cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/101003
title: Genomic data of the Crested Ibis (<em>Nipponia nippon</em>).

description: The Crested Ibis (<em>Nipponia nippon </em> (Temminck, 1855)) is the only member of the genus Nipponia and also known as the Japanese Crested Ibis (Toki). Originally widespread across China, Japan, Korea, Taiwan and Russia, by 1988 the species had disappeared from nearly all these places, except two surviving breeding pairs in Southern Qinling mountains of Yangxian County, China.<br> 
DNA was collected from a female that descended from one of these pairs, belonging to a population now rescued from near extinction. We sequenced the 1.6 Gb genome to a depth of approximately 105X with short reads from a series of libraries with various insert sizes (170bp, 500bp, 800bp, 2kb, 5kb, 10kb and 20kb). <br>
The assembled scaffolds of high quality sequences totaled 1.17 Gb, with the contig and scaffold N50 values of 22kb and 5.4Mb respectively. We identified 16,756 protein-coding genes with a mean length of 19.4 kb.
DOI: 10.6084/m9.figshare.17025506.v4
title: A draft genome assembly of the Atlantic chub mackerel (Scomber colias) using Illumina and Pacbio Hifi reads

description: Supporting data for "A draft genome assembly of the Atlantic chub mackerel (Scomber colias) using Illumina and Pacbio Hifi reads"
DOI: 10.5524/100926
title: Supporting data for "Vulcan: Improved long-read mapping and structural variant calling via dual-mode alignment"

description: Long-read sequencing has enabled unprecedented surveys of structural variation across the entire human genome. To maximize the potential of long-read sequencing in this context, novel mapping methods have emerged that have primarily focused on either speed or accuracy. Various heuristics and scoring schemas have been implemented in widely used read mappers (minimap2 and NGMLR) to optimize for speed or accuracy, which have variable performance across different genomic regions and for specific structural variants. Our hypothesis is that constraining read mapping to the use of a single gap penalty across distinct mutational hotspots reduces read alignment accuracy and impedes structural variant detection.<br> We tested our hypothesis by implementing a read mapping pipeline called Vulcan that uses two distinct gap penalty modes, which we refer to as dual-mode alignment. The high-level idea is that Vulcan leverages the computed normalized edit distance of the mapped reads via e.g. minimap2 to identify poorly aligned reads and realigns them using the more accurate yet computationally more expensive long read mapper (NGMLR). In support of our hypothesis, we show Vulcan improves the alignments for Oxford Nanopore Technology (ONT) long-reads for both simulated and real datasets. These improvements, in turn, lead to improved accuracy for structural variant calling performance on human genome datasets compared to either of the read mapping methods alone. <br>Vulcan is the first long-read mapping framework that combines two distinct gap penalty modes, resulting in improved structural variant recall and precision. Vulcan is open-source and available under the MIT License at https://gitlab.com/treangenlab/vulcan<br><br><br>PLEASE NOTE: Most fo the files associated with this dataset are hosted in cold storage, please contact us via email with the details of the dataset and any particular files you would like to download, and we will be happy to make those available to you.<br>
DOI: 10.5524/100950
title: Supporting data for "Fungal and ciliate protozoa are the main rumen microbes associated with methane emissions in dairy cattle"

description: Mitigating the effects of global warming has become the main challenge for humanity in the last decades. Livestock farming contributes to greenhouse gas emissions, with an important output of methane from enteric fermentation processes, mostly in ruminants. As ruminal microbiota is directly involved in digestive fermentation processes and methane biosynthesis, understanding the ecological relationships between rumen microorganisms and their active metabolic pathways is essential for reducing emissions. This study analyzed whole rumen metagenome using long reads and considering its compositional nature in order to disentangle the role of rumen microbes in methane emissions. <br>The beta-diversity analyses suggested an association between methane production and overall microbiota composition (0.01 &lt; R2 &lt; 0.02). Differential abundance analysis identified 36 genera and 279 KEGGs as significantly associated with methane production (Padj&lt;0.05). Those genera associated to high methane production were Eukaryota from Alveolata and Fungi clades, while Bacteria were associated to low methane emissions. The genus-level association network showed two clusters grouping Eukaryota and Bacteria, respectively. Regarding microbial gene functions, 41 KEGGs resulted to be differentially abundant between low and high emission animals, and were mainly involved in metabolic pathways. No KEGGs included in the methane metabolism pathway (ko00680) were detected as associated to high methane emissions. The KEGG network showed three clusters grouping KEGGs associated to high emissions, low emissions and not differentially abundant in either of them. A deeper analysis of the differentially abundant KEGGs revealed that genes related with anaerobic respiration through nitrate degradation were more abundant in low emissions animals. <br>Methane emissions are largely associated to the relative abundance of ciliate and fungi. The role of nitrate electron acceptors can be particularly important as this respiration mechanism directly competes with methanogenesis. Therefore, whole metagenome sequencing is necessary to jointly consider relative abundance of Bacteria, Archaea and Eukaryota in the statistical analyses. Nutritional and genetic strategies to reduce CH4 emissions should focus on reducing the relative abundance of Alveolata and Fungi in the rumen. This experiment has generated the largest ONT ruminal metagenomic dataset currently available.
DOI: 10.5524/100951
title: Supporting data for "A reference genome for the critically endangered woylie, Bettongia penicillata ogilbyi"

