cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/100715
title: Supporting data for "PEMA: a flexible Pipeline for Environmental DNA Metabarcoding Analysis of the 16S/18S rRNA, ITS and COI marker genes"

description: Environmental DNA (eDNA) and metabarcoding allow the identification of a mixture of species individuals and launch a new era in bio- and eco-assessment. A great number of steps are required to obtain taxonomically assigned matrices from raw data. For most of these, a plethora of tools are available; each tools execution parameters need to be tailored to reflect each experiments idiosyncrasy. Adding to this complexity, the computation capacity of High Performance Computing systems is frequently required for such analyses. To address the aforementioned difficulties, bioinformatic pipelines need to combine state-of-the art technologies and algorithms with an easy to get-set-use framework, allowing researchers to tune each study. Software containerization technologies ease the sharing and running of software packages across operating systems; thus, they strongly facilitate pipeline development and usage. Likewise are programming languages specialized for big data pipelines, incorporating features like roll-back checkpoints and on-demand partial pipeline execution. <br>PEMA is a containerized assembly of key metabarcoding analysis tools with a low effort in setting up, running and customizing to researchers needs. Based on third party tools, PEMA performs read pre-processing, (M)OTUs clustering, ASV inference, and taxonomy assignment for 16S and 18S rRNA as well as ITS and COI marker gene data. Due to its simplified parameterisation and checkpoint support, PEMA allows users to explore alternative algorithms for specific steps of the pipeline without the need of a complete re-execution. PEMA was evaluated against both mock communities and previously published datasets and achieved comparable quality results. <br> An HPC-based approach was used to develop PEMA, however it can be used in personal computers as well. Given its time-efficient performance and its quality results, it is suggested that PEMA can be used for accurate eDNA metabarcoding analysis, thus enhancing the applicability of next-generation biodiversity assessment studies.
DOI: 10.5524/100718
title: Supporting data for "Laniakea: an open solution to provide Galaxy "on-demand" instances over heterogeneous cloud infrastructures"

description: While the popular workflow manager Galaxy is currently made available through several publicly accessible servers, there are scenarios where users can be better served by full administrative control over a private Galaxy instance, including, but not limited to, concerns about data privacy, customisation needs, prioritisation of particular job types, tools development, training activities. In such cases, a cloud-based Galaxy virtual instance represents an alternative that equips the user with complete control over the Galaxy instance itself without the burden of the hardware and software infrastructure involved in running and maintaining a Galaxy server. We present Laniakea, a complete software solution to set up a Galaxy on-demand Platform as a Service (PaaS). Building on the INDIGO-DataCloud software stack, Laniakea can be deployed over common cloud architectures usually supported both by public and private e-infrastructures. The user interacts with a Laniakea-based service through a simple front-end that allows a general setup of a Galaxy instance, then Laniakea takes care of the automatic deployment of the virtual hardware and the software components. At the end of the process, the user gains access with full administrative privileges to a private, production-grade, fully customisable, Galaxy virtual instance, and to the underlying virtual machine (VM). Laniakea features deployment of single-server or cluster-backed Galaxy instances, sharing of reference data across multiple instances, data volumes encryption, and support for VM image-based, Docker-based, and Ansible recipes-based Galaxy deployments. A Laniakea based Galaxy on-demand service, named Laniakea@ReCaS, is currently hosted at the ELIXIR-IT ReCaS cloud facility. Laniakea offers to scientific e-infrastructures a complete and easy-to-use software solution to provide a Galaxy on-demand service to their users. Laniakea-based cloud services will help in making Galaxy more accessible to a broader user base by removing most of the burdens involved in deploying and running a Galaxy service. In turn, this will facilitate the adoption of Galaxy in scenarios where classic public instances do not represent an optimal solution. Finally, the implementation of Laniakea can be easily adapted and expanded to support different services and platforms beyond Galaxy.
DOI: 10.20391/21154739-f718-457b-96ff-838408f2b696
title: DeepPod: A convolutional Neural Network Based Quantification of Fruit Number in Arabidopsis

