Bioinformatics

MOTIVATION: Multispectral biological fluorescence microscopy has enabled the identification of multiple targets in complex samples. The accuracy in the unmixing result degrades (1) as the number of fluorophores used in any experiment increases and (2) as the signal-to-noise ratio in the recorded images decreases. Further, the availability of prior knowledge regarding the expected spatial distributions of fluorophores in images of labeled cells provides an opportunity to improve the accuracy of fluorophore identification and abundance...

MOTIVATION: Researchers usually conduct statistical analyses based on models built on raw data collected from individual participants (individual-level data). There is a growing interest in enhancing inference efficiency by incorporating aggregated summary information from other sources, such as summary statistics on genetic markers' marginal associations with a given trait generated from genome-wide association studies. However, combining high-dimensional summary data with individual-level data using existing integrative procedures can be challenging due to various numeric issues in optimizing an objective function over a large number of unknown parameters...

MOTIVATION: Generating molecules of high quality and drug-likeness in the vast chemical space is a big challenge in the drug discovery. Most existing molecule generative methods focus on diversity and novelty of molecules, but ignoring drug potentials of the generated molecules during the generation process. RESULTS: In this study, we present a novel de novo multi-objective quality assessment-based drug design approach QADD, which integrates an iterative refinement framework with a novel graph-based molecular quality assessment model on drug potentials...

SUMMARY: HiCube is a lightweight web application for interactive visualization and exploration of diverse types of genomics data at multiscale resolutions. Especially, HiCube displays synchronized views of Hi-C contact maps and three-dimensional (3D) genome structures with user-friendly annotation and configuration tools, thereby facilitating the study of 3D genome organization and function. AVAILABILITY AND IMPLEMENTATION: HiCube is implemented in Javascript and can be installed via NPM...

MOTIVATION: Iso-Seq RNA long read sequencing enables the identification of full-length transcripts and isoforms, removing the need for complex analysis such as transcriptome assembly. However, the raw sequencing data need to be processed in a series of steps before annotation is complete. Here, we present nf-core/isoseq, a pipeline for automatic read processing and genome annotation. Following nf-core guidelines, the pipeline has few dependencies and can be run on any of platforms. AVAILABILITY: The pipeline is freely available online on the nf-core website (https://nf-co...

MOTIVATION: Pairwise sequence alignment is a very time-consuming step in common bioinformatics pipelines. Speeding up this step requires heuristics, efficient implementations, and/or hardware acceleration. A promising candidate for all of the above is the recently proposed GenASM algorithm. We identify and address three inefficiencies in the GenASM algorithm: it has a high amount of data movement, a large memory footprint, and does some unnecessary work. RESULTS: We propose Scrooge, a fast and memory-frugal genomic sequence aligner...

SUMMARY: Highly accurate protein structure predictors have generated hundreds of millions of protein structures; these pose a challenge in terms of storage and processing. Here we present Foldcomp, a novel lossy structure compression algorithm and indexing system to address this challenge. By using a combination of internal and cartesian coordinates and a bi-directional NeRF-based strategy, Foldcomp improves the compression ratio by a factor of 3 compared to the next best method. Its reconstruction error of 0...

MOTIVATION: Beta-diversity quantitatively measures the difference among microbial communities, thus enlightening the association between microbiome composition and environment properties or host phenotypes. The beta-diversity analysis mainly relies on distances among microbiomes that are calculated by all microbial features. However, in some cases, only a small fraction of members in a community plays crucial roles. Such tiny proportion is insufficient to alter the overall distance, which is always missed by end-to-end comparison...

MOTIVATION: Reconstructing and analyzing all blood vessels throughout the brain is significant for understanding brain function, revealing the mechanisms of brain disease, and mapping the whole-brain vascular atlas. Vessel segmentation is a fundamental step in reconstruction and analysis. The whole-brain optical microscopic imaging method enables the acquisition of whole-brain vessel images at the capillary resolution. Due to the massive amount of data and the complex vascular features generated by high-resolution whole-brain imaging, achieving rapid and accurate segmentation of whole-brain vasculature becomes a challenge...

MOTIVATION: Finding outliers in RNA Sequencing (RNA-Seq) gene expression (GE) can help in identifying genes that are aberrant and cause Mendelian disorders. Recently developed models for this task rely on modeling RNA-Seq GE data using the Negative Binomial distribution (NBD). However, some of those models either rely on procedures for inferring NBD's parameters in a non-biased way that are computationally demanding, and thus make confounder control challenging, while others rely on less computationally demanding but biased procedures and convoluted confounder control approaches that hinder interpretability...

