vg::MCMCGenotyper Class Reference

#include <mcmc_genotyper.hpp>

Public Member Functions
	MCMCGenotyper (SnarlManager &snarls, VG &graph, const int n_iterations, const int seed, const int burn_in, const int frequency)
unique_ptr< PhasedGenome >	run_genotype (const vector< multipath_alignment_t > &reads, const double log_base) const
double	log_target (unique_ptr< PhasedGenome > &phased_genome, const vector< multipath_alignment_t > &reads) const
tuple< int, const Snarl *, vector< NodeTraversal > >	proposal_sample (unique_ptr< PhasedGenome > &current) const
int	generate_discrete_uniform (minstd_rand0 &random_engine, int lower_bound, int upper_bound) const
double	generate_continuous_uniform (const double a, const double b) const
unique_ptr< PhasedGenome >	generate_initial_guess () const
unordered_map< pair< const Snarl *, const Snarl * >, int32_t >	make_snarl_map (const vector< multipath_alignment_t > &reads, PhasedGenome &phased_genome) const
algorithms::Graph	make_snarl_graph (unordered_map< pair< const Snarl *, const Snarl * >, int32_t > map) const
vector< unordered_set< size_t > >	karger_stein (const vector< multipath_alignment_t > &reads, PhasedGenome &genome) const
unordered_set< size_t >	alt_proposal_sample (vector< unordered_set< size_t >> &gamma, PhasedGenome &genome) const

Private Attributes
SnarlManager &	snarls
VG &	graph
const int	n_iterations
const int	seed
const int	burn_in
const int	frequency
minstd_rand0	random_engine

Detailed Description

This class is a genotyper that uses MCMC to find two optimal paths through the graph given a set of aligned reads.

Constructor & Destructor Documentation

MCMCGenotyper()

vg::MCMCGenotyper::MCMCGenotyper	(	SnarlManager &	snarls,
		VG &	graph,
		const int	n_iterations,
		const int	seed,
		const int	burn_in,
		const int	frequency
	)

Member Function Documentation

alt_proposal_sample()

unordered_set< size_t > vg::MCMCGenotyper::alt_proposal_sample	(	vector< unordered_set< size_t >> &	gamma,
		PhasedGenome &	genome
	)		const

generate_continuous_uniform()

double vg::MCMCGenotyper::generate_continuous_uniform	(	const double	a,
		const double	b
	)		const

Given a range [a,b] will return a random number uniformly distributed within that range

generate_discrete_uniform()

int vg::MCMCGenotyper::generate_discrete_uniform	(	minstd_rand0 &	random_engine,
		int	lower_bound,
		int	upper_bound
	)		const

Generates a number randomly using the discrete uniform distribution

generate_initial_guess()

unique_ptr< PhasedGenome > vg::MCMCGenotyper::generate_initial_guess

(

)

const

Generate a PhasedGenome to use as an initial value in M-H Uses the two non-alt paths from the linear reference as haplotypes

karger_stein()

vector< unordered_set< size_t > > vg::MCMCGenotyper::karger_stein	(	const vector< multipath_alignment_t > &	reads,
		PhasedGenome &	genome
	)		const

Make a snarl graph with edge weights scored by how well mapped reads support phasing of snarl Use an alternative proposal distribution using sets generated from karger-stein min cut algorithm to escape bottlenecks leading to rapid convergence

log_target()

double vg::MCMCGenotyper::log_target	(	unique_ptr< PhasedGenome > &	phased_genome,
		const vector< multipath_alignment_t > &	reads
	)		const

Represents the poseterior distribution function returns the posterir probability

make_snarl_graph()

algorithms::Graph vg::MCMCGenotyper::make_snarl_graph

(

unordered_map< pair< const Snarl *, const Snarl * >, int32_t >

map

)

const

Generate a graph using the snarl map

make_snarl_map()

unordered_map< pair< const Snarl *, const Snarl * >, int32_t > vg::MCMCGenotyper::make_snarl_map	(	const vector< multipath_alignment_t > &	reads,
		PhasedGenome &	phased_genome
	)		const

Generate a map from a pair of snarls to an edge weight Uses snarls read API, reads and the optimal_score_on pahsed genome as a scoring scheme for the edge weight overlapping the snarl pair.

proposal_sample()

tuple< int, const Snarl *, vector< NodeTraversal > > vg::MCMCGenotyper::proposal_sample

(

unique_ptr< PhasedGenome > &

current

)

const

Generates a proposal sample over the desired distrubution returns a sample from the proposal distribution

run_genotype()

unique_ptr< PhasedGenome > vg::MCMCGenotyper::run_genotype	(	const vector< multipath_alignment_t > &	reads,
		const double	log_base
	)		const

Takes as input a collection of mapped reads stored as a vector of multipath alignments and uses MCMC to find two optimal paths through the graph. Output: phased genome

Member Data Documentation

burn_in

const int vg::MCMCGenotyper::burn_in

private

frequency

const int vg::MCMCGenotyper::frequency

private

graph

VG& vg::MCMCGenotyper::graph

private

n_iterations

const int vg::MCMCGenotyper::n_iterations

private

random_engine

minstd_rand0 vg::MCMCGenotyper::random_engine

mutableprivate

seed

const int vg::MCMCGenotyper::seed

private

snarls

SnarlManager& vg::MCMCGenotyper::snarls

private

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The documentation for this class was generated from the following files:

• src/mcmc_genotyper.hpp
• src/mcmc_genotyper.cpp