bf42be44fc
-- The previous creation algorithm used the following algorithm: for each kmer1 -> kmer2 in each read add kmers 1 and 2 to the graph add edge kmer1 -> kmer2 in the graph, if it's not present (does check) update edge count by 1 if kmer1 -> kmer2 already existed in the graph -- This algorithm had O(reads * kmers / read * (getEdge cost + addEdge cost)). This is actually pretty expensive because get and add edges is expensive in jgrapht. -- The new approach uses the following algorithm: for each kmer1 -> kmer2 in each read add kmers 1 and 2 to a kmer counter, that counts kmer1+kmer2 in a fast hashmap for each kmer pair 1 and 2 in the hash counter add edge kmer1 -> kmer2 in the graph, if it's not present (does check) with multiplicity count from map update edge count by count from map if kmer1 -> kmer2 already existed in the graph -- This algorithm ensures that we add very much fewer edges -- Additionally, created a fast kmer class that lets us create kmers from larger byte[]s of bases without cutting up the byte[] itself. -- Overall runtimes are greatly reduced using this algorith |
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| .. | ||
| annotator | ||
| beagle | ||
| bqsr | ||
| compression/reducereads | ||
| diagnostics | ||
| diffengine | ||
| fasta | ||
| filters | ||
| genotyper | ||
| haplotypecaller | ||
| indels | ||
| phasing | ||
| validation | ||
| varianteval | ||
| variantrecalibration | ||
| variantutils | ||