description: Images used for manual annotation, training and test of a convolutional neural network. Images are in *.png format and manual data in .csv.
DOI: 10.5524/100668
title: Supporting data for "Assessment of human diploid genome assembly with 10x Linked-Reads data"

description: Producing cost-effective haplotype-resolved personal genomes remains challenging. 10x Linked-Read sequencing, with its high base quality and long-range information, has been demonstrated to facilitate <i>de novo</i> assembly of human genomes and variant detection. In this study, we investigate in depth how the parameter space of 10x library preparation and sequencing affects assembly quality, on the basis of both simulated and real libraries.<br>We prepared and sequenced eight 10x libraries with a diverse set of parameters from standard cell lines NA12878 and NA24385 and performed whole genome assembly on the data. We also developed the simulator LRTK-SIM to follow the workflow of 10x data generation and produce realistic simulated Linked-Read data sets. We found that assembly quality could be improved by increasing the total sequencing coverage (C) and keeping physical coverage of DNA fragments (CF) or read coverage per fragment (CR) within broad ranges. The optimal physical coverage was between 332X and 823X and assembly quality worsened if it increased to greater than 1,000X for a given C. Long DNA fragments could significantly extend phase blocks, but decreased contig contiguity. The optimal length-weighted fragment length (W_FL) was around 50 150kb. When broadly optimal parameters were used for library preparation and sequencing, ca. 80% of the genome was assembled in a diploid state. <br>The Linked-Read libraries we generated and the parameter space we identified provide theoretical considerations and practical guidelines for personal genome assemblies based on 10x Linked-Read sequencing.
DOI: 10.5524/100672
title: Supporting data for "Genome-wide analysis of the H3K27me3 epigenome and transcriptome in Brassica rapa"

description: Genome-wide maps of histone modifications have been obtained for several plant species. However, most studies focus on model systems and do not enforce FAIR data management principles. Here we study the H3K27me3 epigenome and associated transcriptome of Brassica rapa, an important vegetable cultivated world-wide. We obtained the genome-wide profile of the epigenetic mark H3K27me3 in B. rapa. We performed chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) from leaves and inflorescences. To correlate histone methylation and messenger RNA (mRNA) levels, we extracted RNA from the same harvested material and 3-end mRNA high-throughput sequencing (3RNA-seq) was performed. To facilitate transparency and reproducibility, a bioinformatic pipeline was generated for ChIP-seq and RNA-seq - the Reproducible Epigenomic pipeline. This pipeline has been made publicly available, together with the output data being extensively annotated in conformance with the FAIR data principles to allow transparency and reuse of our datasets and analytical tools. Our work reveals the epigenomic landscape of H3K27me3 in B. rapa and provide novel genomics datasets and bioinformatics analytical resources. We anticipate that this work will lead the way to further epigenomic studies in the complex genome of Brassica crops.
DOI: 10.5524/100675
title: Supporting data for "Multifaceted Hi-C benchmarking: what makes a difference in chromosome-scale genome scaffolding?"

description: Hi-C is derived from chromosome conformation capture (3C) and targets chromatin contacts on a genomic scale. This method has also been used frequently in scaffolding nucleotide sequences obtained by de novo genome sequencing and assembly, in which the number of resultant sequences rarely converges to the chromosome number. Despite its prevalent use, the sample preparation methods for Hi-C have not been intensively discussed, especially from the standpoint of genome scaffolding.To gain insight into the best practice of Hi-C scaffolding, we performed a multifaceted methodological comparison using vertebrate samples and optimized various factors during sample preparation, sequencing, and computation. As a result, we identified several key factors that helped improve Hi-C scaffolding, including the choice and preparation of tissues, library preparation conditions, the choice of restriction enzyme(s), and the choice of scaffolding program and its usage.This study provides the first comparison of multiple sample preparation kits/protocols and computational programs for Hi-C scaffolding by an academic third party. We introduce a customized protocol designated inexpensive and controllable Hi-C (iconHi-C) protocol, which incorporates the optimal conditions identified in this study, and demonstrated this technique on chromosome-scale genome sequences of the Chinese softshell turtle <i>Pelodiscus sinensis</i>.
DOI: 10.5524/100679
title: Supporting data for "The draft nuclear genome assembly of Eucalyptus pauciflora: a pipeline for comparing de novo assemblies"

