manual/part1/pitch.md
# How can MiGA help me?
MiGA's analyses can accurately classify genomes providing a statistical
classification support, identify taxonomic novelty, and annotate and evaluate
sequencing reads and assembly quality, among others.
MiGA can take in a variety of inputs such as raw, unassembled reads,
assembled isolate genomes, metagenome-assembled genomes (MAGs),
and single-cell amplified genomes (SAGs).
MiGA uses a combination of the genome-aggregate average nucleotide
identity concept or ANI and the average amino-acid identity, AAI, to
taxonomically classify a query genomic sequence against the genome sequences in
its reference database. Part of MiGA’s strength lies in the 10,000+ reference
genomes that make up its database and an efficient heuristic algorithm to search
the query genome against all this database. The reference database is regularly
updated and improved with minimal downtime, ensuring consistently improved
classification accuracy.