From DNAnexus R&D: a scalable datastore for population genome sequencing, with on-demand joint genotyping. (GL, genotype likelihood)

This is an early-stage R&D project we're developing openly. The code doesn't yet do anything useful! There's a wiki project roadmap, which should be read in the spirit of "plans are worthless, but planning is indispensable."

First install gcc 4.9 or higher, cmake libjemalloc-dev libboost-dev libzip-dev libsnappy-dev liblz4-dev libbz2-dev python-pyvcf. Then:

cmake -Dtest=ON . && make && ./unit_tests

Other dependencies (should be set up automatically by CMake):

• htslib
• rocksdb
• yaml-cpp
• CTPL
• fcmm
• Catch test framework
• Capnproto efficient serialization

Evolving developer documentation can be found on the project github page.

• C++14 - take advantage of the goodies
• Use smart pointers to avoid passing resources needing manual deallocation across function/class boundaries
• Prefer references over pointers when they shouldn't be null nor change ever.
• Avoid exceptions; prefer returning a Status, defined early in types.h
• nb the frequently-used convenience macro S() defined just below Status
• Avoid public constructors with nontrivial bodies; prefer static initializer function returning Status
• Avoid elaborate templated class hierarchies

The code has some hooks for performance profiling using perf and FlameGraph.

To profile performance within the DNAnexus applet run the applet as usual plus -i enable_perf=true. This produces an output file genotype.stacks containing sampling observation counts for common call stacks. To generate an SVG visualization with FlameGraph:

git clone https://github.com/brendangregg/FlameGraph
FlameGraph/flamegraph.pl < genotype.stacks > genotype.svg