading pipeline, the performance of the pipeline, and the process behind it.#### NOTE: All VCF files being loaded into Varify must be annotated with the [CBMi fork of SnpEff](https://github.com/CBMi-BiG/snpEff). The key difference is that the CBMi fork attempts to generate valid HGVS for insertions and deletions, including those which require "walking and rolling" to identify the correct indel frame while the standard SnpEff version only contains a partial implementation of HGVS notation [as noted here](http://snpeff.sourceforge.net/SnpEff_manual.html#filters).### Retrieving Test DataWe have provided a [set of test data](https://github.com/cbmi/varify-demo-data) to use to test the load pipeline or use as sample data when first standing up your Varify instance. To use the test data, run the commands below.```bashwget https://github.com/cbmi/varify-demo-data/archive/0.1.tar.gz -O varify-demo-data-0.1.tar.gztar -zxf varify-demo-data-0.1.tar.gzgunzip varify-demo-data-0.1/CEU.trio.2010_03.genotypes.annotated.vcf.gz```At this point, the VCF and MANIFEST in the `varify-demo-data-0.1` directory are ready for loading in the pipeline. You can use the `varify-demo-data-0.1` directory as the argument to the `samples queue` command in the _Queue Samples_ step below if you want to just load this test data.#### Tmux (optional)Since the pipeline can take a while to load large collections(see Performance section below), you may want to consider following the Tmux steps to attach/detach to/from the load process.[Tmux](http://robots.thoughtbot.com/post/2641409235/a-tmux-crash-course) is like [screen](http://www.gnu.org/software/screen/), just newer. It is useful for detaching/reattaching sessions with long running processes.**New Session**```bashtmux```**Existing Session**```bashtmux attach -t 0 # first session```### Activate Environment```bashsource bin/activate```#### Define RQ_QUEUESFor this example, we will assume you have `redis-server` running on `localhost:6379` against the database with index 0. If you have redis running elsewhere simply update the settings below with the address info and DB you wish to use. Open your `local_settings.py` file and add the following setting:```pythonRQ_QUEUES = { 'default': { 'HOST': 'localhost', 'PORT': 6379, 'DB': 0, }, 'samples': { 'HOST': 'localhost', 'PORT': 6379, 'DB': 0, }, 'variants': { 'HOST': 'localhost', 'PORT': 6379, 'DB': 0, },}```#### Queue SamplesOptionally specify a directory, otherwise it will recursively scan all directories defined in the `VARIFY_SAMPLE_DIRS` setting in the Varify project.```bash./bin/manage.py samples queue [directory]```#### Kick Off WorkersYou can technically start as many of each type for loading data in parallel, but this may cause undesired database contention which could actually slow down the loading process. A single worker for `variants` is generally preferred and two or three are suitable for the `default` type.```bash./bin/manage.py rqworker variants &./bin/manage.py rqworker default &```Note, these workers will run forever, if there is only a single sample being loaded, the `--burst` argument can be used to terminate the worker when there are no more items left in the queue.#### Monitor WorkersYou can monitor the workers and the queues using the `rq-dashboard` or `rqinfo`. Information on setting up and using those services can be found [here](http://python-rq.org/docs/monitoring/).#### Post-LoadAfter the batch of samples have been loaded, two more commands need to be executed to update the annotations and cohort frequencies. These are performed _post-load_ for performance reasons.```bash./bin/manage.py variants load --evs --1000g --sift --polyphen2 > variants.load.txt 2>&1 &./bin/manage.py samples allele-freqs > samples.allele-freqs.txt 2>&1 &```### Performance- File size: 610 MB- Variant count: 1,794,055#### BaselineIteration over flat file (no parsing) with batch counting (every 1000)- Time: 80 seconds- Memory: 0#### Baseline VCFIteration over VCF parsed file using PyVCF- Time: 41 minutes (extrapolated)- Memory: 246 KB### Parallelized Queue/Worker Process#### Summary of Workflow1. Fill Queue2. Spawn Worker(s)3. Consume Job(s) - Validate Input - (work) - Validate Output - Commit#### Parallelism ConstraintsThe COPY command is a single statement which means the data being loaded isall or nothing. If multiple samples are being loaded in parallel, it is likelythey will have overlapping variants.To prevent integrity errors, workers will need to consult one or morecentralized caches to check if the current variant has been _addressed_already. If this is the case, the variant will be skipped by the worker.This incurs a second issue in that downstream jobs depend on the existence ofsome data that does not yet exist because another worker has not yet committedits data. In this case, non-matches will be queued up in the `deferred` queuethat can be run at a later time, after the `default` queue is empty or inparallel with the `default` queue.
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