cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/102376
title: Supporting data for "The Regulatory Mendelian Mutation score for GRCh38"

description: Genome sequencing efforts for individuals with rare Mendelian disease have increased the research focus on the non-coding genome and the clinical need for methods that prioritize potentially disease causal non-coding variants. Some tools for assessment of variant pathogenicity as well as annotations are not available for the current human genome build (GRCh38), for which the adoption in databases, software and pipelines was slow.<br>Here, we present an updated version of the Regulatory Mendelian Mutation (ReMM) score, re-trained on features and variants derived from the GRCh38 genome build. Like its GRCh37 version, it achieves good performance on its highly imbalanced data. To improve accessibility and provide users with a toolbox to score their variant files and lookup scores in the genome, we developed a website and API for easy score lookup.<br>Scores of the GRCh38 genome build are highly correlated to the prior release with a performance increase due to the better coverage of features. For prioritization of non-coding mutations in imbalanced datasets, the ReMM score performed much better than other variation scores. Pre-scored whole genome files of GRCh37 and GRCh38 genome builds are available on Zenodo. The website, UCSC genome browser tracks, and an API are available at https://remm.bihealth.org.
DOI: 10.5524/102377
title: Supporting data for "On the benefits of self-taught learning for brain decoding"

description: We study the benefits of using a large public neuroimaging database composed of fMRI statistic maps, in a self-taught learning framework, for improving brain decoding on new tasks. First, we leverage the NeuroVault database to train, on a selection of relevant statistic maps, a convolutional autoencoder to reconstruct these maps. Then, we use this trained encoder to initialize a supervised convolutional neural network to classify tasks or cognitive processes of unseen statistic maps from large collections of the NeuroVault database. We show that such a self-taught learning process always improves the performance of the classifiers but the magnitude of the benefits strongly depends on the number of samples available both for pre-training and finetuning the models and on the complexity of the targeted downstream task.
DOI: 10.5524/102379
title: Supporting data for "TF-Prioritizer: a java pipeline to prioritize condition-specific transcription factors"

description: Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., ChIP-seq, ATAC-seq, or DNase-seq) and RNA-seq data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results.<br>We developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multi-modal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE data sets for cell lines K562 and MCF-7, including twelve histone modification ChIP-seq as well as ATAC-seq and DNase-seq datasets, where we observe and discuss assay-specific differences.<br>TF-Prioritizer accepts ATAC-seq, DNase-seq, or ChIP-seq and RNA-seq data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
DOI: 10.5524/102380
title: Supporting data for "Strategies and Techniques for Quality Control and Semantic Enrichment with Multimodal Data: A Case Study in Colorectal Cancer with eHDPrep"

description: Integration of data from multiple domains can greatly enhance the quality and applicability of knowledge generated in analysis workflows. However, working with health data is challenging, requiring careful preparation in order to support meaningful interpretation and robust results. Ontologies encapsulate relationships between variables that can enrich the semantic content of health datasets to enhance interpretability and inform downstream analyses.<br>We developed an R package for electronic Health Data Preparation eHDPrep, demonstrated upon a multi-modal colorectal cancer dataset (n=661 patients, n=155 variables; Colo-661), a further demonstrator is taken from The Cancer Genome Atlas (n=461 patients, n=94 variables; TCGA-COAD). eHDPrep offers user-friendly methods for quality control, including internal consistency checking and redundancy removal with information-theoretic variable merging. Semantic enrichment functionality is provided, enabling generation of new informative meta-variables according to ontological common ancestry between variables, demonstrated with SNOMED CT and the Gene Ontology in the current study. eHDPrep also facilitates numerical encoding, variable extraction from free-text, completeness analysis and user review of modifications to the dataset.<br>eHDPrep provides effective tools to assess and enhance data quality, laying the foundation for robust performance and interpretability in downstream analyses. Application to multi-modal colorectal cancer datasets resulted in improved data quality, structuring, and robust encoding, as well as enhanced semantic information. We make eHDPrep available as an R package from CRAN and GitHub.
DOI: 10.5524/102387
title: Supporting data for "Deep neural networks with knockoff features identify nonlinear causal relations and estimate effect sizes in complex biological systems"

