Turtle: identifying frequent k-mers with cache-efficient algorithms.

Motivation: Counting the frequencies of k-mers in read libraries is often a first step in the analysis of high-throughput sequencing data. Infrequent k-mers are assumed to be a result of sequencing errors. The frequent k-mers constitute a reduced but error-free representation of the experiment, which can inform read error correction or serve as the input to de novo assembly methods.

SLIQ: simple linear inequalities for efficient contig scaffolding.

Scaffolding is an important subproblem in de novo genome assembly, in which mate pair data are used to construct a linear sequence of contigs separated by gaps. Here we present SLIQ, a set of simple linear inequalities derived from the geometry of contigs on the line that can be used to predict the relative positions and orientations of contigs from individual mate pair reads and thus produce a contig digraph. The SLIQ inequalities can also filter out unreliable mate pairs and can be used as a preprocessing step for any scaffolding algorithm.