cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/100474
title: Supporting data for "PhenoSpD: an integrated toolkit for phenotypic correlation es-timation and multiple testing correction using GWAS summary statistics"

description: Identifying phenotypic correlations between complex traits and diseases can provide useful etiological insights. Restrict-ed access to much individual-level phenotype data makes it difficult to estimate large-scale phenotypic correlation across the human phenome. Two state-of-the-art methods, metaCCA and LD score regression, provide an alternative approach to estimate phenotypic correlation using only genome-wide association study (GWAS) summary results. <br>Here, we present an integrated R toolkit, PhenoSpD, to 1) use LD score regression to estimate phenotypic correlations using GWAS summary statistics; and 2) utilize the estimated phenotypic correlations to inform correction of multiple testing for complex human traits using the spectral decomposition of matrices (SpD). The simulations suggest 1) it is pos-sible to identify non-independence of phenotypes using samples with partial overlap, as overlap decreases the estimated phenotypic correlations will attenuate towards zero and multiple testing correction will be more stringent than in perfectly overlapping samples; 2) in contrast to LD score regression, metaCCA will provide approximate genetic correlations rather than phenotypic correlation, which limits its application for multiple testing correction. In a case study, PhenoSpD using UK Biobank GWAS results suggested 399.6 independent tests among 487 human traits, which is close to the 352.4 inde-pendent tests estimated using true phenotypic correlation. We further applied PhenoSpD to an estimated 5618 pair-wise phenotypic correlations among 107 metabolites using GWAS summary statistics from Kettunen et al. and PhenoSpD suggested the equivalent of 33.5 independent tests for theses metabolites. <br>PhenoSpD extends the use of summary level results, providing a simple and conservative way to reduce dimensionality for complex human traits using GWAS summary statistics. This is particularly valuable in the age of large-scale biobank and consortia studies, where GWAS results are much more accessible than individual-level data. <br>R code and documentation for PhenoSpD V1.0.0 is available online https://github.com/MRCIEU/PhenoSpD.
DOI: 10.5524/100476
title: Supporting data for "A workflow for simplified analysis of ATAC-cap-seq data in R"

description: ATAC-cap-seq is a high-throughput sequencing method that combines targeted nucleic acid enrichment of precipitated DNA fragments with an upstream ATAC-seq step. There are increased analytical difficulties arising from working with a set of regions of interest that may be small in number and biologically dependent. Common statistical pipelines for RNAseq might be assumed to apply but can give misleading results on ATAC-cap-seq data. A tool is needed to allow a non-specialist user to quickly and easily summarise data and apply sensible and effective normalisation and analysis. We developed atacR to allow a user to easily analyse their ATAC enrichment experiment. It provides comprehensive summary functions and diagnostic plots for studying enriched tag abundance. Applying between-sample normalisation is made straightforward and functions for normalising based on user-defined control regions, whole library size and regions selected from the least variable regions in a dataset are provided. Three methods for detecting differential abundance of tags from enriched methods are provided, including Bootstrap t, Bayes Factor and a wrapped version of the standard exact test in the edgeR package. We compared the precision, recall and F-score of each detection method on resampled datasets at varying replicate, significance threshold and genes changed, we found that the Bayes factor method had greatest overall detection power, though edgeR was slightly stronger in simulations with lower numbers of genes changed. Our package allows a non-specialist user to easily and effectively apply methods appropriate to the analysis of ATAC-cap-seq in a reproducible manner. The package is implemented in pure R and is fully interoperable with common workflows in Bioconductor.
DOI: 10.5524/100478
title: Supporting data for "Clustering trees: a visualisation for evaluating clusterings at multiple resolutions"

