Biology subjects

Schoenherr, S.

Publications and source records attributed to Schoenherr, S..

7 recordsLinked to original sources

bioRxiv2024

Cloudgene 3: Transforming Nextflow Pipelines into Powerful Web Services

SummaryNextflow has emerged as a flexible and scalable workflow system for building computational pipelines in life sciences. Simultaneously, Software-as-a-Service platforms enable researchers to concentrate on data analysis rather than on setting up pipelines locally. However, converting existing pipelines into web services can be challenging due to complexities such as handling large datasets, web development and overall security. Cloudgene 3 addresses these challenges by providing a platform that transforms Nextflow pipelines into scalable web services in just a few steps. Making pipelines available as public or private services enhances collaboration among diverse teams and improves accessibility, eliminating the need for extensive technical expertise. Availability and ImplementationCloudgene 3 is free available at https://www.cloudgene.io Contactlukas.forer@i-med.ac.at

bioinformatics↗

bioRxiv2024

Improving the Reliability and Quality of Nextflow Pipelines with nf-test

The workflow management system Nextflow builds together with the nf-core community an essential ecosystem in Bioinformatics. However, ensuring the correctness and reliability of large and complex pipelines is challenging, since a unified and automated unit-style testing framework specific to Nextflow is still missing. To provide this crucial component to the community, we developed the testing framework nf-test. It introduces a modular approach that enables pipeline developers to test individual process blocks, workflow patterns and entire pipelines in insolation. nf-test is based on a similar syntax as Nextflow DSL 2 and provides unique features such as snapshot testing and smart testing to save resources by testing only changed modules. We show on different pipelines that these improvements minimize development time, reduce test execution time by up to 80% and enhance software quality by identifying bugs and issues early. Already adopted by dozens of pipelines, nf-test improves the robustness and reliability in pipeline development.

bioinformatics↗

bioRxiv2024

Nanopore sequencing with unique molecular identifiers enables accurate mutation analysis and haplotyping in the complex Lipoprotein(a) KIV-2 VNTR

BackgroundRepetitive genome regions, such as variable number of tandem repeats (VNTR) or short tandem repeats (STR), are major constituents of the uncharted dark genome and evade conventional sequencing approaches. The protein-coding LPA kringle IV type-2 (KIV-2) VNTR (5.6 kb per unit, 1-40 units per allele) is a medically highly relevant example with a particularly intricate structure, multiple haplotypes, intragenic homologies and an intra-VNTR STR. It is the primary regulator of plasma lipoprotein(a) [Lp(a)] concentrations, an important cardiovascular risk factor. However, despite Lp(a) variance is mostly genetically determined, Lp(a) concentrations vary widely between individuals and ancestries. This VNTR region hides multiple causal variants and functional haplotypes. MethodsWe evaluated the performance of amplicon-based nanopore sequencing with unique molecular identifiers (UMI-ONT-Seq) for SNP detection, haplotype mapping, VNTR unit consensus sequence generation and copy number estimation via coverage-corrected haplotypes quantification in the KIV-2 VNTR. We used 15 human samples and low-level mixtures (0.5% to 5%) of KIV-2 plasmids as a validation set. We then applied UMI-ONT-Seq to extract KIV-2 VNTR haplotypes in 48 multi-ancestry 1000-Genome samples and analyzed at scale a poorly characterized STR within the KIV-2 VNTR. ResultsUMI-ONT-Seq detected KIV-2 SNPs down to 1% variant level with high sensitivity, specificity and precision (0.977{+/-}0.018; 1.000{+/-}0.0005; 0.993{+/-}0.02) and accurately retrieved the full-length haplotype of each VNTR unit. Human variant levels were highly correlated with next-generation sequencing (R2=0.983) without bias across the whole variant level range. Six reads per UMI produced sequences of each KIV-2 unit with Q40-quality. The KIV-2 repeat number determined by coverage-corrected unique haplotype counting was in close agreement with droplet digital PCR (ddPCR), with 70% of the samples falling even within the narrow confidence interval of ddPCR. We then analyzed 62,679 intra-KIV-2 STR sequences and identified ancestry-specific STR patterns. Finally, we characterized the KIV-2 haplotype patterns across multiple ancestries. ConclusionsUMI-ONT-Seq accurately retrieves the SNP haplotype and precisely quantifies the VNTR copy number of each repeat unit of the complex KIV-2 VNTR region across multiple ancestries. This study utilizes the KIV-2 VNTR, presenting a novel and potent tool for comprehensive characterization of medically relevant complex genome regions at scale.

genomics↗

bioRxiv2023

Performing highly parallelized and reproducible GWAS analysis on biobank-scale data

