cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/101023
title: Genomic data of the Speckled mousebird (<em>Colius striatus</em>).

description: The Speckled Mousebird (<em>Colius striatus</em> (Gmelin, 1789)) is the largest species of mousebird and named because of its overall mousey-brown colour. The bird can be found from Cameroon to Eritrea and Ethiopia, and southern South Africa. Described as a noisy creature, it is not however, known for its voice, and is a rather social bird often observed feeding in groups. <br>These data have been produced as part of the Avian Phylogenomic Project. DNA was collected from a male specimen at the Copenhagen Zoo in Denmark, tended to by Mads Bertelsen, now vouchered (138165) at the Natural History Museum of Denmark. We sequenced the genome to a depth of approximately 27X. The assembled scaffolds of high quality sequences total 1.08Gb, with the contig and scaffold N50 values of 18kb and 45kb respectively. We identified 13,538 protein-coding genes with a mean length of 12.4kb.<br>
DOI: 10.5524/101024
title: Genomic data of the Sunbittern (<em>Eurypyga helias</em>).

description: The Sunbittern (<em>Eurypyga helias helias</em> (Pallas, 1781)) is the sole member of the family Eurypygidae and is found in Central to South America from Mexico, Peru to Brazil. It has similar morphological features to the Kagu of New Caledonia and is a non-migrant bird that is normally found on the ground scratching for insects. <br>
These data have been produced as part of the Avian Phylogenomics Project. DNA was collected from a female from the Odense Zoo in Denmark, of an animal obtained by Mads Bertelsen. We sequenced the genome to a depth of approximately 33X. <br>
The assembled scaffolds of high quality sequences total 1.1Gb, with the contig and scaffold N50 values of 16kb and 46kb respectively. We identified 13,974 protein-coding genes with a mean length of 12.3kb. <br>
DOI: 10.5524/101025
title: Genomic data of the Northern Fulmar (<em>Fulmarus glacialis</em>).

description: The Northern Fulmar (<em>Fulmarus glacialis glacialis</em> (Linnaeus, 1761)), also known as Fulmar or Arctic Fulmar, is a highly abundant sea bird and commonly found in north Pacific and north Atlantic subarctic regions. It is a member of the Procellariidae family, which include petrels and shearwaters, and like other petrels, the Northern Fulmar's walking ability is limited but is a very a strong flier. <br>
These data have been produced as part of the Avian Phylogenomics Project. DNA was collected from a vouchered sample (137838) of Natural History Museum of Denmark from a male caught in Denmark. We sequenced the genome to a depth of approximately 33X. <br>
The assembled scaffolds of high quality sequences total 1.14Gb, with the contig and scaffold N50 values of 17kb and 46kb respectively. We identified 14,306 protein-coding genes with a mean length of 12.8kb. <br>
DOI: 10.5524/101026
title: Genomic data of the Red throated loon (<em>Gavia stellata</em>).

description: The Red-throated Loon (<em>Gavia stellata </em> (Pontoppidan, 1763)), also known as the Red-throated Diver, is a migratory aquatic bird that breeds mainly in the Arctic regions and spends winters in the northern coastal waters. The Red-throated loon has a large global population, making it the most widely distributed member of the Gaviidae (Loon or Diver) family. <br>
These data have been produced as part of the Avian Phylogenomics Project. DNA was collected from a vouchered sample (137940) of Natural History Museum of Denmark from a male caught in Denmark. We sequenced the genome to a depth of approximately 33X. <br>
The assembled scaffolds of high quality sequences total 1.15Gb, with the contig and scaffold N50 values of 16kb and 45kb respectively. We identified 13,454 protein-coding genes with a mean length of 13.2kb. <br>
DOI: 10.5524/101027
title: Genomic data of the White tailed eagle (<em>Haliaeetus albicilla</em>).

