For building the sequence graph index, each sample was processed with KMC (version 3, Kokot et al., 2017) to convert the reads in FASTA format into lists of k-mer counts, using different values of k ranging from 13 to 19 in increments of 2. All k-mers that contained the character “N” or occurred in a sample less than twice were removed. For each value of k, we built a separate index, consisting of a labeled de Bruijn graph, using an implicit representation of the complete graph and a compressed label representation based on Multiary Binary Relation Wavelet Trees (Multi-BRWT). For further details, we refer to the manuscript (Karasikov et al., 2020). To build the index, for each sample the KMC k-mer count lists were transformed into de Bruijn graphs, from which path covers in the form of contig sets were extracted and stored as intermediate FASTA files. The contig sets of each sample were then transformed into annotation columns (one column per sample) by mapping them onto an implicit complete de Bruijn graph of order k. All annotation columns were then merged into a joint annotation matrix and transformed into Multi-BRWT format. Finally, the topology of the Multi-BRWT representation was optimized by relaxing its internal tree arity constraints to allow for a maximum arity of 40.

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