cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/100508
title: Supporting data for "MetaPGN: a pipeline for construction and graphical visualization of annotated pangenome networks"

description: Pangenome analyses facilitate the interpretation of genetic diversity and evolutionary history of a taxon. However, there is an urgent and unmet need to develop new tools for advanced pangenome construction and visualization, especially for metagenomic data. Here we present an integrated pipeline, named MetaPGN, for construction and graphical visualization of pangenome network from either microbial genomes or metagenomes. Given either isolated genomes or metagenomic assemblies coupled with a reference genome of the targeted taxon, MetaPGN generates a pangenome in a topological network, consisting of genes (nodes) and gene-gene genomic adjacencies (edges) of which biological information can be easily updated and retrieved. MetaPGN also includes a self-developed Cytoscape plugin for layout of and interaction with the resulting pangenome network, providing an intuitive and interactive interface for full exploration of genetic diversity. We demonstrate the utility of MetaPGN by constructing <em>Escherichia coli </em>(<em>E. coli</em>) pangenome networks from five <em>E. coli</em> pathogenic strains and 760 human gut microbiomes respectively, revealing extensive genetic diversity of <em>E. coli</em> within both isolates and gut microbial populations. With the ability to extract and visualize gene contents and gene-gene physical adjacencies of a specific taxon from large-scale metagenomic data, MetaPGN provides advantages in expanding pangenome analysis to uncultured microbial taxa. MetaPGN is available at https://github.com/peng-ye/MetaPGN
DOI: 10.5524/100509
title: Supporting data for "Aequatus: An open-source homology browser"

description: Phylogenetic information inferred from the study of homologous genes helps us to understand the evolution of genes and gene families, including the identification of ancestral gene duplication events as well as regions under positive or purifying selection within lineages. Gene family and orthogroup characterisation enables the identification of syntenic blocks, which can then be visualised with various tools. Unfortunately, currently available tools display only an overview of syntenic regions as a whole, limited to the gene level, and none provide further details about structural changes within genes, such as the conservation of ancestral exon boundaries amongst multiple genomes.<br>We present Aequatus, a standalone web-based tool that provides an indepth view of gene structure across gene families, with various options to render and filter visualisations. It relies on pre-calculated alignment and gene feature information typically held in, but not limited to, the Ensembl Compara and Core databases. We also offer Aequatus.js, a reusable JavaScript module that fulfils the visualisation aspects of Aequatus, available within the Galaxy web platform as a visualisation plugin, which can be used to visualise gene trees generated by the GeneSeqToFamily workflow.<br> Aequatus is an open-source tool freely available to download under the MIT license at https://github.com/TGAC/Aequatus. A demo server is available at http://aequatus.earlham.ac.uk/. A publicly available instance of the GeneSeqToFamily workflow to generate gene tree information and visualise it using Aequatus is available on the Galaxy EU server at https://usegalaxy.eu
DOI: 10.5524/100513
title: Supporting data for "Transfer learning improves resting-state functional connectivity pattern analysis using convolutional neural networks"

description: Deep learning is gaining importance in the prediction of cognitive states and brain pathology based on neuroimaging data. Including multiple hidden layers in artificial neural networks enables unprecedented predictive power; however, the proper training of deep neural networks requires thousands of exemplars. Collecting this amount of data is not feasible in typical neuroimaging experiments. A handy solution to this problem, which has largely fallen outside the scope of deep learning applications in neuroimaging, is to repurpose deep networks that have already been trained on large datasets by fine-tuning them to target datasets/tasks with fewer exemplars. Here we investigated how this method, called transfer learning, can aid age category classification and regression based on brain functional connectivity patterns derived from resting-state functional magnetic resonance imaging. We trained a connectome-convolutional neural network on a larger public dataset and then examined how the knowledge learned can be used effectively to perform these tasks on smaller target datasets collected with a different type of scanner and/or imaging protocol and pre-processing pipeline. Age classification on the target datasets benefitted from transfer learning. Significant improvement (~9-13% increase in accuracy) was observed when the convolutional layers weights were initialized based on the values learned on the public dataset and then fine-tuned to the target datasets. Transfer learning also appeared promising in improving the otherwise poor prediction of chronological age. Transfer learning is a plausible solution to adapt convolutional neural networks to neuroimaging data with few exemplars and different data acquisition and pre-processing protocols.
DOI: 10.5524/100514
title: Supporting data for "Imaging tissues and cells beyond the diffraction limit with structured illumination microscopy and Bayesian image reconstruction"