description: The White tailed eagle (<em>Haliaeetus albicilla groenlandicus</em> (Brehm, 1831)) is one of the largest birds of prey belonging to the Accipitridae family and is considered a close cousin of the Bald Eagle. The White-tailed eagle is a large bird with a wingspan that measures 1.782.45 m, and is an apex predator, meaning it is a predator with no predators of its own. <br>
These data have been produced as part of the Avian Phylogenomics Project. DNA was collected from a vouchered sample (137926) of Natural History Museum of Denmark from a male caught in Greenland. We sequenced the genome to a depth of approximately 26X. <br>
The assembled scaffolds of high quality sequences total 1.14Gb, with the contig and scaffold N50 values of 20kb and 56kb respectively. We identified 13,831 protein-coding genes with a mean length of 14.2kb. <br>
DOI: 10.5524/100980
title: Supporting data for "How to remove or control confounds in predictive models, with applications to brain biomarkers"

description: With increasing data sizes and more easily available computational methods, neurosciences rely more and more on predictive modeling with machine learning, eg to extract biomarkers of pathologies. Yet, a successful prediction may capture a confounding effect correlated with the outcome instead of brain features specific to the outcome of interest e.g. the pathology. For instance, as patients tend to move more in the scanner than controls, imaging biomarkers of a pathology may mostly reflect head motion, leading to inefficient use of resources and wrong interpretation of the biomarkers. Here we study how to adapt statistical methods that control for confounds to predictive modeling settings. We review how to train predictors that are not driven by such spurious effects. We also show how to measure the unbiased predictive accuracy of these biomarkers, based on a confounded dataset. For this purpose, cross-validation must be modified to account for the nuisance effect. To guide understanding and practical recommendations, we apply various strategies to assess predictive models in the presence of confounds on simulated data and population brain imaging settings. Theoretical and empirical studies show that deconfounding should not be applied to the train and test data jointly: modeling the effect of confounds, on the train data only, should instead be decoupled from removing confounds. Cross-validation that isolates nuisance effects gives an additional piece of information: confound-free prediction accuracy.
DOI: 10.5524/100981
title: Supporting data for "Benchmarking missing-values approaches for predictive models on health databases"

description: As databases grow larger, it becomes harder to fully control their collection, and they frequently come with missing values: incomplete observations. These large databases are well suited to train machine-learning models, for instance for forecasting or to extract biomarkers in biomedical settings. Such predictive approaches can use discriminative, rather than generative, modeling, and thus open the door to new missing-values strategies. Yet existing empirical evaluations of strategies to handle missing values have focused on inferential statistics.<br>Here we conduct a systematic benchmark of missing-values strategies in predictive models with a focus on large health databases: four electronic health record datasets, a population brain imaging one, a health survey and two intensive care ones. Using gradient-boosted trees, we compare native support for missing values with simple and state-of-the-art imputation prior to learning. We investigate prediction accuracy and computational time. For prediction after imputation, we find that adding an indicator to express which values have been imputed is important, suggesting that the data are missing not at random. Elaborate missing values imputation can improve prediction compared to simple strategies but requires longer computational time on large data. Learning trees that model missing values, with missing incorporated attribute, leads to robust, fast, and well-performing predictive modeling.<br>Native support for missing values in supervised machine learning predicts better than state-of-the-art imputation with much less computational cost. When using imputation, it is important to add indicator columns expressing which values have been imputed.
DOI: 10.5524/100983
title: Supporting data for "KOREF_S1: the phased, parental Trio-binned Korean reference genome using long-reads and Hi-C sequencing methods"

description: KOREF is the Korean reference genome which was constructed with various sequencing technologies including long reads, short reads, and optical mapping methods. It is also the first East Asian multiomic reference genome accompanied by extensive clinical information, time series and multiomic data, and his parental sequencing data. However, it was still not a chromosome-scale reference. Here, we updated the previous KOREF assembly to a new chromosome-level haploid assembly of KOREF, KOREF_S1v2.1. ONT PromethION, PacBio HiFi-CCS, and Hi-C technology were used to build the most accurate East Asian reference assembled so far.<br>We produced 705 Gb ONT reads and 114 Gb PacBio HiFi reads, and corrected ONT reads by PacBio reads. The corrected ultra-long reads reached higher accuracy of 1.4% base-errors than the previous KOREF_S1v1.0, which was mainly built with short reads. KOREF has parental genome information, and we successfully phased it using a trio-binning method acquiring a near-complete haploid-assembly. The final assembly resulted in total length of 2.9 Gb with an N50 of 150 Mb, and the longest scaffold covered 97.3% of GRCh38s chromosome 2. And the final assembly showed high base accuracy, less than 0.01% of base-errors.<br>KOREF_S1v2.1 is the first chromosome-scale haploid assembly of the Korean reference genome with high contiguity and accuracy. Our study provides useful resources of the Korean reference genome and demonstrates a new strategy of hybrid assembly which collaborates ONTs PromethION and PacBios HiFi-CCS.
DOI: 10.5524/100985
title: Supporting data for "Genome of the ramshorn snail Biomphalaria straminea - an obligate intermediate host of schistosomiasis"

