Viral RefSeq databases for Centrifuge, Kraken2 and DIAMOND

Owing to technological advances in ancient DNA, it is now possible to
sequence viruses from the past to track down their origin and evolution.
However, ancient DNA data is considerably more degraded and contaminated
than modern data making the identification of ancient viral genomes
particularly challenging. Several methods to characterise the modern
microbiome (and, within this, the virome) have been developed; in
particular, tools that assign sequenced reads to specific taxa in order to
characterise the organisms present in a sample of interest. While these
existing tools are routinely used in modern data, their performance when
applied to ancient microbiome data to screen for ancient viruses remains
unknown.  In this work, we conducted an extensive simulation
study using public viral sequences to establish which tool is the most
suitable to screen ancient samples for human DNA viruses. We compared the
performance of four widely used classifiers, namely Centrifuge, Kraken2,
DIAMOND and MetaPhlAn2, in correctly assigning sequencing reads to the
corresponding viruses. To do so, we simulated reads by adding noise
typical of ancient DNA to a set of publicly available human DNA viral
sequences and to the human genome. We fragmented the DNA into different
lengths, added sequencing error and C to T and G to A deamination
substitutions at the read termini. Then we measured the resulting
sensitivity and precision for all classifiers.  Across most
simulations, more than 228 out of the 233 simulated viruses are recovered
by Centrifuge, Kraken2 and DIAMOND, in contrast to MetaPhlAn2 which
recovers only around one third. Overall, Centrifuge and Kraken2 have the
best performance with the highest values of sensitivity and precision. We
found that deamination damage has little impact on the performance of the
classifiers, less than the sequencing error and the length of the reads.
Since Centrifuge can handle short reads (in contrast to DIAMOND and
Kraken2 with default settings) and since it achieves the highest
sensitivity and precision at the species level across all the simulations
performed, it is our recommended tool. Regardless of the tool used, our
simulations indicate that, for ancient human studies, users should use
strict filters to remove all reads of potential human origin. Finally, we
recommend to verify which species are present in the database used, as it
might happen that default databases lack sequences for viruses of
interest.