description: Biodiversity is declining globally, and Australia has one of the worst extinction records for mammals. Development of sequencing technologies has opened genomics to wildlife, which is an important tool for conservation and management. Despite this, only 5% of threatened Australian species currently have a genome available through NCBI. Here we report the first reference genome for the woylie (<i>Bettongia penicillata ogilbyi</i>), a critically endangered marsupial from Western Australia, and the first genome within the Potoroidae family. The woylie reference genome was generated using PacBio HiFi long-reads, resulting in a 3.39Gb assembly with a scaffold N50 of 6.49Mb and 86.5% complete mammalian BUSCOs. Assembly of a global transcriptome from pouch skin, tongue, heart and blood RNAseq reads was used to guide annotation with Fgenesh++, resulting in the annotation of 24,655 genes. The woylie reference genome is a valuable resource for conservation, management and investigations into disease-induced decline of this critically endangered marsupial.
DOI: 10.5524/100956
title: Supporting data for "Multi-dimensional leaf phenotypes reflect root system genotype in grafted grapevine over the growing season"

description: Modern biological approaches generate volumes of multi-dimensional data, offering unprecedented opportunities to address biological questions previously beyond reach due to small or subtle effects. A fundamental question in plant biology is the extent to which below-ground activity in the root system influences above-ground phenotypes expressed in the shoot system. Grafting, an ancient horticultural practice that fuses the root system of one individual (the rootstock) with the shoot system of a second, genetically distinct individual (the scion), is a powerful experimental system to understand below-ground effects on above-ground phenotypes. Previous studies on grafted grapevines have detected rootstock influence on scion phenotypes including physiology and berry chemistry. However, the extent of the rootstocks influence on leaves, the photosynthetic engines of the vine, and how those effects change over the course of a growing season, are still largely unknown.<br>Here, we investigate associations between rootstock genotype and shoot system phenotypes using five multi-dimensional leaf phenotyping modalities measured in a common grafted scion: ionomics, metabolomics, transcriptomics, morphometrics, and physiology. Rootstock influence is ubiquitous but subtle across modalities with the strongest signature of rootstock observed in the leaf ionome. Moreover, we find that the extent of rootstock influence on scion phenotypes and patterns of phenomic covariation are highly dynamic across the season.<br>These findings substantially expand previously identified patterns to demonstrate that rootstock influence on scion phenotypes is complex and dynamic and underscore that broad understanding necessitates volumes of multi-dimensional data previously unmet.
DOI: 10.5524/100957
title: Supporting data for "Chromosome-level genome assembly of the shuttles hoppfish, <i>Periophthalmus modestus</i>"

description: The shuttles hoppfish (mudskipper), <i>Periophthalmus modestus</i>, is one of a number of mudskippers which are the largest group of amphibious teleost fishes that are uniquely adapted to live on mudflats. Since mudskippers can survive on land for extended periods of time by breathing through their skin and through the lining of the mouth and throat, they were evaluated as a model for the evolutionary sea-land transition of Devonian protoamphibians, ancestors of all present tetrapods. <br>A total of 39.6, 80.2 and 52.9 Gbp of Illumina, PacBio and Hi-C data, respectively, was assembled into 1,419 scaffolds with a N50 length of 33 Mbp and BUSCO score of 96.3%. The assembly covered 117% of the estimated genome size (729 Mbp) while the top 23 longest scaffolds were above 20 Mbp in size and close to the estimated one. Of the genome, 43.8% were various repetitive elements such as DNAs, tandem repeats, LINEs and simple repeats. <i>Ab initio</i> and homology-based gene prediction identified 30,505 genes, of which 94% had homology to the 14 Actinopterygiit ranscriptomes and 89% and 85% did Pfam familes and InterPro domains respectively. Comparative genomics with 15 Actinopterygii species identified 59,448 gene families of which 12% were only in <i>P.modestus</i>. <br>We present the high quality of the first genome assembly and gene annotation of the shuttles hoppfish. It will provide a valuable resource for further studies on sea-land transition, bimodal respiration, nitrogen excretion, osmoregulation, thermoregulation, vision and mechanoreception
DOI: 10.5524/100960
title: Supporting data for "Interpretable network-guided epistasis detection"