description: Schistosomiasis or bilharzia is a parasitic disease caused by trematode flatworms of the genus Schistosoma. Infection of <i>Schistosoma mansoni</i> in humans results when cercariae emerge into water from freshwater snails in the genus Biomphalaria, and seek out and penetrate human skin. The snail <i>Biomphalaria straminea</i> is native to South America and is now also present in Central America and China, and represents a potential vector host for spreading schistosomiasis. To date, genomic information for the genus is restricted to the neotropical species <i>Biomphalaria glabrata</i>. This limits understanding of the biology and management of other schistosomiasis vectors, such as <i>B. straminea</i>.<br>Using a combination of Illumina short read, 10X Genomics linked read, and Hi C sequencing data, our 1.005 Gbp <i>B. straminea</i> genome assembly is of high contiguity, with a scaffold N50 of 25.3 Mbp. Transcriptomes from adults were also obtained. Developmental homeobox genes, hormonal genes, and stress-response genes were identified, and repeat content was annotated (40.68% of genomic content). Comparisons with other mollusc genomes (including Gastropoda, Bivalvia and Cephalopoda) revealed syntenic conservation, patterns of homeobox gene linkage indicative of evolutionary changes to gene clusters, expansion of heat shock protein genes, and the presence of sesquiterpenoid and cholesterol metabolic pathway genes in Gastropoda. In addition, hormone treatment together with RT-qPCR assay reveal a sesquiterpenoid hormone responsive system in <i>B. straminea</i>, illustrating this renowned insect hormonal system is also present in the lophotrochozoan lineage. <br>This study provides the first genome assembly for the snail <i>B. straminea</i> and offers an unprecedented opportunity to address a variety of biology related to snail vectors of schistosomiasis, as well as evolutionary and genomics questions related to molluscs more widely.
DOI: 10.5524/100988
title: Supporting data for "Fast and accurate estimation of multidimensional site frequency spectra from low-coverage high-throughput sequencing data"

description: The site frequency spectrum summarises the distribution of allele frequencies throughout the genome, and it is widely used as a summary statistic to infer demographic parameters and to detect signals of natural selection. The use of high-throughput low-coverage DNA sequencing data can lead to biased estimates of the site frequency spectrum due to high levels of uncertainty in genotyping. <br>Here we design and implement a method to efficiently and accurately estimate the multidimensional site frequency spectrum for large numbers of haploid or diploid individuals across an arbitrary number of populations, using low-coverage sequencing data. The method maximises a likelihood function that represents the probability of the sequencing data observed given a multi-dimensional site frequency spectrum using genotype likelihoods. Notably, it uses an advanced binning heuristic paired with an accelerated expectation-maximisation algorithm for a fast and memory-efficient computation, and can generate both unfolded and folded spectra and bootstrapped replicates for haploid and diploid genomes. Based on extensive simulations, we show that the new method requires remarkably less storage and is faster than previous implementations whilst retaining the same accuracy. When applied to low-coverage sequencing data from the fungal pathogen <i>Neonectria neomacrospora</i>, results recapitulate the patterns of population differentiation generated using the original high-coverage data. <br>The new implementation allows for accurate estimation of population genetic parameters from arbitrarily large, low-coverage data sets, thus facilitating cost-effective sequencing experiments in model and non-model organisms.
DOI: 10.5524/100989
title: Supporting data for "Triku: a feature selection method based on nearest neighbors for single-cell data"

