cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/100556
title: Supporting data for "Genome sequence of the barred knifejaw Oplegnathus fasciatus (Temminck & Schlegel, 1844): the first chromosome-level draft genome in the family Oplegnathidae"

description: The barred knifejaw (<em>Oplegnathus fasciatus</em>), a member of the Oplegnathidae family of the Centrarchiformes, is a commercially important rocky reef fish native to East Asia.<em> O. fasciatus</em> has become an important fishery resource for offshore cage aquaculture and fish stocking of marine ranching in China, Japan and Korea. Recently, sexual dimorphism in growth with neo-sex chromosome and widespread biotic diseases in <em>O. fasciatus</em> has been received increasing concern. However, adequate genome resources for gaining insight into sex-determining mechanisms and establishing genetically resistant breeding systems for <em>O. fasciatus</em> are lacking. Here, we analysed the entire genome of a female <em>O. fasciatus</em> fish using long-read sequencing and Hi-C data to generate chromosome-length scaffolds and a highly contiguous genome assembly. We assembled the <em>O. fasciatus</em> genome with a total of 245.0 Gb of raw reads that were generated using both of PacBio Sequel and Illumina HiSeq 2000 platforms. The final draft genome assembly was approximately 778.7 Mb, which reached a high level of continuity with a contig N50 of 2.1 Mb. The genome size was consistent with the estimated genome size (777.5 Mb) based on <em>k</em>-mer analysis. We combined Hi-C data with a draft genome assembly to generate chromosome-length scaffolds. Twenty-four scaffolds corresponding to the twenty-four chromosomes were assembled to a final size of 768.8 Mb with a contig N50 of 2.1 Mb and a scaffold N50 of 33.5 Mb using 1,372 contigs. The identified repeat sequences accounted for 33.9% of the entire genome, and 24,003 protein-coding genes with an average of 10.1 exons per gene were annotated using <em>de novo</em> methods, with RNA-seq data and homologies to other teleosts. According to phylogenetic analysis using protein-coding genes, <em>O. fasciatus</em> is closely related to <em>Larimichthys crocea</em>, with <em>O. fasciatus</em> diverging from their common ancestor approximately 70.5-88.5 million years ago. We generated a high-quality draft genome with chromosome assembly for <em>O. fasciatus</em> using long reads by using the PacBio sequencing technologies, which represents the first chromosome-level reference genome for Oplegnathidae species. Assembly of this genome will provide insight into sex-determining mechanisms and serve as a resource for accelerating genome-assisted improvements in resistant breeding systems.
DOI: 10.5524/100557
title: Supporting data for "MGS-Fast: MetaGenomic Shotgun data Fast annotation using microbial gene catalogs"

description: Current methods used for annotating metagenomics shotgun sequencing (MGS) data, rely on a computationally intensive and low stringency approach of mapping each read to a generic database of proteins or reference microbial genomes. <br>We developed MGS-Fast, an alternative analysis approach for shotgun whole genome metagenomic data utilizing Bowtie2 DNA-DNA alignment of reads, to the IGC database of well annotated genes compiled from human microbiome data. This method is rapid and provides high stringency matches (&gt;90% DNA sequence identity) of the metagenomics reads to genes with annotated functions. We demonstrate the use of this method with data from a study of liver disease and synthetic reads, and Human Microbiome Project shotgun data, to detect differentially abundant KEGG gene functions in these experiments. This rapid annotation method is freely available as a Galaxy workflow within a Docker image.
DOI: 10.5524/100559
title: Supporting data for "De novo genome assembly of the Indian Blue Peacock (Pavo cristatus), from Oxford Nanopore and Illumina sequencing"

