Fill a forward table cache

An in-memory cache for forward tables can be filled using this function, for either the whole sequence length or some sub-sequence.

Usage

FillTableCache(
  cache,
  pars,
  nthreads = min(parallel::detectCores(logical = FALSE), cache[[1]]$to_recipient -
    cache[[1]]$from_recipient + 1)
)

Arguments

cache

a cache of forward tables as generated by CreateForwardTableCache().

pars

a kalisParameters object, as returned by Parameters().

nthreads

the number of CPU cores to use. By default uses the parallel package to detect the number of physical cores.

Value

There is nothing returned.

NOTE: for performance reasons, cache is updated in-place.

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 CreateForwardTableCache() and should then be filled with this function. 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; CreateForwardTableCache() to generate 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
}
} # }