description: Feature selection is a relevant step in the analysis of single-cell RNA sequencing datasets. Most of the current feature selection methods are based on general univariate descriptors of the data such as the dispersion or the percentage of zeros. Despite the use of correction methods, the generality of these feature selection methods biases the genes selected towards highly-expressed genes, instead of the genes defining the cell populations of the dataset. <br>Triku is a feature selection method that favors genes defining the main cell populations. It does so by selecting genes expressed by groups of cells that are close in the <i>k</i> nearest neighbor graph. The expression of these genes is higher than the expected expression if the <i>k</i> cells were chosen at random. Triku efficiently recovers cell populations present in artificial and biological benchmarking datasets, based on ARI, NMI, supervised classification, and silhouette coefficient measurements. Additionally, gene sets selected by triku are more likely to be related to relevant Gene Ontology terms and contain fewer ribosomal and mitochondrial genes. <br> Triku is developed in Python 3 and is available at https://github.com/alexmascension/triku.
DOI: 10.5524/100991
title: Supporting data for "scMAPA: Identification of Cell-type-specific Alternative Polyadenylation in Complex Tissues"

description: Alternative polyadenylation (APA) causes shortening or lengthening of the 3'-untranslated region (3'-UTR) of genes (APA genes) in diverse cellular processes such as cell proliferation and differentiation (cell-type-specific APA). To identify cell-type-specific APA genes in scRNA-Seq data, current bioinformatic methods have several limitations. First, they assume certain read coverage shapes in the scRNA-Seq data, which can be violated in multiple APA genes. Second, their identification is limited between two cell types and not directly applicable to the data of multiple cell types. Third, they do not control undesired source of variance that potentially introduces noise to the cell-type-specific identification of APA genes. To address these limitations, we developed a combination of a computational change-point algorithm and a statistical model, single-cell Multi-group identification of APA (scMAPA). To avoid the assumptions on the read coverage shape, scMAPA formulates a change-point problem after transforming the 3' biased scRNA-Seq data to represent the full-length 3'UTR signal. To identify cell-type-specific APA genes while adjusting for undesired source of variation, scMAPA models APA isoforms in consideration of the cell types and the undesired source. In our novel simulation data and human peripheral blood monocellular data, scMAPA outperforms existing methods in terms of sensitivity, robustness, and stability. In mouse brain data consisting of multiple cell types sampled from multiple regions, scMAPA identifies cell-type-specific APA genes, elucidating novel roles of APA for dividing immune cells and differentiated neuron cells and in multiple brain disorders. Altogether, scMAPA elucidates the cell-type-specific function of APA events and sheds novel insights into the functional roles of APA events in complex tissues.
DOI: 10.5524/100993
title: Supporting data for "Manual curation and phylogenetic analysis of chitinase family genes in the Asian citrus psyllid, <i>Diaphorina citri</i>

description: Chitinases are enzymes that digest the polysaccharide polymer chitin. Chitin is a major component of insect exoskeletons, which must be replaced multiple times during growth and development in a process known as molting. Insect genomes usually have multiple chitinase genes, some of which are required for molting and some whose functions are still unknown. Since knockdown of the chitinases required for molting causes high levels of lethality, chitinase genes have drawn interest as targets for RNAi-based pest control methods. The Asian citrus psyllid, <i>Diaphorina citri</i>, carries the bacterium that causes Huanglongbing, also known as citrus greening disease, which is devastating the citrus industry worldwide. We have identified and annotated 12 chitinase family genes from <i>D. citri</i> as part of a community effort to create high quality gene models to facilitate the design of interdictory molecules for pest control. Using predicted protein domain content and phylogenetic analysis, we categorized the <i>D. citri</i> chitinases according to a previously established classification scheme and re-evaluated the classification of chitinases in other hemipterans. In addition to chitinases belonging to known groups, we identified a novel class of chitinases present in <i>D. citri</i> and several related hemipterans that appears to be the result of horizontal gene transfer.
DOI: 10.5524/100994
title: Supporting data for "Genomic identification, annotation, and comparative analysis of Vacuolar-type ATP synthase subunits in <i>Diaphorina citri</i>"

