I am running
unitig-caller --call --reads input_reads.txt --out output_folder --threads 76 --pyseer
and
./DBGWAS -strains input_strains.txt -keepNA -output output_folder -nb-cores 76
the two input files have the same assembled genomes and NA as phenotype. I was expecting to get an identical number of nodes in the graph but I am getting a mismatch of a few million - 2,251,639 (Uniting-caller) and 7,022,727 (DBGWAS). Does Uniting-caller have a filtering threshold? Where does the difference come from?
I am running
unitig-caller --call --reads input_reads.txt --out output_folder --threads 76 --pyseer
and
./DBGWAS -strains input_strains.txt -keepNA -output output_folder -nb-cores 76
the two input files have the same assembled genomes and NA as phenotype. I was expecting to get an identical number of nodes in the graph but I am getting a mismatch of a few million - 2,251,639 (Uniting-caller) and 7,022,727 (DBGWAS). Does Uniting-caller have a filtering threshold? Where does the difference come from?