LongReadSum: A fast and flexible quality control and signal summarization tool for long-read sequencing data.

While several well-established quality control (QC) tools are available for short reads sequencing data, there is a general paucity of computational tools that provide long read metrics in a fast and comprehensive manner across all major sequencing platforms (such as PacBio, Oxford Nanopore, Illumina Complete Long Read) and data formats (such as ONT POD5, FAST5, basecall summary files and PacBio unaligned BAM). Additionally, none of the current tools provide support for summarizing Oxford Nanopore basecall signal or comprehensive base modification (methylation) information from genomic data. Furthermore, nowadays a single PromethION flowcell on the Oxford Nanopore platform can generate terabytes of signal data, which cannot be handled by existing tools designed for small-scale flowcells.

Noncoding de novo mutations in are associated with autism spectrum disorders.

Coding mutations (DNMs) contribute to the risk for autism spectrum disorders (ASD), but the contribution of noncoding DNMs remains relatively unexplored. Here we use whole genome sequencing (WGS) data of 12,411 individuals (including 3,508 probands and 2,218 unaffected siblings) from 3,357 families collected in Simons Foundation Powering Autism Research for Knowledge (SPARK) to detect DNMs associated with ASD, while examining Simons Simplex Collection (SSC) with 6383 individuals from 2274 families to replicate the results. For coding DNMs, reached exome-wide significance (p=2.

A signal processing and deep learning framework for methylation detection using Oxford Nanopore sequencing.

Oxford Nanopore sequencing can detect DNA methylations from ionic current signal of single molecules, offering a unique advantage over conventional methods. Additionally, adaptive sampling, a software-controlled enrichment method for targeted sequencing, allows reduced representation methylation sequencing that can be applied to CpG islands or imprinted regions. Here we present DeepMod2, a comprehensive deep-learning framework for methylation detection using ionic current signal from Nanopore sequencing.

Classification of integers based on residue classes via modern deep learning algorithms.

Judging whether an integer can be divided by prime numbers such as 2 or 3 may appear trivial to human beings, but it can be less straightforward for computers. Here, we tested multiple deep learning architectures and feature engineering approaches to classifying integers based on their residues when divided by small prime numbers. We found that the ability of classification critically depends on the feature space.

Assessing the Expression of Long INterspersed Elements (LINEs) via Long-Read Sequencing in Diverse Human Tissues and Cell Lines.

Transposable elements, such as Long INterspersed Elements (LINEs), are DNA sequences that can replicate within genomes. LINEs replicate using an RNA intermediate followed by reverse transcription and are typically a few kilobases in length. LINE activity creates genomic structural variants in human populations and leads to somatic alterations in cancer genomes.

A survey of algorithms for the detection of genomic structural variants from long-read sequencing data.

As long-read sequencing technologies are becoming increasingly popular, a number of methods have been developed for the discovery and analysis of structural variants (SVs) from long reads. Long reads enable detection of SVs that could not be previously detected from short-read sequencing, but computational methods must adapt to the unique challenges and opportunities presented by long-read sequencing. Here, we summarize over 50 long-read-based methods for SV detection, genotyping and visualization, and discuss how new telomere-to-telomere genome assemblies and pangenome efforts can improve the accuracy and drive the development of SV callers in the future.

PrecisionFDA Truth Challenge V2: Calling variants from short and long reads in difficult-to-map regions.

The precisionFDA Truth Challenge V2 aimed to assess the state of the art of variant calling in challenging genomic regions. Starting with FASTQs, 20 challenge participants applied their variant-calling pipelines and submitted 64 variant call sets for one or more sequencing technologies (Illumina, PacBio HiFi, and Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with updated Genome in a Bottle benchmark sets and genome stratifications.

NanoCaller for accurate detection of SNPs and indels in difficult-to-map regions from long-read sequencing by haplotype-aware deep neural networks.

Long-read sequencing enables variant detection in genomic regions that are considered difficult-to-map by short-read sequencing. To fully exploit the benefits of longer reads, here we present a deep learning method NanoCaller, which detects SNPs using long-range haplotype information, then phases long reads with called SNPs and calls indels with local realignment. Evaluation on 8 human genomes demonstrates that NanoCaller generally achieves better performance than competing approaches.

Atorvastatin Attenuates Cold-Induced Hypertension by Preventing Gut Barrier Injury.

Chronic exposure to cold causes arterial hypertension [cold-induce hypertension (CIH)]. Emerging data have indicated that gut barrier dysfunction is involved in the pathogenesis of hypertension. In this study, we explored the effect of gut barrier dysfunction on vascular inflammation induced by cold exposure and the therapeutic effect of atorvastatin in a CIH rat model.

Biomechanical Analysis of a Filiform Mechanosensory Hair Socket of Crickets.

Filiform mechanosensory hairs of crickets are of great interest to engineers because of the hairs' highly sensitive response to low-velocity air-currents. In this study, we analyze the biomechanical properties of filiform hairs of the cercal sensory system of a common house cricket. The cercal sensory system consists of two antennalike appendages called cerci that are situated at the rear of the cricket's abdomen.

Analysis of laser fabricated microjoint performance in cerebrospinal fluid using a computational approach.

Assessment of neural biocompatibility requires that materials be tested with exposure in neural fluids. We have studied the mechanical performance of laser bonded microjoints between titanium foil and polyimide film (TiPI) in artificial cerebrospinal fluid (CSF). The samples were exposed in CSF for two, four and twelve weeks at 37 °C.

Postimplantation pressure testing and characterization of laser bonded glass/polyimide microjoints.

The stability of the laser bonded titanium coated glass/polyimide microjoints were studied in vivo by implanting on a rat brain surface for 10 days. In the current state, the strength of the joints were measured by a specially designed instrument called "pressure test" equipment where the samples were subjected to a variable pressure load (using high pressure nitrogen) controlled by a pressure regulator. The strength of the joints seems to degrade by about 28% as a result of soaking in rat brain.