  Background: Identification of biological specimens is a major requirement for
a range of applications. Reference-free methods analyse unprocessed sequencing
data without relying on prior knowledge, but generally do not scale to
arbitrarily large genomes and arbitrarily large phylogenetic distances.
Results: We present Cnidaria, a practical tool for clustering genomic and
transcriptomic data with no limitation on genome size or phylogenetic
distances. We successfully simultaneously clustered 169 genomic and
transcriptomic datasets from 4 kingdoms, achieving 100% identification accuracy
at supra-species level and 78% accuracy for species level. Discussion: CNIDARIA
allows for fast, resource-efficient comparison and identification of both raw
and assembled genome and transcriptome data. This can help answer both
fundamental (e.g. in phylogeny, ecological diversity analysis) and practical
questions (e.g. sequencing quality control, primer design).