description: <i>Pavo cristatus</i>, the Indian peafowl are located in natural habitats of South Asia. The male blue peacock bird is known for its elegance, majestic looks and beauty. Since prehistoric times they have been described in Indian culture and has been adopted as the national bird of India. In this study, we present the first draft genome sequence of the peacock using Illumina and Oxford Nanopore technologies (ONT).<br>ONT sequencing resulted in approximately 2.3-fold sequencing coverage, whereas Illumina generated 150 bp paired-end sequence data at 284.6-fold sequencing coverage from five libraries. Subsequently, we generated de novo genome assembly of the peacock genome with a 0.915 Gigabases (Gb) with a scaffold N50 of 0.23 Megabases (Mb). We also predicted that the peacock genome contains 23,153 protein-coding genes and 75.3 Mb (7.33%) of repetitive sequences.<br>We report a high-quality genome assembly of the peacock using a hybrid assembly generated from Illumina and ONT sequencing platforms. Long read chemistry generated from ONT was found to be useful in addressing challenges related to de novo assembly particularly at regions containing repetitive sequences that span longer than the read length, and which cannot be resolved using only short-read-based assembly. The contig assembly on the short reads from Illumina resulted in an N50 of 1639 bases, whereas using 2.3x coverage from ONT increased the N50 by nine fold to 14,749 bases. The initial contig assembly based on Illumina sequencing reads alone resulted in total of 685,241 contigs. Further scaffolding on assembled contigs using both Illumina and ONT sequencing reads resulted in a final assembly having 15,025 super scaffolds with a N50 of about 0.23 Mb. The completeness of our genome assembly was verified with the fact that 95% of proteins predicted by homology were matched to those submitted in public repository. Further in concordance with other phylogenetic studies, the avian phylogeny on the conserved genes showed P. cristatus being closest with Gallus gallus followed by Meleagris gallopavo and Anas platyrhynchos. In comparison to the recently published peacock genome assembly, the current hybrid assembly appears to be much superior with a greater sequencing depth, lesser non-ATGC in the assembly and with a reduced number of scaffolds as evident by a nearly 9.1-fold improvement in N50 statistics.
DOI: 10.5524/100563
title: Supporting data for "TranscriptAchilles: a genome-wide platform to predict isoform biomarkers of gene essentiality in cancer"

description: Aberrant alternative splicing (AS) plays a key role in cancer development. In recent years, AS is being used as a prognosis biomarker, a therapy response biomarker and even as a therapeutic target. Next generation RNA sequencing has an unprecedented potential to measure the transcriptome. However, due to the complexity of dealing with isoforms, the scientific community has not sufficiently exploited this valuable resource in precision medicine. We present TranscriptAchilles, the first large-scale tool to predict transcript biomarkers associated with gene essentiality in cancer. This application integrates 412 loss-of-function RNA interference screens of over 17,000 genes together with their corresponding whole-transcriptome expression profiling. Using this tool, we have studied which are the cancer subtypes for which alternative splicing plays a significant role to state gene essentiality. In addition, we include a case study of renal cell carcinoma that shows the biological soundness of the results. TranscriptAchilles provides a user-friendly web interface to identify transcript or gene biomarkers of gene essentiality, which could be used as a starting point for a drug development project. This approach opens a wide range of translational applications in cancer.
DOI: 10.7946/mq0g
title: Staggered Mock Metagenomic Communities

description: Artificial metagenomic reads from mock communities.  Data from https://www.imicrobe.us/#/projects/265  The raw sequence data from the staggered mock community (SRP115095 in project accession PRJNA397434) were used to develop simulated metagenomes. We used the known staggered mock community abundance profile to generate a simulated metagenome using GemSim (454 sequencing) with 0.5, 1, 5, and 10 million reads based on the relative abundance of organisms in the staggered mock community. We developed four simulated metagenomes to test the effect of changing the dominant organism abundance and genetic composition including: 10 million reads from the staggered mock community (mock 1), the mock community with alterations in a few abundant species (mock 2), the mock community with many alterations in abundant species (mock 3), and mock 3 with additional sequences from archaea to further alter the genetic composition (mock 4). The same community profiles were used to generate paired-end illumina dataset (100 million reads), using GemSim (illumina v4 error model). Finally, using SimLord, the community profiles were used to generate simulated third generation sequencing datasets (Pacific Bioscience SMRT sequencing - 1 million reads). SimLord default parameters were used to generate those simulated datasets.
DOI: 10.26188/5bd78e3f49e3f
title: GiardiaWB_iTASSER.tar.gz

description: Protein structures predicted for 4901 Giardia duodenalis (assemblage A; strain WB) proteins, with associated ligand binding site predictions, ligand-protein complexes, closest empirically determined structural homologues (RSCB PDB reference structures) and gene ontology predictions.<br>Individual structures and associated information is hosted at http://predictein.org/giardia_duodenalis
DOI: 10.5524/100518
title: Supporting data for "A critical comparison of technologies for a plant genome sequencing project"

description: A high quality genome sequence of any model organism is an essential starting point for genetic and other studies. Older clone based methods are slow and expensive, whereas faster, cheaper short read only assemblies can be incomplete and highly fragmented, which minimises their usefulness. The last few years have seen the introduction of many new technologies for genome assembly. These new technologies and associated new algorithms are typically benchmarked on microbial genomes or, if they scale appropriately, on larger (e.g. human) genomes. However, plant genomes can be much more repetitive and larger than the human genome, and plant biochemistry often makes obtaining high quality DNA free from contaminants difficult. Reflecting their challenging nature we observe that plant genome assembly statistics are typically poorer than for vertebrates.<br>Here we compare Illumina short read, PacBio long read, 10x Genomics linked reads, Dovetail Hi-C and BioNano Genomics optical maps, singly and combined, in producing high quality long range genome assemblies of the potato species <i>S. verrucosum</i>. We benchmark the assemblies for completeness and accuracy, as well as DNA, compute requirements and sequencing costs. <br> The field of genome sequencing and assembly is reaching maturity and the diferences we observe between assemblies are surprisingly small. We expect that our results will be helpful to other genome projects, and that these datasets will be used in benchmarking by assembly algorithm developers
DOI: 10.5524/100528
title: Supporting data for "PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud"

