cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/100866
title: Supporting data for "Twelve years of SAMtools and BCFtools"

description: SAMtools and BCFtools are widely used programs for processing and analysing high-throughput sequencing data. They include tools for file format conversion and manipulation, sorting, querying, statistics, variant calling and effect analysis amongst other methods. The first version appeared online twelve years ago and has been maintained and further developed ever since, with many new features and improvements added over the years. The SAMtools and BCFtools packages represent a unique collection of tools that have been used in numerous other software projects and countless genomic pipelines. Both SAMtools and BCFtools are freely available on GitHub under the permissive MIT licence, free for both non-commercial and commercial use. Both packages have been installed over a million times via Bioconda. The source code and documentation are available from https://www.htslib.org.
DOI: 10.5524/100822
title: Supporting data for "A Scalable Framework for Reproducible Processing of Volumetric, Nanoscale Neuroimaging Datasets"

description: Emerging neuroimaging datasets (collected with imaging techniques such as Electron Microscopy, Two-Photon Calcium Imaging, or X-ray Microtomography) describe the location and properties of neurons and their connections at an unprecedented scale, promising new ways of understanding the brain. These modern imaging techniques used to interrogate the brain can quickly accumulate gigabytes to petabytes of structural brain imaging data. Unfortunately, many neuroscience laboratories lack the computational resources to work with datasets of this size: computer vision tools are often not portable or scalable, and there is considerable difficulty in reproducing results or extending methods.<br>We developed an ecosystem of neuroimaging data analysis pipelines that utilize open-source algorithms to create standardized modules and end-to-end optimized approaches. As exemplars, we apply our tools to estimate synapse-level connectomes from electron microscopy data and cell distributions from X-ray microtomography data. To facilitate scientific discovery, we propose a generalized processing framework, that connects and extends existing open-source projects to provide large-scale data storage, reproducible algorithms, and workflow execution engines.<br>Our accessible methods and pipelines demonstrate that approaches across multiple neuroimaging experiments can be standardized and applied to diverse datasets. The techniques developed are demonstrated on neuroimaging datasets, but could equally be applied to similar problems in other domains.
DOI: 10.5524/100826
title: Supporting data for "BiG-SLiCE: A Highly Scalable Tool Maps the Diversity of 1.2 Million Biosynthetic Gene Clusters"

description: Genome mining for Biosynthetic Gene Clusters (BGCs) has become an integral part of natural product discovery. The &gt;200,000 microbial genomes now publicly available hold information on abundant novel chemistry. One way to navigate this vast genomic diversity is through comparative analysis of homologous BGCs, which allows identification of cross-species patterns that can be matched to the presence of metabolites or biological activities. However, current tools suffer from a bottleneck caused by the expensive network-based approach used to group these BGCs into Gene Cluster Families (GCFs).<br>Here, we introduce BiG-SLiCE, a tool designed to cluster massive numbers of BGCs. By representing them in Euclidean space, BiG-SLiCE can group BGCs into GCFs in a non-pairwise, near-linear fashion. We used BiG-SLiCE to analyze 1,225,071 BGCs collected from 209,206 publicly available microbial genomes and metagenome-assembled genomes (MAGs) within ten days on a typical 36-cores CPU server. We demonstrate the utility of such analyses by reconstructing a global map of secondary metabolic diversity across taxonomy to identify uncharted biosynthetic potential. BiG-SLiCE also provides a "query mode" that can efficiently place newly sequenced BGCs into previously computed GCFs, plus a powerful output visualization engine that facilitates user-friendly data exploration.<br> BiG-SLiCE opens up new possibilities to accelerate natural product discovery and offers a first step towards constructing a global, searchable interconnected network of BGCs. As more genomes get sequenced from understudied taxa, more information can be mined to highlight their potentially novel chemistry. BiG-SLiCE is available via https://github.com/medema-group/bigslice.
DOI: 10.5524/100831
title: Supporting data for "A new duck genome reveals conserved and convergently evolved chromosome architectures of birds and mammals"

