The present invention relates to methods for preparing an isolated biological sample containing at least one of
DNA and
RNA, such that the
DNA and / or
RNA is preserved in the sample at ambient temperatures for at least thirty days, the method comprising: contacting the isolated biological sample with a composition comprising a
chaotropic agent, and subjecting the contacted sample to microbial
cell lysis; and optionally, contacting the lysed biological sample with a
slurry of size-selected
silicon dioxide to form at least one of
DNA-
silicon dioxide complexes or
RNA-
silicon dioxide complexes in the sample; isolating at least one of DNA-
silicon dioxide complexes or RNA-
silicon dioxide complexes from the sample; and, separating at least one of DNA and RNA from the
silicon dioxide and collecting at least one of the DNA and RNA.The present invention further relates to methods for preparing an isolated biological sample, the method comprising, separating the components in an isolated biological sample according to their size, wherein the components are at least one of DNA and RNA; purifying and isolating SSU rRNA from the biological sample using a composition comprising a
ribonuclease inhibitor and
a deoxyribonuclease to remove DNA from the sample, reverse transcribing the SSU rRNA into ds cDNA using random primers for SSU rRNA.The present invention also relates to computer implemented methods comprising, receiving an isolated sample prepared according to the methods of the invention, sequencing the sample, and providing the sequence with a sequence identifier (ID), the sequence comprising a plurality of groups of k-mers, each group of k-mers defining a node in a multi-level hierarchy which defines the relationship between the groups of k-mers; providing each group of k-mers with a respective
group identifier (ID), determining the frequency of the k-mers in each group; generating a
group signature array for each group of k-mers, each
group signature array comprising the k-mers in each group that have the most increased frequency compared with the sibling k-mers; generating a signature map comprising each
group signature array and at least one of the identifiers, the identifier of at least one parent group and the identifier of at least one child group; and outputting the signature map to be used to classify the sequence.