description: Metabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organisms metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological and many other applied biological domains. Its computationally-intensive nature has driven requirements for open data formats, data repositories and data analysis tools. However, the rapid progress has resulted in a mosaic of independent and sometimes incompatible analysis methods that are difficult to connect into a useful and complete data analysis solution.<br>PhenoMeNal (Phenome and Metabolome aNalysis) is an advanced and complete solution to set up Infrastructure-as-a-Service (IaaS) that brings workflow-oriented, interoperable metabolomics data analysis platforms into the cloud. PhenoMeNal seamlessly integrates a wide array of existing open source tools which are tested and packaged as Docker containers through the projects continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi and Pachyderm.<br> PhenoMeNal constitutes a keystone solution in cloud e-infrastructures available for metabolomics. PhenoMeNal is a unique and complete solution for setting up cloud e-infrastructures through easy-to-use web interfaces that can be scaled to any custom public and private cloud environment. By harmonizing and automating software installation and configuration and through ready-to-use scientific workflow user interfaces, PhenoMeNal has succeeded in providing scientists with workflow-driven, reproducible and shareable metabolomics data analysis platforms which are interfaced through standard data formats, representative datasets, versioned, and have been tested for reproducibility and interoperability. The elastic implementation of PhenoMeNal further allows easy adaptation of the infrastructure to other application areas and omics research domains.
DOI: 10.5524/100530
title: Supporting data for "NanoAmpli-Seq: A workflow for amplicon sequencing for mixed microbial communities on the nanopore sequencing platform."

description: Amplicon sequencing on Illumina sequencing platforms leverages their deep sequencing and multiplexing capacity, but is limited in genetic resolution due to short read lengths. While Oxford Nanopore or Pacific Biosciences platforms overcome this limitation, their application has been limited due to higher error rates or smaller data output. In this study, we introduce an amplicon sequencing workflow, i.e., NanoAmpli-Seq, that builds on Intramolecular-ligated Nanopore Consensus Sequencing (INC-Seq) approach and demonstrate its application for full-length 16S rRNA gene sequencing. NanoAmpli-Seq includes vital improvements to the aforementioned protocol that reduces sample-processing time while significantly improving sequence accuracy. The developed protocol includes chopSeq software for fragmentation and read orientation correction of INC-Seq consensus reads while nanoClust algorithm was designed for read partitioning-based de novo clustering and within cluster consensus calling to obtain full-length 16S rRNA gene sequences. The datafiles and protocols provided here represent the intermediate files during data processing and associated detailed workflow.
DOI: 10.5524/100531
title: Supporting data for 'SMRT long reads and Direct Label and Stain optical maps allow the generation of a high-quality genome assembly for the European barn swallow (Hirundo rustica rustica)'

description: The barn swallow (<i>Hirundo rustica</i>) is a migratory bird that has been the focus of a large number of ecological, behavioural and genetic studies. To facilitate further population genetics and genomic studies, here we present a reference genome assembly for the European subspecies (<i>H. r. rustica</i>). <br>As part of the Genome10K (G10K) effort on generating high quality vertebrate genomes, we have assembled a highly contiguous genome assembly using Single Molecule Real-Time (SMRT) DNA sequencing and several Bionano optical map technologies. We compared and integrated optical maps derived both from the Nick, Label, Repair and Stain and from the Direct Label and Stain (DLS) technologies. As proposed by Bionano, the DLS more than doubled the scaffold N50 with respect to the nickase. The dual enzyme hybrid scaffold led to a further marginal increase in scaffold N50 and an overall increase of confidence in the scaffolds. After removal of haplotigs, the final assembly is approximately 1.21 Gbp in size, with a scaffold N50 value of over 25.95 Mbp. <br>This high-quality genome assembly represents a valuable resource for further studies of population genetics and genomics in the barn swallow, and for studies concerning the evolution of avian genomes. It also represents one of the very first genomes assembled by combining SMRT long-read sequencing with the new Bionano DLS technology for scaffolding. The quality of this assembly demonstrates the potential of this methodology to substantially increase the contiguity of genome assemblies.
DOI: 10.5524/100534
title: Supporting data for "Annotation of the Giardia proteome through structure-based homology and machine learning"

