Efficient computation of spaced seed hashing with block indexing.

Background: Spaced-seeds, i.e. patterns in which some fixed positions are allowed to be wild-cards, play a crucial role in several bioinformatics applications involving substrings counting and indexing, by often providing better sensitivity with respect to k-mers based approaches.

FSH: fast spaced seed hashing exploiting adjacent hashes.

Background: Patterns with wildcards in specified positions, namely , are increasingly used instead of -mers in many bioinformatics applications that require indexing, querying and rapid similarity search, as they can provide better sensitivity. Many of these applications require to compute the hashing of each position in the input sequences with respect to the given spaced seed, or to multiple spaced seeds. While the hashing of -mers can be rapidly computed by exploiting the large overlap between consecutive -mers, spaced seeds hashing is usually computed from scratch for each position in the input sequence, thus resulting in slower processing.

Higher recall in metagenomic sequence classification exploiting overlapping reads.

Background: In recent years several different fields, such as ecology, medicine and microbiology, have experienced an unprecedented development due to the possibility of direct sequencing of microbioimic samples. Among problems that researchers in the field have to deal with, taxonomic classification of metagenomic reads is one of the most challenging. State of the art methods classify single reads with almost 100% precision.

MetaProb: accurate metagenomic reads binning based on probabilistic sequence signatures.

Motivation: Sequencing technologies allow the sequencing of microbial communities directly from the environment without prior culturing. Taxonomic analysis of microbial communities, a process referred to as binning, is one of the most challenging tasks when analyzing metagenomic reads data. The major problems are the lack of taxonomically related genomes in existing reference databases, the uneven abundance ratio of species and the limitations due to short read lengths and sequencing errors.