description: Structured illumination microscopy (SIM) is a family of methods in optical fluorescence microscopy that can achieve both optical sectioning and super-resolution effects. SIM is a valuable method for high resolution imaging of fixed cells or tissues labeled with conventional fluorophores, as well as for imaging the dynamics of live cells expressing fluorescent protein constructs. In SIM, one acquires a set of images with shifting illumination patterns. This set of images is subsequently treated with image analysis algorithms to produce an image with reduced out-of-focus light (optical sectioning) and/or with improved resolution (super-resolution). Five complete, freely available SIM datasets are presented including raw and analyzed data. We report methods for image acquisition and analysis using open source software along with examples of the resulting images when processed with different methods. We processed the data using established optical sectioning SIM and super-resolution SIM methods, and with newer Bayesian restoration approaches which we are developing. Various methods for SIM data acquisition and processing are actively being developed, but complete raw data from SIM experiments is not typically published. Publically available, high quality raw data with examples of processed results will aid researchers when developing new methods in SIM. Biologists will also find interest in the high-resolution images of animal tissues and cells we acquired. All of the data was processed with SIMToolbox, an open source and freely available software solution for SIM.
DOI: 10.5524/100515
title: Supporting data for "NAT/NCS2-hound: A webserver for the detection and evolutionary classification of prokaryotic and eukaryotic nucleobase-cation symporters of the NAT/NCS2 family"

description: Nucleobase transporters are important for supplying the cell with purines and/or pyrimidines, for controlling the intracellular pool of nucleotides and for obtaining exogenous nitrogen/carbon sources for the metabolism. Nucleobase transporters are also evaluated as potential targets for antimicrobial therapies, since several pathogenic microorganisms rely on purine/pyrimidine salvage from their hosts. The majority of known nucleobase transporters belong to the evolutionarily conserved and ubiquitous NAT/NCS2 protein family. Based on a large-scale phylogenetic analysis that we performed on thousands of prokaryotic proteomes, we have developed a webserver that can detect and distinguish this family of transporters from other homologous families that recognize different substrates. We can further categorize these transporters to certain evolutionary groups with distinct substrate preferences. The webserver scans whole proteomes and graphically displays which proteins are identified as NAT/NCS2, to which evolutionary groups and subgroups they belong to and which conserved motifs they have. For key subgroups and motifs, the server displays annotated information from published crystal-structures and mutational studies pointing to key functional amino acids that may help experts assess the transport capability of the target sequences. The server is 100% accurate in detecting NAT/NCS2 family members. We also used the server to analyze 9109 prokaryotic proteomes and identified Clostridia, Bacilli, beta- and gamma-Proteobacteria, Actinobacteria and Fusobacteria as the taxa with the largest number of NAT/NCS2 transporters per proteome. An analysis of 120 representative eukaryotic proteomes also demonstrates the server's capability of correctly analyzing this major lineage, with plants emerging as the group with the highest number of NAT/NCS2 members per proteome.
DOI: 10.5524/100466
title: Supporting data for "Long-read sequencing and de novo genome assembly of Ammopiptanthus nanus, a desert shrub"

