cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/100733
title: Supporting data for "MaRe: Processing Big Data with Application Containers on Apache Spark"

description: Life science is increasingly driven by Big Data analytics, and the MapReduce programming model has been proven successful for data-intensive analyses. However, current MapReduce frameworks offer poor support for reusing existing processing tools in bioinformatics pipelines. Further, these frameworks do not have native support for application containers, which are becoming popular in scientific data processing. Here we present MaRe, an open-source programming library which introduces support for Docker containers in Apache Spark. Apache Spark and Docker are the MapReduce framework and container engine that have collected the largest open source community, thus MaRe provides interoperability with the cutting-edge software ecosystem. We demonstrate MaRe on two data-intensive applications in life science, showing ease of use and scalability. MaRe enables scalable data-intensive processing in life science with Apache Spark and application containers. When compared with current best practices, that involve the use of workflow systems, MaRe has the advantage of providing data locality, ingestion from heterogeneous storage systems and interactive processing. MaRe is generally-applicable and available as open source software.
DOI: 10.5524/100736
title: Supporting data for "A catalog of microbial genes from the bovine rumen unveils a specialized and diverse biomass-degrading environment"

description: The rumen microbiota provides essential services to its host and, through its role in ruminant production, contributes to human nutrition and food security. A thorough knowledge of the genetic potential of rumen microbes will provide opportunities for improving the sustainability of ruminant production systems. The availability of gene reference catalogs from gut microbiomes has advanced the understanding of the role of the microbiota in health and disease in humans and other mammals. In this work, we established a catalog of reference prokaryote genes from the bovine rumen. <br>Using deep metagenome sequencing we identified 13,825,880 non-redundant prokaryote genes from the bovine rumen. Compared to human, pig and mouse gut metagenome catalogs, the rumen is larger and richer in functions and microbial species associated with the degradation of plant cell wall material and production of methane. Genes encoding enzymes catalyzing the breakdown of plant polysaccharides showed a particularly high richness that is otherwise impossible to infer from available genomes or shallow metagenomics sequencing. The catalog expands the dataset of carbohydrate-degrading enzymes described in the rumen. Using an independent dataset from a group of 77 cattle fed 4 common dietary regimes, we found that only &lt;0.1% of genes were shared by all animals, which contrast with a large overlap for functions, i.e. 63% for KEGG functions. Different diets induced differences in the relative abundance rather than the presence or absence of genes, which explains the great adaptability of cattle to rapidly adjust to dietary changes. <br>These data bring new insights into functions, carbohydrate-degrading enzymes and microbes of the rumen that is complementing the available information on microbial genomes. The catalog is a significant biological resource enabling deeper understanding of phenotypes and biological processes and will be expanded as new data is made available.
DOI: 10.5524/100737
title: Supporting data for "Reduced chromatin accessibility underlies gene expression differences in homologous chromosome arms of diploid Aegilops tauschii and hexaploid wheat"

description: Polyploidy is centrally important in the evolution and domestication of plants as it leads to major genomic-scale changes, such as altered patterns of gene expression, which are thought to underlie the emergence of new traits. Despite the common occurrence of these globally altered patterns of gene expression in polyploids, the mechanisms involved are currently not well understood.<br> Using a precisely defined framework of highly conserved syntenic genes on hexaploid wheat chromosome 3DL and its progenitor 3L chromosome arm of diploid <i>Aegilops tauschii</i>, we show that 70% of these gene pairs exhibited proportionately reduced gene expression, in which expression in the hexaploid context of the 3DL genes was approximately 40% of the levels observed in diploid <i>Ae. tauschii.</i>Approximately 30% of genes were differentially expressed, including several genes with elevated expression during the later stages of grain development in wheat compared to <i>Ae. tauschii</i>. Gene sequence and methylation differences accounted for approximately 11% of the differences in gene expression. In contrast, over 80% of genes with differential expression exhibited altered patterns of chromatin accessibility of genes in the hexaploid chromosome arm compared to its diploid progenitor. An overall reduction in chromatin accessibility across regulatory regions of genes was observed in the hexaploid context compared to the diploid <i>Ae. tauschii</i> context. <br>These chromosome arm analyses show that differential chromatin accessibility may underlie differences in gene expression in hexaploid chromosome arm of wheat compared to its diploid progenitor chromosome arm.
DOI: 10.5524/100761
title: Supporting data for "Graph2GO: a multi-modal attributed network embedding method for inferring protein functions"