description: Clustering techniques are widely used in the analysis of large data sets to group together samples with similar properties. For example, clustering is often used in the field of single-cell RNA-sequencing in order to identify different cell types present in a tissue sample. There are many algorithms for performing clustering and the results can vary substantially. In particular, the number of groups present in a data set is often unknown and the number of clusters identified by an algorithm can change based on the parameters used. To explore and examine the impact of varying clustering resolution we present clustering trees. This visualisation shows the relationships between clusters at multiple resolutions allowing researchers to see how samples move as the number of clusters increases. In addition, meta-information can be overlaid on the tree to inform the choice of resolution and guide in identification of clusters. We illustrate the uses of clustering trees using two examples, the classical iris dataset and a complex single-cell RNA-sequencing dataset.
DOI: 10.5524/100480
title: Supporting data for "The chromosome-level genome assemblies of two rattans (Calamus simplicifolius and Daemonorops jenkinsiana)"

description: <i>Calamus simplicifolius</i> and <i>Daemonorops jenkinsiana</i> are two representative rattans, as the most significant material sources for the rattan industry. However, the lack of reference genome sequences is a major obstacle for basic and applied biology on rattan. <br>We rendered the two chromosome-level genome assemblies of <i>C. simplicifolius</i> and <i>D. jenkinsiana</i> using the Illumina, PacBio, and Hi-C sequencing data. A total of ~730 Gb and ~682 Gb of raw data covered the predicted genome length (~1.98 Gb of <i>C. simplicifolius</i> and ~1.61 Gb of <i>D. jenkinsiana</i>) to ~ 372× and ~ 426× read depth, respectively. The two de novo genome assemblies of ~1.94 Gb and ~1.58 Gb are generated with the scaffold N50 of ~160 Mb and ~119 Mb in <i>C. simplicifolius</i> and <i>D. jenkinsiana</i>, respectively. The <i>C. simplicifolius</i> and <i>D. jenkinsiana</i> genome were predicted to harbor 51,235 and 53,342 intact protein-coding gene models, respectively. BUSCO evaluation demonstrated that the genome completeness reached 96.4% and 91.3% in the <i>C. simplicifolius</i> and <i>D. jenkinsiana</i> genome, respectively. Genome evolution showed that four Arecaceae plants were located in a cluster and the divergence time between the two rattans was ~19.3 Mya. Additionally, we genome-widely identified 193 and 172 genes involved in the lignin biosynthesis pathway in <i>C. simplicifolius</i> and <i>D. jenkinsiana</i>, respectively. <br> We present the first de novo assemblies of the two rattan genomes (<i>C. simplicifolius</i> and <i>D. jenkinsiana</i>). These essential data will not only provide a fundamental resource of functional genomics particularly in promoting germplasm utilization for breeding improved rattan material property, but also will serve as two reference genomes for performing comparative studies between and among different species.
DOI: 10.5524/100481
title: Supporting data for "ANNOgesic: A Swiss army knife for the RNA-Seq based annotation of bacterial/archaeal genomes"

description: To understand the gene regulation of an organism of interest, a comprehensive genome annotation is essential. While some features, such as coding sequences, can be computationally predicted with high accuracy based purely on the genomic sequence, others, such as promoter elements or non-coding RNAs are harder to detect. RNA-Seq has proven to be an efficient method to identify these genomic features and to improve genome annotations. However, processing and integrating RNA-Seq data in order to generate high-resolution annotations is challenging, time consuming and requires numerous different steps. We have constructed a powerful and modular tool called ANNOgesic that provides the required analyses and simplifies RNA-Seq-based bacterial and archaeal genome annotation. It can integrate data from conventional RNA-Seq and dRNA-Seq, predicts and annotates numerous features, including small non-coding RNAs, with high precision. The software is available under an open source license (ISCL) at https://pypi.org/project/ANNOgesic/.
DOI: 10.5524/100489
title: Supporting data for "Draft genome of <i>Glyptosternon maculatum</i>, an endemic fish from Tibet-plateau"

