We will have the following seminar by Alex Di Genova,
https://adigenova.github.io, on March 8th.

Title: Fast-SG: An alignment-free algorithm for hybrid assembly

Date: 2018-Mar-08   Time: 10:00
Room: INESC-ID 336

Abstract: Long read sequencing technologies are the ultimate solution
for genome repeats, allowing near reference level reconstructions
of large genomes. However, long read de novo assembly pipelines are
computationally intense and require a considerable amount of coverage,
thereby hindering their broad application to the assembly of large
genomes. Alternatively, hybrid assembly methods which combine short
and long read sequencing technologies can reduce the time and cost
required to produce de novo assemblies of large genomes. In this
paper, we propose a new method, called FAST-SG, which uses a new
ultra-fast alignment- free algorithm specifically designed for
constructing a scaffolding graph using light-weight data structures.
FAST-SG can construct the graph from either short or long reads.
This allows the reuse of efficient algorithms designed for short
read data and permits the definition of novel modular hybrid assembly
pipelines. Using comprehensive standard datasets and benchmarks,
we show how FAST-SG outperforms the state-of-the-art short read
aligners when building the scaffolding graph, and can be used to
extract linking information from either raw or error-corrected long
reads. We also show how a hybrid assembly approach using FAST-SG
with shallow long read coverage (5X) and moderate computational
resources can produce long-range and accurate reconstructions of
the genomes of Arabidopsis thaliana (Ler-0) and human (NA12878).

BioRxiv Preprint: https://www.biorxiv.org/content/early/2017/10/26/209122