description: Ammopiptanthus nanus is a rare broad-leaved shrub in the desert and arid regions of Central Asia. This plant species exhibits extremely high tolerance to drought and freezing and has been used in abiotic tolerance research in plants. As a relic of the Tertiary period, A. nanus is of great significance to plant biogeographic research in the ancient Mediterranean region. Here we report a draft genome assembly using the PacBio platform and gene annotation for A. nanus. <br> A total of 64.72 gigabases (Gb) of raw PacBio Sequel reads were generated from four 20 kb libraries. After filtering, 64.53 Gb of clean reads were obtained, giving 72.59 × coverage depth. Assembly using Canu gave an assembly length of 823.74 Mb, with a contig N50 of 2.76 Mb. The final size of the assembled A. nanus genome was close to the 889 Mb estimated by k-mer analysis. The gene annotation completeness was evaluated by BUSCO, and 1,327 out of the 1,440 conserved genes (92.15%) could be found in the A. nanus assembly. Genome annotation revealed that 74.08% of the A. nanus genome is composed of repetitive elements, and 53.44% of long terminal repeat elements (LTRs). We predicted 37,188 protein-coding genes, of which 96.53% were functionally annotated.<br> The genomic sequences of A. nanus could be a valuable source for comparative genomic analysis in the legume family, and will be useful for understanding the phylogenetic relationships of the Thermopsideae and the evolutionary response of plant species to the Qinghai Tibetan Plateau uplift.
DOI: 10.5524/100468
title: Supporting data for"Hot-starting software containers for STAR aligner"

description: Using software containers has become standard practice to reproducibly deploy and execute biomedical workflows on the cloud. However, some applications which contain time-consuming initialization steps will produce unnecessary costs for repeated executions. <br>We demonstrate that hot-starting, from containers that have been frozen after the application has already begun execution, can speed up bioinformatics workflows by avoiding repetitive initialization steps. We use an open source tool called Checkpoint and Restore in Userspace (CRIU) to save the state of the containers as a collection of checkpoint files on disk after it has read in the indices. The resulting checkpoint files are migrated to the host and CRIU is used to regenerate the containers in that ready-to-run hot-start state. As a proof-of-concept example, we create a hot-start container for the STAR aligner and deploy this container to align RNA sequencing data. We compare the performance of the alignment step with and without checkpoints on cloud platforms using local and network disks.<br>We demonstrate that hot-starting Docker containers from snapshots taken after repetitive initialization steps are completed, significantly speeds up the execution of the STAR aligner on all experimental platforms, including Amazon Web Services (AWS), Microsoft Azure and local virtual machines. Our method can be potentially employed in other bioinformatics applications in which a checkpoint can be inserted after a repetitive initialization phase.
DOI: 10.5524/100469
title: Supporting data for "Nighres: Processing tools for high-resolution neuroimaging"

description: With recent improvements in magnetic resonance imaging (MRI) at ultra-high fields, the amount of data collected per subject in a given MRI experiment has increased considerably. Standard image processing packages are often challenged by the size of these data and dedicated methods are needed to leverage their extraordinary spatial resolution. Here we introduce a flexible Python toolbox which implements a set of advanced techniques for high-resolution neuroimaging. With these tools, segmentation and laminar analysis of cortical MRI data can be performed at resolutions up to 500 µm in reasonable times. Comprehensive online documentation makes the toolbox easy to use and install. An extensive developer's guide encourages contributions of other researchers that will help to accelerate progress in the promising field of high-resolution neuroimaging.
DOI: 10.5524/100471
title: Supporting data for "A similarity-based approach to leverage multi-cohort medical data on the diagnosis and prognosis of Alzheimer's disease"

description: Heterogeneous diseases such as Alzheimer's disease manifest a variety of phenotypes among populations. Early diagnosis and effective treatment offer costbenefits. Many studies on biochemical and imaging markers have shown potential promise in improving diagnosis, yet establishing quantitative diagnostic criteria for ancillary tests remains challenging. <br> We have developed a similarity-based approach that matches individuals to subjects with similar conditions. We modeled the disease with a Gaussian process, and tested the method in the Alzheimer's Disease Big Data DREAM Challenge. Ranked the highest among submitted methods, our diagnostic model predicted cognitive impairment scores in an independent dataset test with a correlation score of 0.573. It differentiated Alzheimer's disease patients from control subjects with an area under receiver operating curve of 0.920. Without knowing longitudial information about subjects, the model predicted patients that are vulnerable to MCI-to-AD conversion through the similarity network. This diagnostic framework can be applied to other diseases with clinical heterogeneity, such as Parkinson's disease.
DOI: 10.5524/100477
title: Supporting data for "SL-quant: A fast and flexible pipeline to quantify spliced leader trans-splicing events from RNA-seq data"

