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Create an in-memory cache for forward tables to improve efficiency when iterating in reverse along the haplotype sequences.

Usage

CreateForwardTableCache(
  pars,
  size = 1,
  from_recipient = 1,
  to_recipient = Inf,
  max.tables = 0
)

Arguments

pars

a kalisParameters object, as returned by Parameters().

size

the maximum amount of RAM (in GB) to devote to this cache. By default, 1GB.

from_recipient

first recipient haplotype if creating a partial forward table cache. By default includes from the first recipient haplotype.

to_recipient

last recipient haplotype if creating a partial forward table cache. By default includes to the last recipient haplotype.

max.tables

positive integer indicating the maximum number of tables to use in the cache. Both this and size will be honoured, so the number of tables may be smaller than this. By default, equals \(\lfloor\log_2(L)\rfloor\).

Value

A list of forward tables representing a cache and ready to be filled is returned.

Details

If the objective is to run the Li and Stephens hidden Markov model both forwards and backwards to the same locus (and to do so for every possible locus), then considerable efficiency can be achieved by first performing a full scan forwards, filling a geometrically spaced cache whilst doing so. Then, by working backwards, the backward propagation moves one locus at a time and the forward propagation can move backwards by moving forward from a recently cached local table.

Memory for a cache can be allocated using this function and should then be filled with FillTableCache(). To use the cache, then instead of using the Forward() function, use ForwardUsingTableCache().

References

Christ, R.R., Wang, X., Aslett, L.J.M., Steinsaltz, D. and Hall, I. (2024) "Clade Distillation for Genome-wide Association Studies", bioRxiv 2024.09.30.615852. Available at: doi:10.1101/2024.09.30.615852 .

See also

MakeForwardTable() to make a forward table; FillTableCache() to fill a cache; ForwardUsingTableCache() to use a cache; Forward() for forward function without using a cache.

Alternatively, see ForwardIterator() to create an iterator which internally creates or uses a table cache.

Examples

if (FALSE) { # \dontrun{
# This code assumes you have already:
#  i) cached the haplotypes using CacheHaplotypes function
#  ii) setup parameters in a variable called pars
#  iii) set the number of loci in a variable called L

# Allocate up to 10GB to a cache, with parameters already setup in pars ...
cache <- CreateForwardTableCache(pars, 10)
# ... and fill it
FillTableCache(cache, pars, nthreads = 8)

# Create forward and backward tables
fwd <- MakeForwardTable(pars)
bck <- MakeBackwardTable(pars)

# Then reach every locus faster by iterating backwards, using the cache to
# move the forward table into position faster
for(l in L:1) {
  Backward(bck, pars, l, nthreads = 8)
  ForwardUsingTableCache(fwd, pars, cache, l, nthreads = 8)
  # Do whatever work is required at
  # every locus here using fwd and bck
}
} # }