description: Eucalyptus pauciflora (the snow gum) is a long-lived tree with high economic and ecological importance. Currently, little genomic information for Eucalyptus pauciflora is available. Here, we sequentially assemble the genome of Eucalyptus pauciflora with different methods, and combine multiple existing and novel approaches to help to select the best genome assembly. We generated high coverage of long- (Nanopore, 174x) and short- (Illumina, 228x) read data from a single Eucalyptus pauciflora individual and compared assemblies from five assemblers (Canu, SMARTdenovo, Flye, Marvel, and MaSuRCA) with different read lengths (1kb and 35 kb minimum read length). A key component of our approach is to keep a randomly selected collection of ~10% of both long- and short-reads separated from the assemblies to use as a validation set for assessing assemblies. Using this validation set along with a range of existing tools, we compared the assemblies in eight ways: contig N50, BUSCO scores, LAI (Long terminal repeat Assembly Index) scores, assembly ploidy, base-level error rate, CGAL (Computing Genome Assembly Likelihoods) scores, structural variation, and genome sequence similarity. Our result showed that MaSuRCA generated the best assembly, which is 594.87 Mb in size, with a contig N50 of 3.23 Mb, and an estimated error rate of ~0.006 errors per base. We report a draft genome of Eucalyptus pauciflora , which will be a valuable resource for further genomic studies of eucalypts. The approaches for assessing and comparing genomes, should help in assessing and choosing among many potential genome assemblies from a single dataset.
DOI: 10.5524/100683
title: Supporting data for "HAMAP as SPARQL rules – A portable annotation pipeline for genomes and proteomes"

description: Genome and proteome annotation pipelines are generally custom built and therefore not easily reusable by other groups, which leads to duplication of effort, increased costs, and suboptimal results. One cost-effective way to increase the data quality in public databases is to encourage the adoption of annotation standards and technological solutions that enable the sharing of biological knowledge and tools for genome and proteome annotation. We have translated the rules of our HAMAP proteome annotation pipeline to queries in the W3C standard SPARQL 1.1 syntax and applied them with two off-the-shelf SPARQL engines to UniProtKB/Swiss-Prot protein sequences described in RDF format. This approach is applicable to any genome or proteome annotation pipeline and greatly simplifies their reuse. HAMAP SPARQL rules and documentation are freely available for download from the HAMAP FTP site ftp://ftp.expasy.org/databases/hamap/sparql/ under a CC-BY-ND 4.0 license. The annotations generated by the rules are under the CC-BY 4.0 license.<br> This supporting dataset contains the data that demonstrates that our new "HAMAP as SPARQL rules" approach yields the same results as our existing custom implementation of the HAMAP proteome annotation pipeline, as described in Figure 6 of the GigaScience publication The file swissprot_go_term_and_keyword_annotations.nq.gz contains an N-Quads representation of the GO term and UniProt keyword annotations generated with our custom HAMAP pipeline and with the new HAMAP SPARQL rules, in separate named graphs for comparison. To reproduce the generation of these annotations with the HAMAP SPARQL rules, one can use the release 2019_10 version of the rules (file hamap_sparql_2019_10_snapshot.tar.gz)
and Swiss-Prot (ftp://ftp.uniprot.org/pub/databases/uniprot/previous_releases/release-2019_10/knowledgebase/uniprot_sprot-only2019_10.tar.gz).
DOI: 10.5524/100688
title: Supporting data for "Introgression of Eastern Chinese and Southern Chinese haplotypes contributes to the improvement of fertility and immunity in European modern pigs"