description: Learning the causal structure helps identify risk factors, disease mechanisms, and candidate therapeutics for complex diseases. However, although complex biological systems are characterized by non-linear associations, existing bioinformatic methods of causal inference cannot identify the nonlinear relationships and estimate their effect size. <br>To overcome these limitations, we developed the first computational method that learns both linear and nonlinear causal relations and estimates the effect size using a deep-neural network approach coupled with the knockoff framework, named causal Directed Acyclic Graphs using deep-learning VAriable SElection (DAG-deepVASE). Using simulation data of diverse scenarios and identifying known and novel causal relations in molecular and clinical data of various diseases, we demonstrated that DAG-deepVASE consistently outperforms existing methods in identifying true and known causal relations. In the analyses, we also illustrate how identifying nonlinear causal relations and estimating their effect size help understand the complex disease pathobiology, which is not possible using other methods. <br>With these advantages, the application of DAG-deepVASE can help identify driver genes and therapeutic agents in biomedical studies and clinical trials.
DOI: 10.6084/m9.figshare.21941213.v3
title: protocols_hms_to_unraveledTFs.tsv

description: Guide which TF can be found in which HM or protocol (ChIP-seq, ATAC-seq, DNAse-seq)
DOI: 10.5281/zenodo.6091361
title: COVID Image segmentation datasets and trained model

description: COVID CT scan datasets for segmentation and trained model for prediction created by training uNet. The referred paper is: https://www.sciencedirect.com/science/article/pii/S2666990021000069 Origin of datasets: https://medicalsegmentation.com/covid19/
DOI: 10.5524/102339
title: Supporting data for "Chromosome-level genome assembly of goose provides insight into the adaptation and growth of local goose breeds"

description: Anatidae contains numerous waterfowl species with great economic value, but the genetic diversity basis remains insufficiently investigated. Here, we report a chromosome-level genome assembly of Lion-head goose <i>Anser cygnoides</i>, a native breed in South China, through the combination of PacBio, Bionano and Hi-C technologies. <br>The assembly had a total genome size of 1.19 Gb, consisting of 1,859 contigs with an N50 length of 20.59 Mb, generating 40 pseudochromosomes, representing 97.27% of the assembled genome, and identifying 21,208 protein-coding genes. Comparative genomic analysis revealed that geese and ducks diverged approximately 28.42 million years ago, and geese have undergone massive gene family expansion and contraction. To identify genetic markers associated with body weight in different geese breeds including Wuzong goose, Huangzong goose, Magang goose and Lion-head goose, a genome-wide association study was performed, yielding an average of 1,520.6 Mb of raw data with detecting 44,858 SNPs. GWAS showed that six SNPs were significantly associated with body weight and 25 were potentially associated. The significantly associated SNPs were annotated as LDLRAD4, GPR180, OR, enriching in growth factor receptors regulation pathways. <br>We present the first chromosome-level assembly of the Lion-head goose genome, which will expand the genomic resources of the Anatidae family, providing a basis for adaptation and evolution. Candidate genes significantly associated with different goose breeds may serve to understand the underlying mechanisms of weight differences.
DOI: 10.5524/102341
title: Supporting data for "Chromosome-level genome and the identification of sex chromosomes in <i>Uloborus diversus</i>"

description: The orb-web is a remarkable example of animal architecture that is observed in families of spiders that diverged over 200 million years ago. While several genomes exist for Araneid orb-weavers, none exist for other orb-weaving families, hampering efforts to investigate the genetic basis of this complex behavior. Here we present a chromosome-level genome assembly for the cribellate orb-weaving spider <i>Uloborus diversus</i>. The assembly reinforces evidence of an ancient arachnid genome duplication and identifies complete open reading frames for every class of spidroin gene, which encode the proteins that are the key structural components of spider silks. We identified the two X chromosomes for <i>U<em>. </em>diversus</i> and identify candidate sex-determining genes. This chromosome-level assembly will be a valuable resource for evolutionary research into the origins of orb-weaving, spidroin evolution, chromosomal rearrangement, and chromosomal sex-determination in spiders.
DOI: 10.5524/102343
title: Supporting data for "Parvovirus dark matter in the cloaca of wild birds."