description: Mechanisms for high altitude adaption have arisen widespread interest to evolution biologists. Several genome wide studies have been carried out for endemic vertebrates in Tibet, including mammals, birds and amphibians. However, little information was known about the adaptive evolution of highland fishes. <i>Glyptosternon maculatum</i> (G. maculatum, Regan, 1905), also known as Regan or barkley, is a fish endemic to the Tibetan plateau, which belongs to Sisoridae family, Siluriformes (catfishes) order. This species live within an elevation ranging from roughly 2800 m to 4200 m. Hence, a high-quality reference genome of <i>G. maculatum</i> provides an opportunity to address high altitude adaption mechanisms of fishes.<br>To get a high-quality reference genome of <i>G. maculatum</i>, we combined PacBio single-molecule real-time sequencing, Illumina paired-end sequencing, 10X Genomics linked-reads and BioNano optical map techniques. In total, 603.99 Gb sequencing data were generated. The assembled genome was about 662.34 Mb with scaffold and contig N50 sizes of 20.90 Mb and 993.67 kb, respectively, which captured 83% complete and 3.9% partial vertebrate Benchmarking Universal Single-copy orthologs (BUSCO). Repetitive elements account for 35.88% of the genome, and 22,066 protein-coding genes were predicted from the genome, of which 91.7% have been functionally annotated.<br>We provide the first comprehensive de novo genome of the <i>G. maculatum</i>. This genetic resource is fundamental for investigating the origin of the <i>G. maculatum</i> and will improve our understanding of high altitude adaption of fishes. The assembled genome can also be used as reference for future population genetic studies of <i>G. maculatum</i>.
DOI: 10.5524/100490
title: Supporting data for "A draft genome assembly of the Chinese sillago (Sillago sinica), the first reference genome for Sillaginidae fishes"

description: Sillaginidae, also known as smelt-whitings, is a family of benthic coastal marine fishes in the Indo-West Pacific that have high ecological and economic importance. Many Sillaginidae species, including the Chinese sillago (<i>Sillago sinica</i>) are recently described in China, providing us with valuable materials to analyze genetic diversification of the family Sillaginidae. Herein, we constructed a reference genome for the Chinese sillago, with the aim to setup a platform for comparative analysis of all species in this family.<br>Using the single-molecule real-time DNA sequencing platform PacBio Sequel, we generated ~27.3 Gb genomic DNA sequences for the Chinese sillago. We reconstructed a genome assembly of 534 Mb using a strategy that taking advantage of complementary strengths of two genome assembly programs Canu and FALCON. The genome size was consistent with the estimated genome size based on Kmer analysis. The assembled genome consisted of 802 contigs with a contig N50 length of 2.6 Mb. We annotated 22,122 protein-coding genes in the Chinese sillago genomes using de novo method and with RNA-seq data and homologies to other teleosts. According to the phylogenetic analysis using protein-coding genes, Chinese sillago was closely related to Larimichthys Crocea and Dicentrarchus labrax, and Chinese sillago diverged from their ancestor around 69.5 - 82.6 million years ago.<br>Using long reads generated with PacBio sequencing technology, we have built a draft genome assembly for the Chinese sillago, which is the first reference genome for Sillaginidae species. This genome assembly sets a stage for comparative analysis of the diversification and adaptation of fishes in Sillaginidae.
DOI: 10.5524/100494
title: Supporting data for "Metabolomics Investigation of Dietary Effects on Flesh Quality in Grass Carp (Ctenopharyngodon idellus)"

