Changed the calculation of the binomial probability to log-scale

In doing so, we can use the native mathematical functions instead of Math::BigInt and Math::BigFloat.
This results in a huge speed up for large input sets. The calculation of the p-values now happens in
less than 1 sec, even for 1000 probes.

This change was 1st implemented in eFORGE. See https://github.com/jherrero/eFORGE/commit/aad0524bcb39191634d082fb2007c02e6b8766d1
Overcome the SQLite limit in the number of SQL variables that can be used in a single query

The code now goes through a loop to ensure that no more than 999 variables are used. As before, the results are simply pushed into the final array, which is returned by the method.

See https://github.com/jherrero/eFORGE/commit/f1dbfdb1e9dfe0dd713231330aab7d9f15341a3a
Speed improvement (DBI)

Change $dbh->prepare to $dbh->prepare_cached and $sth->fetchall_arrayref to $sth->fetchrow_arrayref

See: https://github.com/jherrero/eFORGE/commit/1f799cde63cf7620e2817786a78cfbba828b28dc?diff=unified
Speed up (process bits)

Use a temporary table instead of hash of hashes to store the results in the internal loop. The data and then copied to the final %test hash at the end of the method.

Also, use an array of indexes instead of a counter for the loop.

See: https://github.com/jherrero/eFORGE/commit/a54a23dab1a73d361ae335cae9881104648000b8