MotivationGenome-wide association studies (GWAS) in large biobanks are transforming genetic research and enable the detection of novel genotype-phenotype relationships. In the last two decades, over 60,000 genetic associations across thousands of human diseases and traits have been discovered using a GWAS approach. Due to denser genotyping and increasing sample sizes, researchers are increasingly faced with computational challenges when executing GWAS analysis. A reproducible, modular and extensible pipeline with a focus on parallelization is essential to simplify data analysis and to allow researchers to devote their time to other essential tasks such as result interpretation and downstream analysis. ResultsHere we present nf-gwas, a Nextflow pipeline to run biobank-scale GWAS analysis. The pipeline automatically performs numerous pre- and post-processing steps, integrates regression modeling from the REGENIE package and currently supports single-variant, gene-based and interaction testing. nf-gwas also includes an extensive reporting functionality that allows to inspect thousands of phenotypes and navigate interactive Manhattan plots directly in the web browser. The pipeline is extensively tested using the unit-style testing framework nf-test to ensure code maintainability, a crucial requirement in clinical and pharmaceutical settings. Furthermore, we validated the pipeline against published GWAS datasets and benchmarked the pipeline on high-performance computing and cloud infrastructures to provide cost estimations to end users. Availabilitynf-gwas is free available at https://github.com/genepi/nf-gwas. Contactlukas.forer@i-med.ac.at

bioinformatics↗

bioRxiv2020

South Asian patient population genetics reveal strong founder effects and high rates of homozygosity - new resources for precision medicine

Population-scale genetic studies can identify drug targets and allow disease risk to be predicted with resulting benefit for management of individual health risks and system-wide allocation of health care delivery resources. Although population-scale projects are underway in many parts of the world, genetic variation between population groups means that additional projects are warranted. South Asia has a population whose genetics is the least characterized of any of the worlds major populations. Here we describe GenomeAsia studies that characterize population structure in South Asia and that create tools for economical and accurate genotyping at population-scale. Prior work on population structure characterized isolated population groups, the relevance of which to large-scale studies of disease genetics is unclear. For our studies we used whole genome sequence information from 4,807 individuals recruited in the health care delivery systems of Pakistan, India and Bangladesh to ensure relevance to population-scale studies of disease genetics. We combined this with WGS data from 927 individuals from isolated South Asian population groups, and developed a custom SNP array (called SARGAM) that is optimized for future human genetic studies in South Asia. We find evidence for high rates of reproductive isolation, endogamy and consanguinity that vary across the subcontinent and that lead to levels of homozygosity that approach 100 times that seen in outbred populations. We describe founder effects that increase the power to associate functional variants with disease processes and that make South Asia a uniquely powerful place for population-scale genetic studies.

genomics↗

bioRxiv2020

Haplocheck: Phylogeny-based Contamination Detection in Mitochondrial and Whole-Genome Sequencing Studies

Within-species contamination is a major issue in sequencing studies, especially for mitochondrial studies. Contamination can be detected by analysing the nuclear genome or by inspecting the heteroplasmic sites in the mitochondrial genome. Existing methods using the nuclear genome are computationally expensive, and no suitable tool for detecting contamination in large-scale mitochondrial datasets is available. Here we present haplocheck, a tool that requires only the mitochondrial genome to detect contamination in both mitochondrial and whole-genome sequencing studies. Haplocheck is able to distinguish between contaminated and real heteroplasmic sites using the mitochondrial phylogeny. By applying haplocheck to the 1000 Genomes Project data, we show (1) high concordance in contamination estimates between mitochondrial and nuclear DNA and (2) quantify the impact of mitochondrial copy numbers on the mitochondrial based contamination results. Haplocheck complements leading nuclear DNA based contamination tools, and can therefore be used as a proxy tool in nuclear genome studies. Haplocheck is available both as a command-line tool at https://github.com/genepi/haplocheck and as a cloud web-service producing interactive reports that facilitates the navigation through the phylogeny of contaminated samples.

bioinformatics↗

bioRxiv2019

Extraordinary claims require extraordinary evidence in the case of asserted mtDNA biparental inheritance

A breakthrough article published in PNAS by Luo et al. (2018) challenges a central dogma in biology which states that the mitochondrial DNA (mtDNA) is inherited exclusively from the mother. By sequencing the mitogenomes of several members of three independent families, the authors inferred an unprecedented pattern of biparental inheritance that requires the participation of an autosomal nuclear factor in the molecular process. However, a comprehensive analysis of their data reveals a number of issues that must be carefully addressed before challenging the current paradigm. Unfortunately, the methods section lacks any description of sample management, validation of their results in independent laboratories was deficient, and the reported findings have been observed at a frequency at complete variance with established evidence. Moreover, the remarkably high (and unusually homogeneous) levels of heteroplasmy reported can be readily detected using classical techniques for DNA sequencing. By reassessing the raw sequencing data with an alternative computational pipeline, we report strong correlation to the NextGENe results provided by the authors on a per sample base. However, the sequencing replicates from the same donors show aberrations in the variants detected that need further investigation to exclude contributions from other sources or methodological artifacts. Finally, applying the principle of reductio ad absurdum, we demonstrate that the nuclear factor invoked by the authors would need to be extraordinarily complex and precise in order to preclude linear accumulation of mtDNA lineages across generations. We discuss alternate scenarios that explain findings of the same nature as reported by Luo et al., in the context of in-vitro fertilization and therapeutic mtDNA replacement ooplasmic transplantation.

genetics↗