description: Detecting epistatic interactions at the gene level is essential to understanding the biological mechanisms of complex diseases. Unfortunately, genome-wide interaction association studies (GWAIS) involve many statistical challenges that make such detection hard. We propose a multi-step protocol for epistasis detection along the edges of a gene-gene co-function network. Such an approach reduces the number of tests performed and provides interpretable interactions, while keeping type I error controlled. Yet, mapping gene-interactions into testable SNP-interaction hypotheses, as well as computing gene pair association scores from SNP pair ones, is not trivial. Here we compare three SNP-gene mappings (positional overlap, eQTL and proximity in 3D structure) and use the adaptive truncated product method to compute gene pair scores. This method is non-parametric, does not require a known null distribution, and is fast to compute. We apply multiple variants of this protocol to a GWAS inflammatory bowel disease (IBD) dataset. Different configurations produced different results, highlighting that various mechanisms are implicated in IBD, while at the same time, results overlapped with known disease biology. Importantly, the proposed pipeline also differs from a conventional approach were no network is used, showing the potential for additional discoveries when prior biological knowledge is incorporated into epistasis detection.
DOI: 10.5524/100963
title: Supporting data for "NiemaGraphGen: A memory-efficient global-scale contact network simulation toolkit"

description: Epidemic simulations require the ability to sample contact networks from various random graph models. Existing methods can simulate city-scale or even country-scale contact networks, but they are unable to feasibly simulate global-scale contact networks due to high memory consumption. <br>NiemaGraphGen (NGG) is a memory-efficient graph generation tool that enables the simulation of global-scale contact networks. NGG avoids storing the entire graph in memory and is instead intended to be used in a data streaming pipeline, resulting in memory consumption that is orders of magnitude smaller than existing tools. <br>NGG provides a massively-scalable solution for simulating social contact networks, enabling global-scale epidemic simulation studies.
DOI: 10.5524/100964
title: Supporting data for "Halvade Somatic: Somatic Variant Calling with Apache Spark"

description: The accurate detection of somatic variants from sequencing data is of key importance for cancer treatment and research. Somatic variant calling requires a high sequencing depth of the tumor sample, especially when also the detection of low-frequency variants is desired. In turn, this leads to large volumes of raw sequencing data to process and hence, large computational requirements. For example, calling the somatic variants according to the GATK best practices guidelines requires days of computing time for a typical whole genome sequencing sample. <br>We introduce Halvade Somatic, a framework for somatic variant calling from DNA sequencing data that takes advantage of multi-node and/or multi-core compute platforms to reduce runtime. It relies on Apache Spark to provide scalable I/O and to create and manage data streams that are processed on different CPU cores in parallel. Halvade Somatic contains all required steps to process the tumor and matched normal sample according to the GATK best practices recommendations: read alignment (BWA), sorting of reads, preprocessing steps such as marking duplicate reads and base quality score recalibration (GATK) and finally, calling the somatic variants (Mutect2). Our approach reduces the runtime on a single 36-core node to 19.5h compared to a runtime of 84.5h for the original pipeline, a speedup of 4.3x. Runtime can be further decreased by scaling to multiple nodes while retaining a high parallel efficiency, e.g., we observe a runtime of 1h 21min using 16 nodes, an additional speedup of 14.4x. The somatic variants called by Halvade Somatic match those obtained by the original GATK/Mutect2 pipeline to a very high degree. Halvade Somatic supports variant calling from both whole genome sequencing (WGS) as well as whole exome sequencing (WES) data and also supports Strelka2 as an alternative or complementary variant calling tool within its pipeline. We provide a Docker image to facilitate single node deployment. Halvade Somatic can be executed on a wide variety of compute platforms, including the Amazon EC2 and Google Cloud. <br>Halvade Somatic is the first somatic variant calling pipeline that leverages big data processing platforms and provides reliable, scalable performance. Source code is freely available.
DOI: 10.5524/100967
title: Supporting data for "MBGC: Multiple Bacteria Genome Compressor"

description: Genomes within the same species reveal large similarity, exploited by specialized multiple genome compressors. The existing algorithms and tools are however targeted at large, e.g., mammalian, genomes, and their performance on bacteria strains is rather moderate. <br>In this work, we propose MBGC, a specialized genome compressor making use of specific redundancy of bacterial genomes. Its characteristic features are finding both direct and reverse-complemented LZ-matches, as well as a careful management of a reference buffer in a multi-threaded implementation. Our tool is not only compression efficient, but also fast. On a collection of 168,311 bacterial genomes, totalling 587GB, we achieve the compression ratio around the factor of 1265, and the compression (resp. decompression) speed around 1580MB/s (resp. 780MB/s) using 8 hardware threads, on a computer with a 14-core / 28-thread CPU and a fast SSD, being almost 3 times more succinct and over 6 times faster in the compression than the next best competitor.
DOI: 10.5524/100974
title: Supporting data for "Assessing species coverage and assembly quality of rapidly accumulating sequenced genomes"