description: Ducks have a typical avian karyotype that consists of macro- and micro-chromosomes, but a pair of much less differentiated ZW sex chromosomes compared to chicken. To elucidate the evolution of chromosome architectures between duck and chicken, and between birds and mammals, we produced a nearly complete chromosomal assembly of a female Pekin duck by combining long-read sequencing and multiplatform scaffolding techniques. The major improvement of genome assembly and annotation quality resulted from successful resolution of lineage-specific propagated repeats that fragmented the previous Illumina-based assembly. We found that the duck topologically associated domains (TAD) are demarcated by putative binding sites of the insulator protein CTCF, housekeeping genes, or transitions of active/inactive chromatin compartments, indicating the conserved mechanisms of spatial chromosome folding with mammals. There are extensive overlaps of TAD boundaries between duck and chicken, and also between the TAD boundaries and chromosome inversion breakpoints. This suggests strong natural selection on maintaining regulatory domain integrity, or vulnerability of TAD boundaries to DNA double-strand breaks. The duck W chromosome retains 2.5-fold more genes relative to chicken. Parallel to the independently evolved human Y chromosome, the duck W evolved massive dispersed palindromic structures, and a sequence divergence pattern with the Z chromosome that reflects stepwise suppression of homologous recombination. Our results provide novel insights into the conserved and convergently evolved chromosome features of birds and mammals, and also importantly add to the genomic resources for poultry studies.
DOI: 10.5524/100832
title: Supporting data for "Understanding the impact of preprocessing pipelines on neuroimaging cortical surface analyses"

description: The choice of preprocessing pipeline introduces variability in neuroimaging analyses that affects the reproducibility of scientific findings. Features derived from structural and functional MR imaging data are sensitive to the algorithmic or parametric differences of preprocessing tasks, such as image normalization, registration, and segmentation to name a few. Therefore it is critical to understand and potentially mitigate the cumulative biases of pipelines in order to distinguish biological effects from methodological variance. Here we use an open structural MR imaging dataset (ABIDE), supplemented with the Human Connectome Project (HCP), to highlight the impact of pipeline selection on cortical thickness measures. Specifically, we investigate the effect of 1) software tool (e.g. ANTs, CIVET, FreeSurfer), 2) cortical parcellation (DKT, Destrieux, Glasser), and 3) quality control procedure (manual, automatic). We divide our statistical analyses by 1) method type, i.e. task-free (unsupervised) versus task-driven (supervised), and 2) inference objective, i.e. neurobiological group differences versus individual prediction. Results show that software, parcellation, and quality control significantly impact task-driven neurobiological inference. Additionally, software selection strongly impacts neurobiological and individual task-free analyses, and quality control alters the performance for the individual-centric prediction tasks. This comparative performance evaluation partially explains the source of inconsistencies in neuroimaging findings. Furthermore, it underscores the need for more rigorous scientific workflows and accessible informatics resources to replicate and compare preprocessing pipelines to address the compounding problem of reproducibility in the age of large-scale, data-driven computational neuroscience.
DOI: 10.5524/100835
title: Supporting data for "Genome Diversity in Ukraine"

