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Motivation: Existing nanopore single-cell data analysis tools showed severe limitations in handling current data sizes., Results: We introduce scywalker, an innovative and scalable package developed to comprehensively analyze long-read sequencing data of full-length single-cell or single-nuclei cDNA. We developed novel scalable methods for cell barcode demultiplexing and single-cell isoform calling and quantification and incorporated these in an easily deployable package. Scywalker streamlines the entire analysis process, from sequenced fragments in FASTQ format to demultiplexed pseudobulk isoform counts, into a single command suitable for execution on either server or cluster. Scywalker includes data quality control, cell type identification, and an interactive report. Assessment of datasets from the human brain, Arabidopsis leaves, and previously benchmarked data from mixed cell lines demonstrate excellent correlation with short-read analyses at both the cell-barcoding and gene quantification levels. At the isoform level, we show that scywalker facilitates the direct identification of cell-type-specific expression of novel isoforms., Availability and Implementation: Scywalker is available on github.com/derijkp/scywalker under the GNU General Public License (GPL) and at https://zenodo.org/records/13359438/files/scywalker-0.108.0-Linux-x86_64.tar.gz., (© The Author(s) 2024. Published by Oxford University Press.)

Summary: Modified nucleotides play a crucial role in gene expression regulation. Here, we describe methplotlib, a tool developed for the visualization of modified nucleotides detected from Oxford Nanopore Technologies sequencing platforms, together with additional scripts for statistical analysis of allele-specific modification within-subjects and differential modification frequency across subjects., Availability and Implementation: The methplotlib command-line tool is written in Python3, is compatible with Linux, Mac OS and the MS Windows 10 Subsystem for Linux and released under the MIT license. The source code can be found at https://github.com/wdecoster/methplotlib and can be installed from PyPI and bioconda. Our repository includes test data, and the tool is continuously tested at travis-ci.com., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2020. Published by Oxford University Press.)

Long-read sequencing has substantial advantages for structural variant discovery and phasing of variants compared to short-read technologies, but the required and optimal read length has not been assessed. In this work, we used long reads simulated from human genomes and evaluated structural variant discovery and variant phasing using current best practice bioinformatics methods. We determined that optimal discovery of structural variants from human genomes can be obtained with reads of minimally 20 kb. Haplotyping variants across genes only reaches its optimum from reads of 100 kb. These findings are important for the design of future long-read sequencing projects., (© The Author(s) 2019. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

Genetic variants in or near miRNA genes can have profound effects on miRNA expression and targeting. As user-friendly software for the impact prediction of miRNA variants on a large scale is still lacking, we created a tool called miRVaS. miRVaS automates this prediction by annotating the location of the variant relative to functional regions within the miRNA hairpin (seed, mature, loop, hairpin arm, flanks) and by annotating all predicted structural changes within the miRNA due to the variant. In addition, the tool defines the most important region that is predicted to have structural changes and calculates a conservation score that is indicative of the reliability of the structure prediction. The output is presented in a tab-separated file, which enables fast screening, and in an html file, which allows visual comparison between wild-type and variant structures. All separate images are provided for downstream use. Finally, we tested two different approaches on a small test set of published functionally validated genetic variants for their capacity to predict the impact of variants on miRNA expression., (© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The dietary sources of CoQ10 and the evaluation of CoQ10 in dairy products were characterized. For quantitation of CoQ10 in food samples, 2 liquid chromatography (LC) methods with UV and mass spectrometry (MS) detections were developed. LC with UV detection was performed at 25 degrees C on a Hyperclone ODS 5 microm 150 x 4.6 mm column with mobile phase consisting of methanol-ethanol-2-propanol (70 + 15 + 15, v/v/v). Flow rate was 1.0 mL/min. Retention time of CoQ10 was 10.9 +/- 0.1 min. The method was sensitive [limit of detection (LOD) = 0.2 mg/kg], reproducible [relative standard deviation (RSD) = 3:0%), and linear up to 25 mg/kg (R > 0.999). LC/MS analysis was performed on a LUNA C18 3 microm, 150 x 4.6 mm column, using mobile phase consisting of ethanol-dioxane-acetic acid (9 + 1 + 0.01, v/v/v), flow rate was 0.6 mL/min, and the retention time of CoQ10 was 4.1 +/- 0.1 min. Identification and quantitation were performed with a Finnigan-LCQ mass detector in positive atmospheric pressure chemical ionization mode. Mass spectra were obtained in selected-ion monitoring mode; molecular mass (M+H)+ m/z 863.4 +/- 1 was used for quantitative determination. MS detection is more sensitive than UV detection (LOD = 0.1 mg/kg), less reproducible (RSD = 4.0%), and linear in selected range. Analytical recoveries are 75-90% and depend on the ratio between the amount of fat in the matrix and the concentration of CoQ10 in the sample. Some soybean milk products were analyzed together with different cow, goat, and sheep milk products. Concentrations obtained with LC and LC/MS were compared with a few accessible results available from the literature. Concentrations varied from 0 ppm in soybean milk to nearly 2 ppm in fresh milk from local farms.