description: The ultra-high density intensive farming model of grass carp (<em>Ctenopharyngodon idellus</em>) may elicit growth inhibition, decline flesh quality and increase disease susceptibility of fish. The quality degradation and excessive fat accumulation in cultured <i>C. idellus</i> have long been attributed to possible alterations in the lipid metabolism of fish muscle tissues as a result of over-nutrition from artificial diets. To investigate the effects of different diets on fish muscle quality, a large-scale metabolomics study was performed on 250 tails of <i>C. idellus</i><br>. The experimental fish were divided into four groups based on sex and diets - female artificial feed (FAF), female grass feed (FGF), male artificial feed (MAF) and male grass feed (MGF). After 113 days rearing period, the AF group showed significantly higher total mass of muscle fat (P &lt; 0.01), with the FAF group being the highest. Metabolomics profiling based on liquid chromatography-mass spectrometry (LC-MS) revealed distinctive patterns of clustering according to the four groups. Overall, artificial feeding was associated with higher concentrations of docosapentaenoic acid (DPA), dihomo-gamma-linolenic acid (DGLA) and arachidonic acid (ARA); whereas grass-feeding was associated with elevated n-3 unsaturated fatty acids (n-3 UFAs), such as eicosapentaenoic acid (EPA), alpha-linolenic acid (ALA) and gamma-linolenic acid (GLA). Artificial feeding also resulted in significant increased docosahexaenoic acid (DHA) in MAF muscle than MGF fish, whereas no significance in the comparison of female samples. Metabolic pathway analyses using both targeted and untargeted approaches consistently revealed that the arachidonic acid metabolism and steroid hormone biosynthesis pathways were significantly different between AF and GF groups. <br> Our results suggested that grass is a better source of diet fatty acid and protein when compared to artificial feed. Grass feeding could effectively lower triglycerides in serum, reduce fat accumulation and alter lipid compositions in fish muscle by increasing the concentrations of n-3 UFAs, leading to better nutrition and health.
DOI: 10.5524/100495
title: Supporting data for "Ximmer: A System for Improving Accuracy and Consistency of CNV Calling from Exome Data"

description: While exome and targeted next generation DNA sequencing are primarily used for detecting single nucleotide changes and small indels, detection of copy number variants (CNVs) can provide highly valuable additional information from the data. Although there are dozens of exome CNV detection methods available, these are often difficult to use and accuracy varies unpredictably between and within data sets. <br>We present Ximmer, a tool which supports an end to end process for evaluating, tuning and running analysis methods for detection of CNVs in germline samples. Ximmer includes a simulation framework, implementations of several commonly used CNV detection methods, and a visualisation and curation tool which together enable interactive exploration and quality control of CNV results. Using Ximmer, we comprehensively evaluate CNV detection on four data sets using five different detection methods. We show that application of Ximmer can improve accuracy and aid in quality control of CNV detection results. In addition, Ximmer can be used to run analyses and explore CNV results in exome data.<br>Ximmer offers a comprehensive tool and method for applying and improving accuracy of CNV detection methods for exome data.
DOI: 10.5524/100496
title: Supporting data for "Single-cell RNA-seq reveals dynamic transcriptome profiling in human early neural differentiation"

description: Investigating cell fate decision and subpopulation specification in the context of the neural lineage is fundamental to understanding neurogenesis and neurodegenerative diseases. The differentiation process of neural-tube-like rosettes in vitro is representative of neural tube structures, which are composed of radially organized, columnar epithelial cells and give rise to functional neural cells. However, the underlying regulatory network of cell fate commitment during early neural differentiation remains elusive. In this study, we investigated the genome-wide transcriptome profile of single cells from six consecutive reprogramming and neural differentiation time points and identified cellular subpopulations present at each differentiation stage. Based on the inferred reconstructed trajectory and the characteristics of subpopulations contributing the most towards commitment to the central nervous system (CNS) lineage at each stage during differentiation, we identified putative novel transcription factors in regulating neural differentiation. In addition, we dissected the dynamics of chromatin accessibility at the same differentiation stages and revealed active cis-regulatory elements for transcription factors known to have a key role in neural differentiation as well as for those that we suggest are also involved. Further, communication network analysis demonstrated that cellular interactions most frequently occurred among embryo body (EB) stage and each cell subpopulation possessed a distinctive spectrum of ligands and receptors associated with neural differentiation, which could reflect the identity of each subpopulation. Our study provides a comprehensive and integrative study of the transcriptomics and epigenetics of human early neural differentiation, which paves the way for a deeper understanding of the regulatory mechanisms driving the differentiation of the neural lineage.
DOI: 10.5524/100497
title: Supporting data for "Fractalis: A scalable open-source service for platform-independent interactive visual analysis of biomedical data"