description: With the development of viral metagenomics and next-generation sequencing technology, more and more novel parvoviruses have been identified in recent years. Including even entirely new lineages. The <i>Parvoviridae</i> family includes a different group of viruses that can infect a wide variety of animals. In this study, systematic analysis was performed to identify the dark matter (datasets that cannot be easily attributed to known viruses) of parvoviruses and to explore their genetic diversity from wild birds cloacal swab samples. We have tentatively defined this parvovirus dark matter as a highly divergent lineage in the <i>Parvoviridae </i> family. All parvoviruses showed several characteristics, including two major protein-coding genes and similar genome lengths. Moreover, we observed that the novel parvo-like viruses share similar genome organizations to most viruses in <i>Parvoviridae</i> but could not clustered with the established subfamilies in phylogenetic analysis. We also found some new members associated with the <i>Bidnaviridae</i> family, which may be derived from parvovirus. This suggests that systematic analysis of domestic and wild animal samples is necessary to explore the genetic diversity of parvoviruses and to mine for more of this potential dark matter.
DOI: 10.5524/102348
title: Supporting data for "Nanopore-based enrichment of antimicrobial resistance genes - a case-based study."

description: Rapid screening of hospital admissions to detect asymptomatic carriers of resistant bacteria can prevent pathogen outbreaks. However, the resulting isolates rarely have their genome sequenced due to cost constraints and long turn-around times to get and process the data, limiting their usefulness to the practitioner. Here we use real-time, on-device target enrichment ("adaptive") sequencing as a highly multiplexed assay covering 1,147 antimicrobial resistance genes. We compare its utility against standard and metagenomic sequencing, focusing on an isolate of <i>Raoultella ornithinolytica</i> harbouring three carbapenemases (<i>NDM , KPC , VIM</i>). Based on this experimental data, we then model the influence of several variables on the enrichment results and predict a large effect of nucleotide identity (higher is better) and read length (shorter is better). Lastly, we show how all relevant resistance genes are detected using adaptive sequencing on a miniature ("Flongle") flow cell, motivating its use in a clinical setting to monitor similar cases and their surroundings.
DOI: 10.5524/102349
title: Supporting data for "Molecular mechanisms underlying hematophagia revealed by comparative analyses of leech genomes"

description: Leeches have been used in traditional Chinese medicine since pre-historic times to treat a spectrum of ailments, but very little is known about their physiological, genetic, and evolutionary characteristics.<br> We sequenced and assembled chromosome-level genomes of three leech species (bloodsucking <i>Hirudo nipponia</i> and <i>Hirudinaria manillensis</i> and non-bloodsucking <i>Whitmania pigra</i>). The dynamic population histories and genome-wide expression patterns of the two bloodsucking leech species were found to be similar. A combined analysis of the genomic and transcriptional data revealed that the bloodsucking leeches have a presumably enhanced auditory sense for prey location in relatively deep fresh water. The copy number of genes related to anticoagulation, analgesia, and anti-inflammation increased in the bloodsucking leeches, and their gene expressions responded dynamically to the bloodsucking process. Furthermore, the expanded <i>FBN1</i> gene family may help in rapid body swelling of leeches after bloodsucking, and the expanded <i>GLB3</i> gene family may be associated with long-term storage of prey blood in a leechs body.<br> The high-quality reference genomes and comprehensive datasets obtained in this study may facilitate innovations in the artificial culture and strain optimization of leeches.
DOI: 10.5524/102352
title: Supporting data for "ViReMa: A Virus Recombination Mapper of Next-Generation Sequencing data characterizes diverse recombinant viral nucleic acids"

