MOTIVATION: As genome graphs are powerful data structures for representing the genetic diversity within populations, they can help identify genomic variations that traditional linear references miss, but their complexity and size makes the analysis of genome graphs challenging. We sought to develop a genome graph analysis tool that helps these analyses to become more accessible by addressing the limitations of existing tools. Specifically, we improve scalability and user-friendliness, and we provide many new statistics tailored to variation graphs for graph evaluation, including sample-specific features. RESULTS: We developed an efficient, comprehensive, and integrated tool, gretl, to analyze genome graphs and gain insights into their structure and composition by providing a wide range of statistics. gretl can be utilized to evaluate different graphs, compare the output of graph construction pipelines with different parameters, as well as perform an in-depth analysis of individual graphs, including sample-specific analysis. With the assistance of gretl, novel patterns of genetic variation and potential regions of interest can be identified, for later, more detailed inspection. We demonstrate that gretl outperforms other tools in terms of speed, particularly for larger genome graphs. AVAILABILITY AND IMPLEMENTATION: Commented Rust source code and documentation is available under MIT license at https://github.com/MoinSebi/gretl together with Python scripts and step-by-step usage examples. The package is available at Bioconda for easy installation.

MOTIVATION: Genome-wide association study (GWAS) requires a researcher to perform a multitude of different actions during analysis. From editing and formatting genotype and phenotype information to running the analysis software to summarizing and visualizing the results. A typical GWAS workflow poses a significant challenge of utilizing the command-line, manual text-editing and requiring knowledge of one or more programming/scripting languages, especially for newcomers. RESULTS: vcf2gwas is a package that provides a convenient pipeline to perform all of the steps of a traditional GWAS workflow by reducing it to a single command-line input of a Variant Call Format file and a phenotype data file. In addition, all the required software is installed with the package. vcf2gwas also implements several useful features enhancing the reproducibility of GWAS analysis. AVAILABILITY AND IMPLEMENTATION: The source code of vcf2gwas is available under the GNU General Public License. The package can be easily installed using conda. Installation instructions and a manual including tutorials can be accessed on the package website at https://github.com/frankvogt/vcf2gwas. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: The ability to accurately read the order of nucleotides in DNA and RNA is fundamental for modern biology. Errors in next-generation sequencing can lead to many artifacts, from erroneous genome assemblies to mistaken inferences about RNA editing. Uneven coverage in datasets also contributes to false corrections. RESULT: We introduce Trowel, a massively parallelized and highly efficient error correction module for Illumina read data. Trowel both corrects erroneous base calls and boosts base qualities based on the k-mer spectrum. With high-quality k-mers and relevant base information, Trowel achieves high accuracy for different short read sequencing applications.The latency in the data path has been significantly reduced because of efficient data access and data structures. In performance evaluations, Trowel was highly competitive with other tools regardless of coverage, genome size read length and fragment size. AVAILABILITY AND IMPLEMENTATION: Trowel is written in C++ and is provided under the General Public License v3.0 (GPLv3). It is available at http://trowel-ec.sourceforge.net. CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: The sequencing of over a thousand natural strains of the model plant Arabidopsis thaliana is producing unparalleled information at the genetic level for plant researchers. To enable the rapid exploitation of these data for functional proteomics studies, we have created a resource for the visualization of protein information and proteomic datasets for sequenced natural strains of A. thaliana. RESULTS: The 1001 Proteomes portal can be used to visualize amino acid substitutions or non-synonymous single-nucleotide polymorphisms in individual proteins of A. thaliana based on the reference genome Col-0. We have used the available processed sequence information to analyze the conservation of known residues subject to protein phosphorylation among these natural strains. The substitution of amino acids in A. thaliana natural strains is heavily constrained and is likely a result of the conservation of functional attributes within proteins. At a practical level, we demonstrate that this information can be used to clarify ambiguously defined phosphorylation sites from phosphoproteomic studies. Protein sets of available natural variants are available for download to enable proteomic studies on these accessions. Together this information can be used to uncover the possible roles of specific amino acids in determining the structure and function of proteins in the model plant A. thaliana. An online portal to enable the community to exploit these data can be accessed at http://1001proteomes.masc-proteomics.org/

MOTIVATION: Next-generation sequencing technologies have facilitated the study of organisms on a genome-wide scale. A recent method called restriction site associated DNA sequencing (RAD-seq) allows to sample sequence information at reduced complexity across a target genome using the Illumina platform. Single-end RAD-seq has proven to provide a large number of informative genetic markers in reference as well as non-reference organisms. RESULTS: Here, we present a method for de novo assembly of paired-end RAD-seq data in order to produce extended contigs flanking a restriction site. We were able to reconstruct one-tenth of the guppy genome represented by 200-500 bp contigs associated to EcoRI recognition sites. In addition, these contigs were used as reference allowing the detection of thousands of new polymorphic markers that are informative for mapping and population genetic studies in the guppy. AVAILABILITY: A perl and C++ implementation of the method demonstrated in this article is available under http://guppy.weigelworld.org/weigeldatabases/radMarkers/ as package RApiD. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Material and methods For a large-scale dataset of over 200,000 SNPs from about 200 individuals together with several phenotypes, published by Atwell et al. [1], we develop efficient methods to find pairs of SNPs which are strongly associated with the phenotype. As an exhaustive search of all possible combinations of interacting SNPs is often unfeasible, even when only considering pairs of interacting SNPs, the challenge is to find methods which avoid an exhaustive search but can still guarantee to find the causal pair. We propose two distinct approaches to efficiently determine the t top-scoring pairs of SNPs.

MOTIVATION: One challenging aspect of genotyping and association mapping projects is often the identification of markers that are informative between groups of individuals and to convert these into genotyping assays. RESULTS: The Multiple SNP Query Tool (MSQT) extracts SNP information from multiple sequence alignments, stores it in a database, provides a web interface to query the database and outputs SNP information in a format directly applicable for SNP-assay design. MSQT was applied to Arabidopsis thaliana sequence data to develop SNP genotyping assays that distinguish a recurrent parent (Col-0) from five other strains. SNPs with intermediate allele frequencies were also identified and developed into markers suitable for efficient genetic mapping among random pairs of wild strains. AVAILABILITY: The source code for MSQT is available at http://msqt.weigelworld.org, together with an online instance of MSQT containing data on 1214 sequenced fragments from 96 ecotypes (wild inbred strains) of the reference plant A. thaliana. All SNP genotyping assays are available in several formats for broad community use. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Abstract Summary: MicroRNAs (miRNAs) are a recently discovered class of non-coding RNAs that regulate gene and protein expression in plants and animals. MiRNAs have so far been identified mostly by specific cloning of small RNA molecules, complemented by computational methods. We present a computational identification approach that is able to identify candidate miRNA homologs in any set of sequences, given a query miRNA. The approach is based on a sequence similarity search step followed by a set of structural filters. Availability: microHARVESTER is offered as a web-service and additionally as source code upon request at Contact: [email protected]