description: Translational research platforms share the aim to promote a deeper understanding of stored data by providing visualization and analysis tools for data exploration and hypothesis generation. However, such tools are usually platform-bound and are not easily reusable by other systems. Furthermore, they rarely address access restriction issues when direct data transfer is not permitted. In this article we present an analytical service that works in tandem with a visualization library to address these problems. Using a combination of existing technologies and a platform-specific data abstraction layer we developed a service that is capable of providing existing web-based data warehouses and repositories with platform-independent visual analytical capabilities. The design of this service also allows for federated data analysis by eliminating the need to move the data directly to the researcher. Instead, all operations are based on statistics and interactive charts without direct access to the dataset. The software presented in this article has a potential to help translational researchers achieve a better understanding of a given dataset and quickly generate new hypothesis. Furthermore, it provides a framework that can be used to share and reuse explorative analysis tools within the community.
DOI: 10.5524/100498
title: Supporting data for "Chromosome-level reference genome and alternative splicing atlas of moso bamboo (Phyllostachys edulis)"

description: Bamboo is one of the most important non-timber forest products worldwide. However, a chromosome-level reference genome is lacking, and the evolutionary landscape of alternative splicing (AS) in bamboo remains unclear despite emerging data and improved technologies. Here, we provide a chromosome-level de novo genome assembly of the moso bamboo (Phyllostachys edulis) using additional abundance data and different assembly strategies. The significantly improved genome is a Scaffold N50 of 79.90 Mb, approximately 243 times longer than the previous version, and 51,074 high-quality protein-coding loci with intact structures were identified using single-molecule real-time sequencing and manual verification. Moreover, we provide a comprehensive AS profile based on the identification of 266,771 uniform AS events in 25,225 AS genes by large-scale transcriptomic sequencing of 26 representative bamboo tissues using both the Illumina and PacBio sequencing platforms. Via comparison with orthologous genes in related plants, we observed dramatic evolutionary characteristics, suggesting that the AS genes are concentrated in more conserved genes that tend to accumulate higher expressed transcripts and share less specificity. Furthermore, gene family expansion, abundant AS and positive selection were identified in crucial genes involved in lignin biosynthesis, indicating that moso bamboo's specificity in being a woody plant in the grass family. These fundamental studies provide useful information for future studies performing in-depth analyses of comparative genome and AS features. Additionally, our results highlight a global perspective of AS during evolution and diversification in bamboo.
DOI: 10.5524/100506
title: Supporting data for "Chromosomal-level assembly of yellow catfish genome using third-generation DNA sequencing and Hi-C analysis"

description: The yellow catfish, Pelteobagrus fulvidraco, belonging to Siluriformes order, is an important economic freshwater aquaculture fish species in Asia, especially in south China. Recently, the aquaculture industry is facing tremendous challenges in germplasm degeneration and poor diseases resistance. Meanwhile, yellow catfish exhibits notable sex dimorphism on growth rate that adult males are about two to three fold bigger than females. How aquaculture industry takes advantage of such sex dimorphism is another challenge. To address these challenges, a high-quality reference genome of the yellow catfish is needed. To construct a high-quality reference genome for yellow catfish, we generated 51.2 Gb short reads and 38.9 Gb long reads using Illumina and PacBio platforms, respectively. The sequencing data were assembled into 732.8 Mb genome assembly with contig N50 length of 1.1 Mb. Additionally, we applied Hi-C technology to identify contacts among contigs, which were then used to assemble contigs into scaffolds, resulting in a genome assembly with 26 chromosomes, and a scaffold N50 length of 25.8 Mb. Using 24,552 protein-coding genes annotated in yellow catfish genome, the phylogenetic relationships of the yellow catfish with other teleosts showed that yellow catfish separated from the common ancestor of channel catfish ~81.9 million years ago. 1,717 gene families were identified to be expanded in yellow catfish and those gene families are mainly enriched in immune system, signal transduction, glycosphingolipid biosynthesis and fatty acid biosynthesis. Taking advantage of Illumina, PacBio and Hi-C technologies, we constructed the first high-quality chromosomal-level genome assembly for the yellow catfish P. fulvidraco. The genomic resources generated in this work not only offered valuable reference genome for functional genomics studies of yellow catfish to decipher the economic traits and sex determination, but also provided important chromosome information for genome comparisons in broad evolutionary research community.