description: Large-scale computational prediction of protein structures represents a cost-effective alternative to empirical structure determination with particular promise for non-model organisms and neglected pathogens. Conventional sequence-based tools are insufficient to annotate the genomes of such divergent biological systems. Conversely, protein structure tolerates substantial variation in primary amino acid sequence, and is thus a robust indicator of biochemical function. Structural proteomics is poised to become a standard part of pathogen genomics research, however informatic methods are now required to assign confidence in large volumes of predicted structures. <br>To predict the proteome of a neglected human pathogen, Giardia duodenalis, and stratify predicted structures into high- and lower-confidence categories using a variety of metrics in isolation and combination. <br> We used the I-TASSER suite to predict structural models for ~5000 proteins encoded in Giardia duodenalis and identify their closest empirically determined structural homologues in the Protein Data Bank. Models were assigned to high or lower-confidence categories depending on the presence of matching PFAM domains in query and reference peptides. Metrics output from the suite and derived metrics were assessed for their ability to predict the high confidence category individually, and in combination through development of a random forest classifier. <br>We identified 1095 high confidence models including 212 hypothetical proteins. Amino acid identity between query and reference peptides was the greatest individual predictor of high confidence status, however the random forest classifier out-performed any metric in isolation (AUC = 0.977), and identified a subset of 305 high confidence-like models, corresponding to false positive predictions. High confidence models exhibited higher transcriptional abundance, and the classifier generalized across species, indicating the broad utility of this approach for automatically stratifying predicted structures. Additional structure-based clustering was used to cross-check confidence predictions in an expanded family of Nek kinases. Several high confidence-like proteins yielded substantial new insight into mechanisms of redox balance in Giardia duodenalis a system central to the efficacy of limited anti-giardial drugs.
DOI: 10.5524/100539
title: Supporting data for "A micro X-ray computed tomography dataset of fossil echinoderms in an ancient obrution bed: a robust method for taphonomic and palaeoecologic analyses"

description: Taphonomic and palaeoecologic studies of obrution beds often employ conventional methods of investigation such as physical removal and extraction of fossils from their sedimentary rock matrix by mechanical preparation. This often-destructive method is not suitable for studying mouldic fossiliferous beds which, due to dissolution of the fossils in post-depositional processes and diagenesis, only contain impressions of the organisms in voids left in host sedimentary rocks. Micro computed tomography (µCT) scan data of 24 fossiliferous rock samples revealed thousands of Paleozoic echinoderms and digitally stitching together individually µCT scanned rock samples within 3D space allows for quantifiable taphonomic data on a fossil echinoderm-rich obrution deposit. A brief step-by-step guide is provided on creating, segmenting and ultimately combining sections of a richly fossiliferous bed to create a virtual model of the bed suited for the quantitative and qualitative taphonomic analysis of a marine benthic assemblage from the Devonian (Emsian) of South Africa. The use of visualising the internal features of fossiliferous beds in 3D is an invaluable taphonomic tool for analysing delicate fossils, accounting for all specimens irrespective of their preservation stages and without damaging the. The technique is particularly useful for analysing fossiliferous deposits with highly mouldic fossils that prove to be difficult to study with traditional methods, because the method relies on the large density contrast between the natural cast and host rock.
DOI: 10.5524/100541
title: Supporting data for "SMAGEXP: a galaxy tool suite for transcriptomics data meta-analysis"

description: With the proliferation of available microarray and high throughput sequencing experiments in the public domain, the use of meta-analysis methods increases. In these experiments, where the sample size is often limited, meta-analysis offers the possibility to considerably enhance the statistical power and give more accurate results. For those purposes, it combines either effect sizes or results of single studies in a appropriate manner. R packages metaMA and metaRNASeq perform meta-analysis on microarray and NGS data, respectively. They are not interchangeable as they rely on statistical modeling specific to each technology.<br> SMAGEXP (Statistical Meta-Analysis for Gene EXPression) integrates metaMA and metaRNAseq packages into Galaxy. We aim to propose a unified way to carry out meta-analysis of gene expression data, while taking care of their specificities. We have developed this tool suite to analyse microarray data from Gene Expression Omnibus (GEO) database or custom data from affymetrix microarrays. These data are then combined to carry out meta-analysis using metaMA package. SMAGEXP also offers to combine raw read counts from Next Generation Sequencing (NGS) experiments using DESeq2 and metaRNASeq package. In both cases, key values, independent from the technology type, are reported to judge the quality of the meta-analysis. These tools are available on the Galaxy main tool shed. Source code, help and installation instructions are available on github. <br>The use of Galaxy offers an easy-to-use gene expression meta-analysis tool suite based on the metaMA and metaRNASeq packages.