description: Pigs were domesticated independently from European and Asian wild boars nearly 10,000 years ago. Chinese indigenous pigs have been historically introduced to improve Europe local pigs. However, the geographic origin and biological functions of introgressed Chinese genes in modern European pig breeds remain largely unknown. Here we explored whole-genome sequencing data from 266 Eurasian wild boars and domestic pigs to produce a fine-scale map of introgression between French Large White (FLW) and Chinese pigs. We show that FLW pigs had historical admixture with both Southern Chinese (SCN) and Eastern Chinese (ECN) pigs approximately 200300 years ago. Moreover, a set of SCN haplotypes was shown to be beneficial for improving disease resistance and those with ECN haplotypes are favorable for improved reproductive performance in FLW pigs. In addition, we confirm human-mediated introgression events at the AHR locus, at which the haplotype of most likely ECN origin contributes to increased fertility of FLW pigs. This study advances our understanding of the breeding history of global domestic pigs and highlights the importance of artificial introgression in the formation of phenotypic characteristics in domestic animals.
DOI: 10.5524/100689
title: Supporting data for "De novo genome assembly and Hi-C analysis reveal the association between chromatin architecture alterations and sex differentiation in the woody plant Jatropha curcas"

description: Chromatin architecture is an essential factor in regulating gene transcription in different cell types and developmental phases. However, studies of chromatin architecture in perennial woody plants and the function of chromatin organization in sex determination have not been reported. <br>Here, we report a chromosome-scale de novo genome assembly of the woody plant Jatropha curcas with a total length of 379.5 Mb and scaffold N50 of 30.7 Mb using PacBio long-reads combined with genome-wide chromosome conformation capture (Hi-C) technology. Based on this high-quality reference genome, we detected chromatin architecture differences between the monoecious and gynoecious inflorescence buds of Jatropha. Differentially expressed genes (DEGs) were significantly enriched in the changed A/B compartments and topologically associated domain (TAD) regions and occurred preferentially in differential contact regions between monoecious and gynoecious inflorescence buds. Twelve DEGs related to flower development or hormone synthesis displayed significantly different genomic interaction patterns in monoecious and gynoecious inflorescence buds.
DOI: 10.5524/100693
title: Supporting data for "Chromosomal-level assembly of Juglans sigillata genome using Nanopore, BioNano and Hi-C analysis"

description: <i>Juglans sigillata</i> (NCBI: txid224355), belonging to Juglandales order, is an economically important tree species in Asia, especially in Yunnan province of China. However, little research has been conducted on <i>J. sigillata</i> at the molecular level, which hinders understanding of its evolution, speciation, and synthesis of secondary metabolites, as well as its wide adaptability to the plateau environment. To address these issues, a high-quality reference genome of <i>J. sigillata</i> would be a very useful resource.<br>To construct a high-quality reference genome for <i>J. sigillata</i>, we first generated 38.0 Gb short reads and 66.31 Gb long reads using Illumina and Nanopore sequencing platforms, respectively. The sequencing data were assembled into a 536.50 Mb genome assembly with a contig N50 length of 4.31 Mb. Additionally, we applied BioNano technology to identify contacts among contigs, which were then used to assemble contigs into scaffolds, resulting in a genome assembly with scaffold N50 length of 16.43 Mb and contig N50 length of 4.34 Mb. To obtain a chromosome-level genome assembly, we constructed one Hi-C library and sequenced 79.97 Gb raw reads using the Illumina HiSeq platform. We anchored approximately 93% of the scaffold sequences into 16 chromosomes and evaluated the quality of our assembly using the high contact frequency heatmap. Repetitive elements account for 50.06% of the genome, and 30,387 protein-coding genes were predicted from the genome, of which 99.8% have been functionally annotated. The genome-wide phylogenetic tree indicated the divergence time between <i>J. sigillata</i> and <i>J.regia</i> was estimated to be 49 million years ago (Mya) based on single-copy orthologous genes.<br> We provide the first chromosome-level genome for <i>J. sigillata</i>. The genome will lay a valuable foundation for future research on genetic improvement of <i>J. sigillata</i>.
DOI: 10.5524/100701
title: Supporting data for "ShinyLearner: A containerized benchmarking tool for machine-learning classification of tabular data"