description: The main goal of this collaborative effort is to provide genome wide data for the previously underrepresented population in Eastern Europe, and to provide cross-validation of the data from genome sequences and genotypes of the same individuals acquired by different technologies. We collected 97 genome-grade DNA samples from consented individuals representing major regions of Ukraine that were consented for the public data release. DNBSEQ-G50 sequences, and genotypes by an Illumina GWAS chip were cross-validated on multiple samples, and additionally referenced to one sample that has been resequenced by Illumina NovaSeq6000 S4 at high coverage. The genome data has been searched for genomic variation represented in this population, and a number of variants have been reported: large structural variants, indels, CNVs, SNPs and microsatellites. This study provides the largest to-date survey of genetic variation in Ukraine, creating a public reference resource aiming to provide data for historic and medical research in a large understudied population. While most of the common variation is shared with other European populations, this survey of population variation contributes a number of novel SNPs and structural variants that have not been reported in the gnomAD/1KG databases representing global distribution of genomic variation. These endemic variants will become a valuable resource for designing future population and clinical studies, help address questions about ancestry and admixture, and will fill a missing place in the puzzle characterizing human population diversity in Eastern Europe. Our results indicate that genetic diversity of the Ukrainian population is uniquely shaped by the evolutionary and demographic forces, and cannot be ignored in the future genetic and biomedical studies. This data will contribute a wealth of new information bringing forth different risk and/or protective alleles. The newly discovered low frequency and local variants can be added to the current genotyping arrays for genome wide association studies, clinical trials, and in genome assessment of proliferating cancer cells.
DOI: 10.5524/100862
title: Supporting data for "X-ray microtomography-based atlas of mouse cranial development"

description: X-ray microtomography (CT) has become an invaluable tool for non-destructive analysis of biological samples in the field of developmental biology. Mouse embryos are a typical model for investigation of human developmental diseases. By obtaining 3-D high resolution scans of the mouse embryo heads, we gain valuable morphological information about the structures prominent in the development of future face, brain and sensory organs. The development of facial skeleton tracked in these CT data provides a valuable background for further studies of congenital craniofacial pathologies and normal development. In this work, re-usable tomographic data from 7 full 3-D scans of mouse embryo heads are presented and made publicly available. The ages of these embryos range from E12.5 to E18.5. The samples were stained by phosphotungstic acid prior to scanning, which greatly enhanced the contrast of various tissues in the reconstructed images and enabled precise segmentation. The images were obtained on a lab-based CT system. Furthermore, we provide manually segmented masks of mesenchymal condensations (for E12.5 and E13.5) and cartilage present in the nasal capsule of the scanned embryos. We present a comprehensive dataset of X-ray 3-D computed tomography images of the developing mouse head with high-quality manual segmentation masks of cartilaginous nasal capsules. The provided CT images can be used for studying any other major structure within the developing mouse heads. The high quality of the manually segmented models of nasal capsules may be instrumental to understand the complex process of the development of the face in mouse model.
DOI: 10.5524/100827
title: Supporting data for "High-quality chromosome-level genome assembly and full-length transcriptome analysis of the pharaoh ant <i>Monomorium pharaonis</i>"

description: Ants with complex societies have fascinated scientists for centuries. Comparative genomic and transcriptomic analyses across ant species and castes have revealed important insights into the molecular mechanisms underlying ant caste differentiation. However, most current ant genomes and transcriptomes are highly fragmented and incomplete, which hinders our understanding of the molecular basis for complex ant societies. By hybridizing Illumina, PacBio, and Hi-C sequencing technologies, we <i>de novo</i> assembled a chromosome-level genome for <i>Monomorium pharaonis</i>, with a scaffold N50 of 27.2 Mb. Our new assembly provides better resolution for the discovery of genome rearrangement events at the chromosome level. Analysis of full-length isoform sequencing (ISO-seq) suggested that ca. 15 Gb of ISO-seq data were sufficient to cover most expressed genes, but the number of transcript isoforms steadily increased with sequencing data coverage. Our high-depth ISO-seq data largely improved the quality of gene annotation and enabled the accurate detection of alternative splicing isoforms in different castes of <i>M. pharaonis</i>. Comparative transcriptome analysis across castes based on the ISO-seq data revealed an unprecedented number of transcript isoforms, including many caste-specific isoforms. We also identified a number of conserved long non-coding RNAs (lncRNAs) that evolved specifically in ant lineages and several that were conserved across insect lineages. We produced a high-quality chromosome-level genome for <i>M. pharaonis</i>, which significantly improved previous short-read assemblies. Together with full-length transcriptomes for all castes, we generated a highly accurate annotation for this ant species. These long-read sequencing results provide a useful resource for future functional studies on the genetic mechanisms underlying the evolution of social behaviors and organization in ants.
DOI: 10.5524/100829
title: A Shotgun Metagenomic study of 361 elderly women