description: Identifying protein functions is important for many biological applications. Since experimental functional characterization of proteins is time-consuming and costly, accurate and efficient computational methods for predicting protein functions are in great demand for generating testable hypotheses guiding large-scale experiments. Here we proposed Graph2GO, a multi-modal graph-based representation learning model that can integrate heterogeneous information including multiple types of interaction networks (sequence similarity network and protein-protein interaction network) and protein features (amino acid sequence, subcellular location and protein domains) to predict protein functions on Gene Ontology. Comparing Graph2GO to BLAST, a baseline model and two popular protein function prediction methods: Mashup and deepNF, we demonstrated that our model can achieve state-of-the-art performance. We show the robustness of our model by testing on multiple species. We also provide a web server supporting function query and downstream analysis on-the-fly. Graph2GO is the first model that utilized attributed network representation learning methods to model both interaction networks and protein features for predicting protein functions, and achieved promising performance. Our model can be easily extended to include more protein features to further improve the performance. Besides, Graph2GO is also applicable to other application scenarios involving biological networks and the learned latent representations can be used as feature inputs for machine learning tasks in various downstream analysis.
DOI: 10.5524/100765
title: Supporting data for "The intersectional genetics landscape for human"

description: The human body is made up of hundreds, perhaps thousands of cell types and states, most of which are currently inaccessible genetically. Genetic accessibility carries significant diagnostic and therapeutic potential by allowing the selective delivery of genetic messages or cures to cells. Research in model organisms has shown that single regulatory element (RE) activities are seldom cell-type specific, limiting their usage in genetic systems designed to restrict gene expression posteriorly to their delivery to cells. Intersectional genetic approaches can theoretically increase the number of genetically accessible cells, but the scope and safety of these approaches to humans have not been systematically assessed due primarily to the lack of suitable thorough RE activity databases and methods to explore them. A typical intersectional method acts like an AND logic gate by converting the input of two or more active REs into a single synthetic output, which becomes unique for that cell. Here, we systematically assessed the intersectional genetics landscape of the human genome using a curated subset of cells from a large RE usage atlas obtained by Cap Analysis of Gene Expression sequencing (CAGE-seq) of thousands of primary and cancer cells (the FANTOM5 consortium atlas). We developed the heuristics and algorithms to retrieve AND gate intersections and quality-rank them intra- and inter-individually. We find that &gt;90% of the 154 primary cell types surveyed can be distinguished from each other with as little as 3 to 4 active REs, with quantifiable safety and robustness. We call these minimal intersections of active REs with cell-type diagnostic potential "Versatile Entry Codes" (VEnCodes). Each of the 158 cancer cell types surveyed could also be distinguished from the healthy primary cell types with small VEnCodes, most of which were highly robust to intra- and inter-individual variation. Finally, we provide methods for the cross-validation of CAGE-seq-derived VEnCodes and for the extraction of VEnCodes from pooled single-cell sequencing data. Our work provides a systematic view of the intersectional genetics landscape in the human genome and demonstrates the potential of these approaches for future gene delivery technologies in humans.
DOI: 10.5524/100766
title: Supporting data for "EHRtemporalVariability: delineating temporal dataset shifts in electronic health records"

description: Temporal variability in healthcare processes or protocols is intrinsic to medicine. Such variability can potentially introduce dataset shifts, a data quality issue when reusing electronic health records (EHRs) for secondary purposes. Temporal dataset shifts can present as trends, as well as abrupt or seasonal changes in the statistical distributions of data over time. The latter are particularly complicated to address in multi-modal and highly coded data. These changes, if not delineated, can harm population and data-driven research, such as machine learning. Given that biomedical research repositories are increasingly being populated with large historical data from EHRs, there is a need for specific software methods to help delineate temporal dataset shifts to ensure reliable data reuse.<br>EHRtemporalVariability is an Open Source R-package and Shiny-app designed to explore and identify temporal dataset shifts. EHRtemporalVariability estimates the statistical distributions of coded and numerical data over time; projects their temporal-evolution through non-parametric Information Geometric Temporal plots; and enables the exploration of changes in variables through Data Temporal Heatmaps. We demonstrate the capability of EHRtemporalVariability to delineate dataset shifts in three impact case studies, one of them available for reproducibility.<br>EHRtemporalVariability enables the exploration and identification of dataset shifts, contributing to the broad examination and repurposing of large, longitudinal datasets. Our goal is to help ensure reliable data reuse for a wide range of biomedical data users. EHRtemporalVariability is designed for technical users who are programmatically utilizing the R-package, as well as users who are not familiar with programming via the Shiny user interface.
DOI: 10.5524/100768
title: Supporting data for "PhaseME: automatic rapid assessment of phasing quality and phasing improvement"

