In the previous version, mem_seed_sw() is only used for PacBio reads to filter
bad seeds. For non-PacBio long queries, bwa-mem uses mem_chain2aln_short() for
a similar purpose. However, it turns out that mem_chain2aln_short() is not
effective given long near-tandem repeats. Bwa-mem still wastes a lot of time
of futile ref substring and extensions.
In this commit, mem_chain2aln_short() has been removed. mem_seed_sw() is used
if the query sequence is long enough (~700bp). For shorter reads, the results
should be almost identical to the previous version.
Reduced -c to 500 by default. As a compensation, we choose up to 1000 positions
if a seed has 500 or more occurrences. In addition, a read with big portion
from such seeds will have lower mapping quality.
Example: GGAGGGGAAGGGTGGGCTGGAGGGGACGGGTGGGCTGGAGGGGAAGGGTGTGCTGGAGGGAAAAGGTGGACTGGAGGGGAAGGGTGGGCTGGAGGGGAAGG
This read has 5 chains, two of which are:
weight=80 26;26;0,4591439948(10:-3095894) 23;23;27,4591439957(10:-3095888) 31;31;70,4591439964(10:-3095873)
weight=50 45;45;51,4591440017(10:-3095806) 50;50;51,4591440017(10:-3095801) 31;31;70,4591440090(10:-3095747)
Extension from the 26bp seed in the 1st chain gives an alignment [0,101) <=> [4591439948,4591440067), which
contains the 50bp seed in the second chain. However, if we extend the 50bp seed, it yields a better alignment
[0,101) <=> [4591439966,4591440067) with a different starting position. The 26bp seed is wrong. This commit
adds a heuristic to fix this issue.
This function causes all kinds of problems when the reference genome consists
of many short reads/contigs/chromsomes. Some of the problems are nearly
unfixable at the point where bwa_fix_xref() gets called. This commit attempts
to fix the problem at the root. It disallows chains spanning multiple contigs
and never retrieves sequences bridging two adjacent contigs. Thus all the
chaining, extension, SW and global alignments are confined to on contig only.
This commit brings many changes. I have tested it on a couple examples
including Peter Field's PacBio example. It works well so far.
Heng Li