description: The spliceosomal transfer of a short spliced leader (SL) RNA to an independent pre-mRNA molecule is called SL trans-splicing and is widespread in the nematode C. elegans. While RNA-seq data contain information on such events, properly documented methods to extract them are lacking. To address this, we developed SL-quant, a fast and flexible pipeline that adapts to paired-end and single-end RNA-seq data and accurately quantifies SL trans-splicing events. It is designed to work downstream of read mapping and uses the reads left unmapped as primary input. Briefly, the SL-sequences are identified with high specificity and are trimmed from the input reads, which are then re-mapped on the reference genome and quantified at the nucleotide position level (SL trans-splice sites) or at the gene level. SL-quant completes within 10 minutes on a basic desktop computer for typical RNA-seq datasets. Validating the method, the SL trans-splice sites identified display the expected consensus sequence and the results of the gene-level quantification are predictive of the gene position within operons. We also compared SL-quant to a recently published SL-containing read identification strategy which revealed being more sensitive, but less specific than SL-quant. Both methods are implemented as a bash script available under the MIT licence at https://github.com/cyaguesa/SL-quant. Full instructions for its installation, usage, and adaptation to other organisms are provided.
DOI: 10.5524/100479
title: Supporting data for "Genome-wide definition of selective sweeps reveals molecular evidence of trait-driven domestication among elite goat (Capra species) breeds for the production of dairy, cashmere, and meat"

description: Domestication of wild goats and subsequent intensive trait-driven crossing, inbreeding, and selection, all have led to dramatic phenotypic purification and intermediate breeds for high-quality production of dairy, cashmere, and meat. Genomic re-sequencing provides a powerful mean for direct identification of trait-associated sequence variations that underlie molecular mechanisms of domestication. Here, we report our effort to define such variations based on data from domestic goat breeds (Capra eagagrus hircus; 5 each) selected for dairy, cashmere, and meat production in referencing to their wild ancestors, Sindh ibex (Capra eagagrus blythi; 2) and Markhor (Capra falconeri; 2). Using ~24 million high-quality single nucleotide polymorphisms (SNPs), ~1.9 million insertions/deletions (indels), and 2,317 copy number variations (CNVs), we define SNP-desert-associated genes (SAGs), domestic-associated genes (DAGs), and trait-associated genes (TAGs), and attempt to associate them with quantitative trait loci (QTL), domestication, and agronomic traits. Surprisingly, a greater majority of SAGs shared by all domestic breeds classified into Gene Ontology categories of metabolism and cell cycle. DAGs, together with some SAGs, are most relevant to behavior, immunity, and trait-specificity, whereas TAGs appear directly involved in growth regulation, such as growth differentiation factor 5 (GDF5) and fibroblast growth factor 5 (FGF5) for bone and hair growth, respectively. When investigating divergence of Capra populations, the sequence variations and candidate genes we have identified provide valuable molecular markers for trait-driven genetic mapping and breeding.
DOI: 10.5524/100484
title: Supporting data for "Population genomics of wild Chinese rhesus macaques reveals a dynamic demographic history and local adaptation, with implications for biomedical research"