description: The detection of what mutations are occurring on the same DNA molecule is essential to predict their consequences. This can be achieved by phasing the genomic variations. Nevertheless, state-of-the-art haplotype phasing is currently a black box in which the accuracy and quality of the reconstructed haplotypes are hard to assess.<br>Here we present PhaseME, a versatile method to provide insights into and improvement of sample phasing results based on linkage data. We showcase the performance and the importance of PhaseME by comparing phasing information obtained from Pacific Biosciences (PacBio) including both CLR (continuous long reads) and HiFi (high-quality consensus reads), Oxford Nanopore Technologies (ONT) and 10Xgenomics sequencing technologies. We found that 10Xgenomics and ONT phasing can be significantly improved while retaining a high N50 and completeness. PhaseME generates reports and summary plots to provide insights into phasing performance and correctness. We observed unique phasing issues for each of the sequencing technologies, highlighting the necessity of quality assessments. PhaseME is able to decrease the Hamming error rate significantly by 26.2% averaged across all four technologies. Additionally, a significant improvement is obtained in the number of long switch errors especially for HiFi 54.6% with only a 5% decrease in phase block N50.<br>PhaseME is a universal method to assess the phasing quality and accuracy and improves the quality of phasing using linkage information. The package is freely available at in GitHub.
DOI: 10.5281/zenodo.3251033
title: Draft genome assemblies of killifish from the Fundulus genus with ONT and Illumina sequencing platforms

description: Four species from the genus Fundulus were selected for genome sequencing to study the physiological and genetic mechanisms that diverge between euryhaline and stenohaline freshwater species within this cyprinodontiform order of ray-finned fishes.
DOI: 10.5524/100728
title: Supporting data for "Artifact-free whole-slide imaging with structured illumination microscopy and Bayesian image reconstruction"

description: Structured illumination microscopy (SIM) is a method which can be used to image biological samples and can achieve both optical sectioning and super-resolution effects. Optimization of the imaging setup and data processing methods results in high quality images without artifacts due to mosaicking or due to the use of SIM methods. Reconstruction methods based on Bayesian estimation can be used to produce images with a resolution beyond that dictated by the optical system. Five complete datasets are presented including large panoramic SIM images of human tissues in pathophysiological conditions. Cancers of the prostate, skin, ovary, and breast, as well as tuberculosis of the lung, were imaged using SIM. The samples are available commercially and are standard histological preparations stained with hematoxylin and eosin. The use of fluorescence microscopy is increasing in histopathology. There is a need for methods which reduce artifacts when employing image stitching methods or optical sectioning methods such as SIM. Stitched SIM images produce results which may be useful for intraoperative histology. Releasing high quality, full slide images and related data will aid researchers in furthering the field of fluorescent histopathology.
DOI: 10.5524/100731
title: Supporting data for "Sequencing smart: De novo sequencing and assembly approaches for a non-model mammal."

description: Whilst much sequencing effort has focused on key mammalian model organisms such as mouse and human, little is known about the correlation between genome sequencing techniques for non-model mammals and genome assembly quality. This is especially relevant to non-model mammals, where the samples to be sequenced are often degraded and low quality. A key aspect when planning a genome project is the choice of sequencing data to generate. This decision is driven by several factors, including the biological questions being asked, the quality of DNA available, and the availability of funds. Cutting-edge sequencing technologies now make it possible to achieve highly contiguous, chromosome-level genome assemblies, but relies on good quality high-molecular-weight DNA. The funds to generate and combine these data are often only available within large consortiums and sequencing initiatives, and are often not affordable for many independent research groups. For many researchers, value-for-money is a key factor when considering the generation of genomic sequencing data. Here we use a range of different genomic technologies generated from a roadkill European Polecat (Mustela putorius) to assess various assembly techniques on this low-quality sample. We evaluated different approaches for de novo assemblies and discuss their value in relation to biological analyses. <br>Generally, assemblies containing more data types achieved better scores in our ranking system. However, when accounting for misassemblies, this was not always the case for Bionano and low-coverage 10x Genomics (for scaffolding only). We also find that the extra cost associated with combining multiple data types is not necessarily associated with better genome assemblies.<br>The high degree of variability between each de novo assembly method (assessed from the seven key metrics) highlights the importance of carefully devising the sequencing strategy to be able to carry out the desired analysis. Adding more data to genome assemblies does not always results in better assemblies so it is important to understand the nuances of genomic data integration explained here, in order to obtain cost-effective value-for-money when sequencing genomes.
DOI: 10.5524/100740
title: Supporting data for "halSynteny: a fast, easy-to-use conserved synteny block construction method for multiple whole-genome alignments"

