Biology subjects

De Rijk, P.

Publications and source records attributed to De Rijk, P..

5 recordsLinked to original sources

bioRxiv2024

Scywalker: scalable end-to-end data analysis workflow for nanopore single-cell transcriptome sequencing

We introduce scywalker, an innovative and scalable package developed to comprehensively analyze long-read nanopore sequencing data of full-length single-cell or single-nuclei cDNA. Existing nanopore single-cell data analysis tools showed severe limitations in handling current data sizes. 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.

bioinformatics↗

bioRxiv2019

Critical length in long read resequencing

Long read sequencing has a substantial advantage 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 simulated long reads 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 15 kbp. Haplotyping genes entirely only reaches its optimum from reads of 100 kbp. These findings are important for the design of future long read sequencing projects.

bioinformatics↗

bioRxiv2018

opentsv prevents the corruption of scientific data byExcel

Microsoft Excel is widely used by researchers to edit tab- or comma-separated data files. However, Excel often corrupts the data when opening these files, most notably by changing some gene names to a date. Although this problem was cautioned against earlier, we show that every year hundreds of published papers still come with supplementary data files containing these errors. Opentsv was developed to effectively circumvent this problem at the root by providing an easy and transparent way to open delimited data files in Excel without these conversions. Opentsv is freely available at https://github.com/derijkp/opentsv.

bioinformatics↗

bioRxiv2018

Accurate characterization of expanded tandem repeat length and sequence through whole genome long-read sequencing on PromethION.

Tandem repeats (TRs) can cause disease through their length, sequence motif interruptions, and nucleotide modifications. For many TRs, however, these features are very difficult - if not impossible - to assess, requiring low-throughput and labor-intensive assays. One example is a VNTR in ABCA7 for which we recently discovered that expanded alleles strongly increase risk of Alzheimers disease. Here, we investigated the potential of long-read whole genome sequencing to surmount these challenges, using the high-throughput PromethION platform from Oxford Nanopore Technologies. To overcome the limitations of conventional base calling and alignment, we developed an algorithm to study the TR size and sequence directly on raw PromethION current data.\n\nWe report the long-read sequencing of multiple human genomes (n = 11) using only a single sequencing run and flow cell per individual. With the use of fresh DNA extractions, DNA shearing to approximately 20kb and size selection, we obtained an average output of 70 gigabases (Gb) per flow cell, corresponding to a 21x genome coverage, and a maximum yield of 98 Gb (30x genome coverage). All ABCA7 VNTR alleles, including expansions up to 10,000 bases, were spanned by long sequencing reads, validated by Southern blotting. Classical approaches of TR length estimation suffered from low accuracy, low precision, DNA strand effects and/or inability to call pathogenic repeat expansions. In contrast, our novel NanoSatellite algorithm, which circumvents base calling by using dynamic time warping on raw PromethION current data, achieved more than 90% accuracy and high precision (5.6% relative standard deviation) of TR length estimation, and detected all clinically relevant repeat expansions. In addition, we identified alternative TR sequence motifs with high consistency, allowing determination of TR sequence and distinction of VNTR alleles with homozygous length.\n\nIn conclusion, we validated the robustness of single-experiment whole genome long-read sequencing on PromethION, a prerequisite for application of long-read sequencing in the clinic. In addition, we outperformed Southern blotting, enabling improved characterization of the role of expanded ABCA7 VNTR alleles in Alzheimers disease, and opening new opportunities for TR research.

genomics↗

bioRxiv2018

Structural variants identified by Oxford Nanopore PromethION sequencing of the human genome

We sequenced the Yoruban NA19240 genome on the long read sequencing platform Oxford Nanopore PromethION for benchmarking and evaluation of recently published aligners and structural variant calling tools. In this work, we determined the precision and recall, present high confidence and high sensitivity call sets of variants and discuss optimal parameters. The aligner Minimap2 and structural variant caller Sniffles are both the most accurate and the most computationally efficient tools in our study. We describe our scalable workflow for identification, annotation, and characterization of tens of thousands of structural variants from long read genome sequencing of an individual or population. By discussing the results of this genome we provide an approximation of what can be expected in future long read sequencing studies aiming for structural variant identification.

bioinformatics↗