description: Bone mass loss contributes to the risk of bone fracture in the elderly. Many factors including age, obesity, estrogen and diet, are associated with bone mass loss. Mice studies suggested that the gut microbiome might affect the bone mass by regulating the immune system, however there has been little evidence from human studies. <br>Bone loss increases after menopause. Thus, we have recruited 361 Chinese post-menopausal women to collect their fecal samples and metadata to conduct metagenome-wide association study (MWAS) to investigate the influence of the gut microbiome on bone health. Gut microbiome sequencing data were produced by BGISEQ500, BMD was calculated using Hologic dual energy X-ray machine, body mass index (BMI) and age were also recorded. Our collected data allows us to explore the gut microbial diversity and their links to bone mass loss, as well as microbial markers for bone mineral density. In addition, these data are potentially useful in studying the role the gut microbiota might play in bone mass loss and in exploring the bone mass loss process.
DOI: 10.17026/dans-26h-kstf
title: A methodological approach to correlate tumor heterogeneity with drug distribution profile in mass spectrometry imaging (MSI) data

description: The dataset folder contains MSI data analyzed in the above paper. The main goal of the study was to use a methodological approach to link tumour heterogeneity with drug homogeneity. The MSI data files in the folder derived from two different cancer cell-lines (ovarian and colon) under two treatment conditions (with and without bevacizumab).
DOI: 10.5524/100785
title: Supporting data for "Machado: open source genomics data integration framework"

description: Genome projects and multiomics experiments generate huge volumes of data that must be stored, mined and transformed into useful knowledge. All this information is supposed to be accessible and, if possible, browsable afterwards. Computational biologists have been dealing with this scenario for over a decade and have been implementing softwares and databases to succeed in this matter. The GMODs (Generic Model Organism Database) biological relational database schema, known as Chado, is one of the few successful open source initiatives, it is widely adopted and many softwares are able to connect to it.<br>We have been developing an open source software named Machado, a genomics data integration framework implemented in Python, to enable research groups to both store and visualize genomics data. The framework relies on the Chado database schema and, therefore, should be very intuitive for current developers to adopt it or have it running on the top of already existing databases. It has several data loading tools for genomics and transcriptomics data and also for annotation results from tools such as BLAST, InterproScan, OrthoMCL and LSTrAP. There is an API to connect to JBrowse and a web visualisation tool is implemented using Django Views and Templates. The Haystack library integrated with the ElasticSearch engine was used to implement a google-like search i.e. single auto-complete search box that provides fast results and filters.<br>Machado aims to be a modern object-relational framework that uses the latests Python libraries to produce an effective open source resource for genomics research.
DOI: 10.5524/100794
title: Supporting data for "A MAP of tumor-host interactions in glioma at single cell resolution"

description: Single-cell RNA sequencing is the reference technique to characterize the heterogeneity of tumor microenvironment. The composition of the various cell types making up the microenvironment can significantly affect the way in which the immune system activates cancer rejection mechanisms. Understanding the cross-talk signals between immune cells and cancer cells is fundamental for the identification of immuno-oncology therapeutic targets. <br>We present a novel method, single-cell Tumor-Host Interaction tool (scTHI), to identify significantly activated ligand-receptor interactions across clusters of cells from single-cell RNA sequencing data. We apply our approach to uncover the ligand-receptor interactions in glioma using six publicly available human glioma datasets encompassing 57,060 gene expression profiles from 71 patients. By leveraging this large-scale collection we show that unexpected cross-talk partners are highly conserved across different datasets in the majority of the tumor samples. This suggests that shared cross-talk mechanisms exist in glioma.<br>Our results provide a complete map of the active tumor-host interaction pairs in glioma that can be therapeutically exploited to reduce the immunosuppressive action of the microenvironment in brain tumors.
DOI: 10.5524/100797
title: Supporting data for "A proteomic approach reveals possible molecular mechanisms and roles for endosymbiotic bacteria in begomovirus transmission by whiteflies"