description: Classification algorithms assign observations to groups based on patterns in data. The machine-learning community have developed myriad classification algorithms, which are employed in diverse life-science research domains. When applying such algorithms, researchers face the challenge of deciding which algorithm(s) to apply in a given research domain. Algorithm choice can affect classification accuracy dramatically, so it is crucial that researchers optimize these choices based on empirical evidence rather than hearsay or anecdotal experience. In benchmark studies, multiple algorithms are applied to multiple datasets, and the researcher examines overall trends. In addition, the researcher may evaluate multiple hyperparameter combinations for each algorithm and use feature selection to reduce data dimensionality. Although software implementations of classification algorithms are widely available, robust benchmark comparisons are difficult to perform when researchers wish to compare algorithms that span multiple software packages. Programming interfaces, data formats, and evaluation procedures differ across software packages; and dependency conflicts may arise during installation. To address these challenges, we created ShinyLearner, an open-source project for integrating machine-learning packages into software containers. ShinyLearner provides a uniform interface for performing classification, irrespective of the library that implements each algorithm, thus facilitating benchmark comparisons. In addition, ShinyLearner enables researchers to optimize hyperparameters and select features via nested cross validation; it tracks all nested operations and generates output files that make these steps transparent. ShinyLearner includes a Web interface to help users more easily construct the commands necessary to perform benchmark comparisons.<br> A CODECHECK certificate for this paper is available at zenodo.3674056 confirming that the figures in the paper could be independently replicated.
DOI: 10.5524/100702
title: Supporting data for "Genome sequence of agarwood tree Aquilaria sinensis (Lour.) Spreng: the first chromosome-level draft genome in the Thymelaeceae family"

description: <i>Aquilaria sinensis</i> (Lour.) Spreng is one of important plant resources for producing agarwood in China. The agarwood collected from the wounded Aquilaria trees have been used for aromatic or medicinal purposes in these regions from the ancient time, whereas the mechanism underlying the formation of agarwood still remained poorly understood by a lack of accurate and high-quality genetics information. <br>We report genomic architecture of<i> A.sinensis</i> by an integrated strategy combining with Nanopore sequencing, Illumina sequencing and Hi-C sequencing. The final genome was approximately 726.5 Mb, which reached a high level of continuity with a contig N50 of 1.1 Mb. We combined Hi-C data with the genome assembly to generate chromosome-level scaffolds. Eight super-scaffolds corresponding to the 8 chromosomes were assembled to a final size of 716.6 Mb, with a scaffold N50 of 88.78 Mb using 1,862 contigs. Benchmarking Universal Single-Copy Orthologs evaluation reveals that the genome completeness reaches 95.27%. The repeat sequences are accounted for 59.13% and the protein-coding genes are annotated for 29,203 in the entire genome. According to phylogenetic analysis using single-copy orthologous genes, we found that <i>A.sinensis</i> is closely related to <i>Gossypium hisutum</i> and <i>Theobroma cacao</i> from the Malvales order, and <i>A.sinensis</i> was diverged from their common ancestor approximately 53.18-84.37 million years ago. <br>Here, we represent the first chromosome-level genome assembly and gene annotation of<i> A.sinensis</i>. This study would contribute to provide valuable genetic resources for the further researches on agarwood formation mechanism, genome-assisted improvements and conservation biology of Aquilaria species.
DOI: 10.5524/100704
title: Supporting data for "DeepPod: A Convolutional Neural Network Based Quantification of Fruit Number in Arabidopsis"

description: High-throughput phenotyping based on non-destructive imaging has great potential in plant biology and breeding programs. However, efficient feature extraction and quantification from image data remains a bottleneck that needs to be addressed. Advances in sensor technology have led to the increasing use of imaging to monitor and measure a range of plants including the model Arabidopsis thaliana. These extensive datasets contain diverse trait information but feature extraction is often still implemented using approaches requiring substantial manual input. The computational detection and segmentation of individual fruits from images is a challenging task, for which we have developed DeepPod, a patch based two-phase deep learning framework. The associated manual annotation task is simple and cost effective without the need for detailed segmentation or bounding boxes. Convolutional neural networks (CNNs) are used for classifying different parts of the plant inflorescence, including the tip, base and body of the siliques and the stem inflorescence. In a post processing step, different parts of the same silique are joined together for silique detection and localisation, whilst taking into account possible overlapping among the siliques. The proposed framework is further validated on a separate test dataset of 2,408 images. Comparisons of the CNN based prediction with manual counting (R2 = 0.90) showed the desired capability of methods for estimating silique number.