description: Large-scale sequencing projects provide high-quality full genome data that can be used for reconstruction of chromosomal exchanges and rearrangements that disrupt conserved syntenic blocks. The highest resolution of cross-species homology can be obtained based on whole-genome, reference-free alignments. Very large multiple alignments of full-genome sequences stored in a binary format demand an accurate and efficient computational approach for synteny blocks production.<br>halSynteny performs efficient processing of pairwise alignment blocks for any pair of genomes in the alignment. The tool is part of the HAL comparative genomics suite and is targeted to build synteny blocks for multi-hundred way, reference-free vertebrate alignments built with the Cactus system. <br>halSynteny enables an accurate and rapid identification of synteny in multiple full-genome alignments. The method is implemented in C++11 as a component of the halTools software and released under MIT license. The package is available at https://github.com/ComparativeGenomicsToolkit/hal/.
DOI: 10.5524/100745
title: Supporting data for "SnpHub: an easy-to-set-up web server framework for exploring large-scale genomic variation data in the post-genomic era with applications in wheat"

description: The cost of high-throughput sequencing is rapidly decreasing, allowing researchers to investigate genomic variations across hundreds or even thousands of samples in the post-genomic era. The management and exploration of these large-scale genomic variation data require programming skills. The public genotype querying databases of many species are usually centralized and implemented independently, making them difficult to update with new data over time. Currently, there is a lack of a widely used framework for setting up user-friendly web servers for exploring new genomic variation data in diverse species. <br>Here, we present SnpHub, a Shiny/R-based server framework for retrieving, analysing and visualizing the large-scale genomic variation data that can be easily set up on any Linux server. After a pre-building process based on the provided VCF files and genome annotation files, the local server allows users to interactively access SNPs/INDELs and annotation information by locus or gene and for user-defined sample sets through a webpage. Users can freely analyse and visualize genomic variations in heatmaps, phylogenetic trees, haplotype networks, or geographical maps. Samplespecific sequences can be accessed as replaced by SNPs/INDELs. SnpHub can be applied to any species, and we build up a SnpHub portal website for wheat and its progenitors based on published data in present studies. SnpHub and its tutorial are available as http://guoweilong.github.io/SnpHub.
DOI: 10.5524/100747
title: Supporting data for "Draft genome assemblies using sequencing reads from Oxford Nanopore Technology and Illumina platforms for four species of North American Fundulus killifish"

description: Whole genome sequencing data from wild-caught individuals of closely-related North American killifish species (<i>Fundulus xenicus</i>, <i>Fundulus catenatus</i>, <i>Fundulus nottii</i>, and <i>Fundulus olivaceus</i>) were obtained using long-read Oxford Nanopore Technology (ONT) PromethION and short-read Illumina platforms. <br>Draft <i>de novo</i> reference genome assemblies were generated using a combination of long and short sequencing reads. For each species, the PromethION platform was used to generate 30-45x sequence coverage, and the Illumina platform was used to generate 50- 160x sequence coverage. Illumina-only assemblies were fragmented with high numbers of contigs while ONT-only assemblies were error prone with low BUSCO scores. The highest N50 values, ranging from 0.4 Mb to 2.7 Mb, were from assemblies generated using a combination of short and long read data. BUSCO scores were consistently above 90% complete using the Eukaryota database. <br>Good quality genomes can be obtained from a combination of using short read Illumina data to polish assemblies generated with long read ONT data. Draft assemblies and raw sequencing data are available for public use. We encourage use and re-use of these data for assembly benchmarking and other analyses.
DOI: 10.5524/100748
title: Genome data for the draft assembly of the aquatic moss <i>Fontinalis antipyretica</i> (Fontinalaceae, Bryophyta)

description: Mosses compose one of the three lineages that form the sister group to extant vascular plants. Having emerged from an early split in the diversification of embryophytes, mosses may offer complementary insights into the evolution of traits following the transition to and colonization of land. To date, two nuclear genomes have been sequenced, namely the model taxon and acrocarpous moss <i>Physcomitrium patens</i>, and <i>Pleurozium schreberi</i> a representative of the diverse pleurocarpous hypnalean mosses. Here, we report the draft nuclear genome of <i>Fontinalis antipyretica</i> (Fontinalaceae, Hypnales), a charismatic aquatic moss widespread in temperate regions of the Northern Hemisphere. We sequenced and de novo assembled its genome using the 10X genomics method. The genome comprises 486.3 Mb, with a scaffold N50 of 38.8 kb. The assembly captured 89.4% of the 303 genes in the BUSCO eukaryote dataset. The newly generated F. antipyretica genome is the second genome of the highly speciose Hypnales, and provides the first opportunity for a comparative genomic study in this lineage that may have diversified after the rise of the angiosperms. It is also the second genome for a seedless aquatic plant, allowing for the assessment of independent genomic transformations linked to a reversed shift to an aquatic habitat.