description: The hemipteran insect <i>Diaphorina citri</i>, or Asian citrus psyllid, is a vector for <i>Candidatus Liberibacter asiaticus</i> (CLas), the bacterium causing citrus greening disease, or Huanglongbing (HLB). Millions of citrus trees have been destroyed, and every grove in Florida, USA, has been directly affected by this disease. In eukaryotes, vacuolar-type ATP synthase (V-ATPase) is an abundant heterodimeric enzyme that serves the cell with essential compartment acidification through the active processes that transport protons across the membrane. Fifteen putative V-ATPase genes in the <i>D. citri</i> genome were manually curated. Comparative genomic analysis revealed that <i>D. citri</i> V-ATPase subunits share domains and motifs with other insects, including the V-ATPase-A superfamily domain. Phylogenetic analysis separates <i>D. citri</i> V-ATPase subunits into expected clades with orthologous sequences. Annotation of the <i>D. citri</i> genome is a critical step towards developing directed pest management strategies to reduce the spread of HLB throughout the citrus industry.
DOI: 10.5524/100995
title: Supporting data for "Ubiquitin Proteasome Pathway annotation in <i>Diaphorina citri</i> can reveal potential targets for RNAi based pest management"

description: Ubiquitination is an ATP-dependent process that targets proteins for degradation by the proteasome. In this study, we annotated 15 genes from the ubiquitin-proteasome pathway in the Asian citrus psyllid, <i>Diaphorina citri</i>. This psyllid vector has come to prominence in the last decade due to its role in the transmission of the devastating bacterial pathogen, <i>Candidatus</i> Liberibacter asiaticus (<i>C</i>Las). Infection of citrus crops by this pathogen causes Huanglongbing (HLB or citrus greening disease) and results in the eventual death of citrus trees. The identification and correct annotation of these genes in <i>D.citri</i> will be useful for functional genomic studies that aid in the development of RNAi-based management strategies aimed at reducing the spread of HLB. Investigating the effects of <i>C</i>Las infection on the expression of ubiquitin-proteasome pathway genes may provide new information regarding the role that these genes play in the acquisition and transmission of <i>C</i>Las by <i>D. citri.</i>
DOI: 10.5524/100996
title: Supporting data for "Annotation of glycolysis, gluconeogenesis, and trehaloneogenesis pathways provide insight into carbohydrate metabolism in the Asian citrus psyllid"

description: Citrus greening disease is caused by the pathogen <i>Candidatus Liberibacter asiaticus</i> and transmitted by the Asian citrus psyllid, <i>Diaphorina citri</i>. No curative treatment or significant prevention mechanism exists for this disease, which causes economic losses from reduced citrus production. A high-quality genome of <i>D. citri</i> is being manually annotated to provide accurate gene models to identify novel control targets and increase understanding of this pest. Here, we annotated 25 <i>D. citri</i> genes involved in glycolysis and gluconeogenesis, and seven in trehaloneogenesis. Comparative analysis showed that glycolysis genes in <i>D. citri</i> are highly conserved but copy numbers vary. Analysis of expression levels revealed upregulation of several enzymes in the glycolysis pathway in the thorax, consistent with the primary use of glucose by thoracic flight muscles. Manually annotating these core metabolic pathways provides accurate genomic foundation for developing gene-targeting therapeutics to control <i>D. citri</i>.
DOI: 10.5524/100997
title: Supporting data for "Annotation of Putative Circadian Rhythm-Associated Genes in <i>Diaphorina citri</i> (Hemiptera : Liviidae)"

description: The circadian rhythm is a process involving multiple genes that generates an internal molecular clock, allowing organisms to anticipate environmental conditions produced by the earths rotation on its axis. This report presents the results of the manual curation of twenty-seven genes likely associated with circadian rhythm in the genome of <i>Diaphorina citri</i>, the Asian citrus psyllid. This insect acts as the vector of the bacterial pathogen <i>Candidatus</i> Liberibacter asiaticus (CLas), the causal agent of citrus greening disease (Huanglongbing). This disease is the most severe detriment to citrus industries and has drastically decreased crop yields worldwide. Based on the genes identified in the psyllid genome, namely <i>cry1</i> and <i>cry2, D. citri</i> likely possesses a circadian model similar to that of the lepidopteran butterfly, <i>Danaus plexippus</i>. Manual annotation of these genes will allow future molecular therapeutics to be developed that can disrupt the psyllid biology.