description: Ambitious initiatives to coordinate genome sequencing of Earths biodiversity mean that the accumulation of genomic data is growing rapidly. In addition to cataloguing biodiversity, these data provide the basis for understanding biological function and evolution. Accurate and complete genome assemblies offer a comprehensive and reliable foundation upon which to advance our understanding of organismal biology at genetic, species, and ecosystem levels. However, ever-changing sequencing technologies and analysis methods mean that available data are often heterogeneous in quality. In order to guide forthcoming genome generation efforts and promote efficient prioritisation of resources, it is thus essential to define and monitor taxonomic coverage and quality of the data. <br>Here we present an automated analysis workflow that surveys genome assemblies from the United States National Center for Biotechnology Information (NCBI), assesses their completeness using the relevant Benchmarking Universal Single-Copy Orthologue (BUSCO) datasets, and collates the results into an interactively browsable resource. We apply our workflow to produce a community resource of available assemblies from the phylum Arthropoda, the Arthropoda Assembly Assessment Catalogue. Using this resource, we survey current taxonomic coverage and assembly quality at the NCBI, we examine how key assembly metrics relate to gene content completeness, and we compare results from using different BUSCO lineage datasets. <br>These results demonstrate how the workflow can be used to build a community resource that enables large-scale assessments to survey species coverage and data quality of available genome assemblies, and to guide prioritisations for ongoing and future sampling, sequencing, and genome generation initiatives
DOI: 10.5524/100975
title: Supporting data for "NETMAGE: A Human Disease Phenotype Map Generator for the Network-based Visualization of PheWAS Results"

description: Disease complications, the onset of secondary phenotypes given a primary condition, can exacerbate the long-term severity of outcomes. However, the exact cause of many of these cross-phenotype associations is still unknown. One potential reason is shared genetic etiology - common genetic drivers may lead to the onset of multiple phenotypes. A holistic, network-based view incorporating knowledge of other diseases and genetic associations will be required to uncover the exact basis of disease complications. Disease-disease networks (DDNs), where nodes represent diseases and edges represent associations between diseases, can provide an intuitive way of understanding the relationships between phenotypes. Using summary statistics from a phenome-wide association study (PheWAS), we can generate a corresponding DDN where edges represent shared single-nucleotide polymorphisms (SNPs) between diseases. Such a network can help us analyze genetic associations across the diseasome, the landscape of all human diseases, and identify potential genetic influences for disease complications. <br>To improve the ease of network-based analysis of shared genetic components across phenotypes, we developed the humaN disEase phenoType MAp GEnerator (NETMAGE), a web-based tool that produces interactive DDN visualizations from PheWAS summary statistics. Users can search the map by various attributes and select nodes to view related phenotypes, associated SNPs, and various network statistics. As a test case, we used NETMAGE to construct a network from UK BioBank (UKBB) PheWAS summary statistic data. Our map correctly displayed previously identified disease comorbidities from the UKBB and identified concentrations of hub diseases in the endocrine/metabolic and circulatory disease categories. By examining the associations between phenotypes in our map, we can identify potential genetic explanations for the relationships between diseases and better understand the underlying architecture of the human diseasome. Our tool thus provides researchers with a means to identify prospective genetic targets for drug design, using network medicine to contribute to the exploration of personalized medicine.
DOI: 10.6084/m9.figshare.13200953.v1
title: 2017 Leaf Shape Data

description: This data set contains zip archives of image scans and CSV files containing the 17-point landmarking system for grapevine morphometric analysis devised by Chitwood 2014. Code for the analysis of landmarks along with any necessary metadata are provided on GitHub at: [].
DOI: 10.6084/m9.figshare.13200980.v1
title: 2017 Ionomics Data

description: This data set contains the ionomic profile of nearly 2600 leaves spanning three phenological stages, three shoot positions, three irrigation treatments, and four rootstock/grafting treatments. Experimental metadata are contained in the data set.
DOI: 10.6084/m9.figshare.13201016.v1
title: 2017 Physiology Data

description: This data set contains the four physiological traits measured in 2017 in addition to soil moisture used to understand the irrigation treatment in the vineyard. Experimental metadata can be found on GitHub at [].
DOI: 10.6084/m9.figshare.13201043.v1
title: 2017 Metabolomics Data

description: This data sets contains the cleaned data from XCMS Online following LC-MS on grapevine leaf metabolite extractions. The experimental design covers two phenological stages, three irrigation treatments, and four rootstock/grafting treatments. Experimental metadata are contained in the data set.