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Van der Jeugt, F.

Publications and source records attributed to Van der Jeugt, F..

3 recordsLinked to original sources

Stack Mapping Anchor Points (SMAP): a versatile suite of tools for read-backed haplotyping

Here we present SMAP, a software package that implements a suite of computational tools to extract multi-allelic haplotypes using read-backed haplotyping. SMAP tools first perform accurate read processing and analyze read mapping distributions across sample sets. Then, two complementary modules can be invoked for haplotype calling: SMAP haplotype-sites combines known Single Nucleotide Polymorphisms (SNPs) and/or read mapping position polymorphisms (SMAPs) to reconstruct compressed, read-reference-encoded haplotype strings. In contrast, SMAP haplotype-window works independent of prior knowledge of polymorphisms, groups reads by locus, defines a window enclosed between two custom border sequences, and retains the entire corresponding DNA sequence as haplotype. Haplotype-window is, among many applications, especially useful for high-throughput CRISPR/Cas mutation screens. Either way, SMAP creates a single integrated haplotype call table across all loci and samples. SMAP haplotyping is extremely versatile and can be applied to highly multiplex amplicon sequencing (HiPlex), Shotgun (e.g. whole genome shotgun (WGS) sequencing, probe capture and RNA-Seq), or Genotyping-by-Sequencing (GBS) data; and to Illumina short reads, PacBio and MinION long reads. SMAP creates discrete genotype calls for individuals of any ploidy or quantitative haplotype frequency spectra for Pool-Seq data, and can scale from tens to thousands of loci and/or samples. SMAP, including the source code written in Python is available at https://gitlab.com/truttink/smap, and a detailed user manual and guidelines for accurate read processing is available at https://ngs-smap.readthedocs.io/, under the GNU Affero General Public License v3.0.

genomics↗

FragGeneScanRs: better and faster gene prediction for short reads

FragGeneScanRs is a better and faster Rust implementation of the FragGeneScan gene prediction model for short and error-prone reads. Its command line interface is backward compatible and adds extra features for more flexible usage. Compared to the original C implementation, shotgun metagenomic reads are processed up to 22 times faster using a single thread, with better scaling for multithreaded execution. Availability and implementationThe Rust code of FragGeneScanRs is freely available from GitHub under the GPL-3.0 license, with instructions for installation, usage and other documentation.

bioinformatics↗

UMGAP: the Unipept MetaGenomics Analysis Pipeline

Shotgun metagenomics is now commonplace to gain insights into communities from diverse environments, but fast, memory-friendly, and accurate tools are needed for deep taxonomic analysis of the metagenome data. To meet this need we developed UMGAP, a highly versatile open source command line tool implemented in Rust for taxonomic profiling of shotgun metagenomes. It differs from state-of-the-art tools in its use of protein code regions identified in short reads for robust taxonomic identifications, a broad-spectrum index that can identify both archaea, bacteria, eukaryotes and viruses, a non-monolithic design, and support for interactive visualizations of complex biodiversities.

bioinformatics↗