  Cheap high-throughput DNA sequencing may soon become routine not only for
human genomes but also for practically anything requiring the identification of
living organisms from their DNA: tracking of infectious agents, control of food
products, bioreactors, or environmental samples.
  We propose a novel general approach to the analysis of sequencing data in
which the reference genome does not have to be specified. Using a distributed
architecture we are able to query a remote server for hints about what the
reference might be, transferring a relatively small amount of data, and the
hints can be used for more computationally-demanding work.
  Our system consists of a server with known reference DNA indexed, and a
client with raw sequencing reads. The client sends a sample of unidentified
reads, and in return receives a list of matching references known to the
server. Sequences for the references can be retrieved and used for exhaustive
computation on the reads, such as alignment.
  To demonstrate this approach we have implemented a web server, indexing tens
of thousands of publicly available genomes and genomic regions from various
organisms and returning lists of matching hits from query sequencing reads. We
have also implemented two clients, one of them running in a web browser, in
order to demonstrate that gigabytes of raw sequencing reads of unknown origin
could be identified without the need to transfer a very large volume of data,
and on modestly powered computing devices.
  A web access is available at http://tapir.cbs.dtu.dk. The source code for a
python command-line client, a server, and supplementary data is available at
http://bit.ly/1aURxkc.