description: Many plant viruses are vector-borne and depend on arthropods for transmission between host plants. Begomoviruses, the largest, most damaging and emerging group of plant viruses, infect hundreds of plant species and new virus species of the group are discovered each year. Begomoviruses are transmitted by members of the whitefly <i>Bemisia tabaci</i> species complex in a persistent-circulative manner. Tomato yellow leaf curl virus (TYLCV) is one of the most devastating begomoviruses worldwide and causes major losses in tomato crops as well as in many agriculturally important plant species. Different <i>B. tabaci</i> populations vary in their virus transmission abilities; however, the causes for these variations are attributed among others to genetic differences among vector populations, as well as to differences in the bacterial symbionts housed within <i>B. tabaci</i>.<br>Here, we performed discovery proteomic analyses in nine whiteflies populations from both Middle East Asia Minor I (MEAM1 formerly known as B biotype) and Mediterranean (MED formerly known as Q biotype) species. We analyzed our proteomic results based on the different TYLCV transmission abilities of the various populations included in the study. The results provide the first comprehensive list of candidate insect and bacterial symbiont (mainly <i>Rickettsia</i>) proteins associated with virus transmission.<br>Our data demonstrate that the proteomic signature of better vectors populations, differ considerably when compared to less efficient vector ones in the two whitefly species tested in this study. While MEAM1 efficient vector populations has a more lenient immune system, the Q efficient vector populations has higher abundance of proteins possibly implicated in virus passage through cells. Both species show a strong link of the facultative symbiont Rickettsia to virus transmission.
DOI: 10.5524/100802
title: Genome data of the bicolor angelfish (Centropyge bicolor)

description: The bicolor angelfish, <i>Centropyge bicolor</i>, is a kind of tropical coral reef fish that is also well-known as bicolor angelfish because of its special and beautiful two-color body. However, the mechanism of bicolor body has not been studied clearly due to the lack of high-quality genomic data. Here we assembled a chromosome-level genome of the bicolor angelfish with a total length of 650 Mb, contig N50 of 114 Kb and scaffold N50 of 4.4 Mb. Based on the genome, 20,222 protein coding genes were annotated. Furthermore, we identified several candidate gene families associated with its bicolored body developing. As we are known, our study is the first provides a chromosome-level genome as reference for the family Pomacanthidae, which would contribute to the future researches of colorful fish.
DOI: 10.5524/100804
title: Supporting software for "The on-premise data sharing infrastructure e!DAL: Foster FAIR data for faster data acquisition"

description: The FAIR data principle as a commitment to support long-term research data management is widely accepted in the scientific community. Although the ELIXIR Core Data Resources and other established infrastructures provide comprehensive and long-term stable services and platforms for FAIR data management, a notable number of research data is still hidden or under risk of getting lost. Currently, high-throughput plant genomics and phenomics technologies are producing research data in abundance, the storage of which is not covered by established core databases. This concerns the data volume, e.g. time series of images or high-resolution hyper-spectral data, the quality of data formatting and annotation, e.g. with regard to structure and annotation specifications of core databases, uncovered data domains, or organizational constraints to not primarily store data outside the institutional boundaries. In order to share these potentially dark data in a FAIR way and master these challenges the ELIXIR Germany/de.NBI service Plant Genomics and Phenomics Research Data Repository (PGP) implements a bring the infrastructure to the data approach which allows us to keep the research data in place and wrap them by a FAIR-aware software infrastructure. <br>This article presents new features of the PGP infrastructure as a best practice on how to easily set up FAIR-compliant and intuitive research data services. Furthermore, the integration of the ELIXIR Authentication and Authorization Infrastructure (AAI) and data discovery services are introduced as a means to lower technical barriers and to increase the visibility of research data.