description: The rhesus macaque (RM, <i>Macaca mulatta</i>) is the most important nonhuman primate model in biomedical research. We present the first genomic survey of wild RMs, sequencing 81 geo-referenced individuals of five subspecies from 17 locations in China, a large fraction of the species natural distribution. <br>Populations were structured into five genetic lineages on the mainland and Hainan Island, recapitulating current subspecies designations. These subspecies are estimated to have diverged 125.8 to 51.3 thousand years ago, but feature recent gene flow. Consistent with the expectation of a larger body size in colder climates and smaller body size in warmer climates (Bergmans rule), the northernmost RM lineage (M. m. tcheliensis), possessing the largest body size of all Chinese RMs, and the southernmost lineage (<i>M. m. brevicaudus</i>), with the smallest body size of all Chinese RMs, feature positively selected genes responsible for skeletal development. Further, two candidate selected genes (Fbp1, Fbp2) found in M. m. tcheliensis are involved in gluconeogenesis, potentially maintaining stable blood glucose levels during starvation when food resources are scarce in winter. The tropical subspecies M. m. brevicaudus showed positively selected genes related to cardiovascular function and response to temperature stimuli, potentially involved in tropical adaptation. We found 118 SNPs matching human disease-causing variants with 82 being subspecies-specific.<br>These data provide a resource for selection of RMs in biomedical experiments. The demographic history of Chinese RMs, and their history of local adaption offers new insights into their evolution and provides valuable baseline information for biomedical investigation.
DOI: 10.5524/100485
title: Supporting data for "The genome of the golden apple snail Pomacea canaliculata provides insight into stress tolerance and invasive adaptation"

description: The golden apple snail (Pomacea canaliculata) is a fresh water snail listed among the top-100 worst invasive species, worldwide and a noted agricultural and quarantine pest that causes great economic losses. It is characterized by fast growth, strong stress tolerance, a high reproduction rate, and adaptation to a broad range of environments.<br> Here, we used long-read sequencing to produce a 440-Mb high-quality chromosome-level assembly for the P. canaliculata genome. In total, 50 Mb (11.4%) repeat sequences and 21,533 gene models were identified in the genome. The major findings of this study include the recent explosion of DNA/hAT-Charlie transposable elements (TEs), the expansion of the P450 gene family and the constitution of the cellular homeostasis system, which contributes to ecological plasticity in stress adaptation. In addition, the high transcriptional levels of perivitellin genes in the ovary and albumen gland promote the function of nutrient supply and defence ability in eggs. Furthermore, the gut metagenome also contains diverse genes for food digestion and xenobiotic degradation.
DOI: 10.5524/100488
title: Supporting data for "Monitoring changes in the Gene Ontology and their impact on genomic data analysis"

description: The Gene Ontology (GO) is one of the most widely used resources in molecular and cellular biology, largely through the use of "enrichment analysis". To facilitate informed use of GO, we present GOTrack (https://gotrack.msl.ubc.ca), which provides access to historical records and trends in the Gene Ontology and GO annotations (GOA). GOTrack gives users access to gene- and term-level information on annotations for nine model organisms as well as an interactive tool that measures the stability of enrichment results over time for user-provided "hit lists" of genes. To document the effects of GO evolution on enrichment, we analyzed over 2500 published hit lists of human genes (most over 9 years old). 53% of hit lists were considered to yield significantly stable enrichment results. Because stability is far from assured for any individual hit list, GOTrack can lead to more informed and cautious application of GO to genomics research.
DOI: 10.5524/100491
title: Supporting data for "The metagenome of the female upper reproductive tract"

description: The human uterus is traditionally believed to be sterile, while the vaginal microbiota plays important role in fending off pathogens. Emerging evidence demonstrates the presence of bacteria beyond the vagina. However, a microbiome-wide metagenomic analysis identifying the overall microorganism communities has been lacking. We performed shotgun-sequencing by Illumina platform of 52 samples from the cervical canal and the peritoneal fluid of Chinese women in reproductive age. Direct annotation of sequencing reads identified the taxonomy of bacteria, archaea, fungi and viruses, confirming and extending the results from our previous study. We replicated the findings in another 24 samples from the vagina, the cervical canal, the uterus and the peritoneal fluid using BGISEQ-500 platform, revealing that microorganisms in the samples from the same individual were largely shared in the whole reproductive tract. Over 99% human sequences were detected in the 20GB raw data. After filtering, vaginal microorganisms were well covered in the generated reproductive tract gene catalogue, while the more diverse upper reproductive tract microbiota might need greater depth of sequencing and more samples to meet the full coverage scale.