MOTIVATION: Feature-based counting is commonly used in RNA-sequencing (RNA-seq) analyses. Here, sequences must align to target features (like genes or non-coding RNAs) and related sequences with different compositions are counted into the same feature. Consequently, sequence integrity is lost, making results less traceable against raw data. IMPLEMENTATION: Small RNA (sRNA) often maps to multiple features and shows an incredible diversity in form and function. Therefore, applying feature-based strategies may increase the risk of misinterpretation...

SUMMARY: Data integration workflows for multiomics data take many forms across academia and industry. Efforts with limited resources often encountered in academia can easily fall short of data integration best practices for processing and combining high content imaging, proteomics, metabolomics and other omics data. We present Phenonaut, a Python software package designed to address the data workflow needs of migration, control, integration, and auditability in the application of literature and proprietary techniques for data source and structure agnostic workflow creation...

MOTIVATION: Deep learning attained excellent results in Digital Pathology recently. A challenge with its use is that high quality, representative training data sets are required to build robust models. Data annotation in the domain is labor intensive and demands substantial time commitment from expert pathologists. Active Learning (AL) is a strategy to minimize annotation. The goal is to select samples from the pool of unlabeled data for annotation that improves model accuracy. However, AL is a very compute demanding approach...

MOTIVATION: Accurate power and sample size estimation is crucial to the design and analysis of genetic association studies. When analyzing a binary trait via logistic regression, important covariates such as age and sex are typically included in the model. However, their effects are rarely properly considered in power or sample size computation during study planning. Unlike when analyzing a continuous trait, the power of association testing between a binary trait and a genetic variant depends, explicitly, on covariate effects, even under the assumption of gene-environment independence...

SUMMARY: To allow the comprehensive histological analysis of the whole intestine, it is often rolled to a spiral before imaging. This Swiss-rolling technique facilitates robust experimental procedures, but it limits the possibilities to comprehend changes along the intestine. Here, we present IntestLine, a Shiny-based open-source application for processing imaging data of (rolled) intestinal tissues and subsequent mapping onto a line. The visualization of the mapped data facilitates the assessment of the whole intestine in both proximal-distal and serosa-luminal axis, and enables the observation of location-specific cell types and markers...

SUMMARY: Microbial secondary metabolites exhibit potential medicinal value. A large number of secondary metabolite biosynthetic gene clusters (BGCs) in the human gut microbiome, which exhibit essential biological activity in microbe-microbe and microbe-host interactions, have not been adequately characterised, making it difficult to prioritise these BGCs for experimental characterization. Here, we present the sBGC-hm, an atlas of secondary metabolite BGCs allows researchers to explore the potential therapeutic benefits of these natural products...

SUMMARY: Founder populations with deep genealogical data are well suited for investigating genetic variants contributing to diseases. Here, we present a major update of the genealogical analysis R package GENLIB, centered around a new function which can simulate the transmission of haplotypes from founders to probands along very large and complex user-specified genealogies. AVAILABILITY AND IMPLEMENTATION: The latest update of the GENLIB package (v1.1.9) contains the new gen...

MOTIVATION: The integration of single-cell multi-omics data can uncover the underlying regulatory basis of diverse cell types and states. However, contemporary methods disregard the omics individuality, and the high noise, sparsity, and heterogeneity of single-cell data also impact the fusion effect. Furthermore, available single-cell clustering methods only focus on the cell type clustering, which can not mine the alternative clustering to comprehensively analyze cells. RESULTS: We propose a single-cell data fusion based multiple clustering (scMCs) approach that can jointly model single-cell transcriptomics and epigenetic data, and explore multiple different clusterings...

MOTIVATION: Efficient tapping into genomic information from a single microscopic image of an intact DNA molecule is an outstanding challenge and its solution will open new frontiers in molecular diagnostics. Here, a new computational method for optical genome mapping utilizing Deep Learning is presented, termed DeepOM. Utilization of a Convolutional Neural Network (CNN), trained on simulated images of labeled DNA molecules, improves the success rate in alignment of DNA images to genomic references...

MOTIVATION: Advances in RNA sequencing technologies have achieved an unprecedented accuracy in the quantification of mRNA isoforms, but our knowledge of isoform-specific functions has lagged behind. There is a need to understand the functional consequences of differential splicing, which could be supported by the generation of accurate and comprehensive isoform-specific Gene Ontology (GO) annotations. RESULTS: We present Isopret (Isoform Interpretation), a method that uses expectation-maximization to infer isoform specific functions based on the relationship between sequence and functional isoform similarity...