description: Genetic recombination is a tremendous source of intra-host diversity in viruses and is critical for their ability to rapidly adapt to new environments or fitness challenges. While viruses are routinely characterized using high-throughput sequencing techniques, characterizing the genetic products of recombination in next-generation sequencing data remains a challenge. Viral recombination events can be highly diverse and variable in nature, including simple duplications and deletions, or more complex events such as copy/snap-back recombination, inter-virus or inter-segment recombination and insertions of host nucleic acids. Due to the variable mechanisms driving virus recombination and the different selection pressures acting on the progeny, recombination junctions rarely adhere to simple canonical sites or sequences. Furthermore, numerous different events may be present simultaneously in a viral population, yielding a complex mutational landscape. We have previously developed an algorithm called <i>ViReMa</i> (Virus Recombination Mapper) that bootstraps the <i>bowtie<em></em></i> short-read aligner to capture and annotate a wide-range of recombinant species found within virus populations. Here, we have updated <i>ViReMa</i> to provide an error-density function designed to accurately detect recombination events in the longer reads now routinely generated by the Illumina platforms and provide output reports for multiple types of recombinant species using standardized formats. We demonstrate the utility and flexibility of <i>ViReMa</i> in different settings to report deletion events in simulated data from Flock House virus, copy-back RNA species in Sendai viruses, short duplication events in HIV, and virus to host recombination in an archaeal DNA virus.
DOI: 10.5524/102353
title: Supporting data for "Improvements to the Gulf Pipefish <i>Syngnathus scovelli</i> Genome"

description: The Gulf pipefish <i>Syngnathus scovelli</i> has emerged as an important species in the study of sexual selection, development, and physiology, among other topics. The fish family Syngnathidae, which includes pipefishes, seahorses and seadragons, has become an increasingly attractive target for comparative research in ecological and evolutionary genomics. These endeavors depend on having a high-quality genome assembly and annotation. However, the first version of the <i>S. scovelli</i> genome assembly was generated by short-read sequencing and annotated using a small set of RNA-sequence data, resulting in limited contiguity and a relatively poor annotation. Here, we present an improved genome assembly and an enhanced annotation, resulting in a new official gene set for <i>S. scovelli</i>. By using PacBio long-read high-fidelity (Hi-Fi) sequences and a proximity ligation (Hi-C) library, we fill small gaps and join the contigs to obtain 22 chromosome-level scaffolds. Compared to the previously published genome, the gaps in our novel genome assembly are smaller, the N75 is much larger (13.3 Mbp), and this new genome is around 95% BUSCO complete. The precision of the gene models in the NCBIs eukaryotic annotation pipeline was enhanced by using a large body of RNA-Seq reads from different tissue types, leading to the discovery of 29,099 genes, of which 3,298 were non-coding RNA sequences. This new genome assembly and the annotation are tagged as a RefSeq genome by NCBI and thus provide substantially enhanced genomic resources for future research involving <i>S. scovelli</i>.
DOI: 10.5524/102361
title: Supporting data for "Resequencing of a Pekin duck breeding population provides insights into the genomic response to short-term artificial selection"

description: Short-term, intense artificial selection drives fast phenotypic changes in domestic animals and leaves imprints on their genomes. However, the genetic basis of this selection response is poorly understood. Here, we employed the Pekin duck Z2 pure line, in which the breast muscle weight was increased nearly three fold after ten generations of breeding. We <i>de-novo</i> assembled a high-quality reference genome of a female Pekin duck of this line (GCA_003850225.1) and identified 8.60 million genetic variants in 119 individuals among 10 generations of the breeding population. <br>We identified 53 selected regions between the first and tenth generations, and 93.8% of the identified variations were enriched in regulatory and noncoding regions. Integrating the selection signatures and genome-wide association approach, we found that two regions covering 0.36 Mb containing <i>UTP25</i> and <i>FBRSL1</i> were most likely to contribute to breast muscle weight improvement. The major allele frequencies of these two loci increased gradually with each generation following the same trend. Additionally, we found that a copy number variation region containing the entire <i>EXOC4</i> gene could explain 1.9% of the variance in breast muscle weight, indicating that the nervous system may play a role in economic trait improvement. <br>Our study not only provides insights into genomic dynamics under intense artificial selection but also provides resources for genomics-enabled improvements in duck breeding.
DOI: 10.5524/102362
title: Supporting data for "Genome assembly of three Amazonian Morpho butterfly species reveals Z-chromosome rearrangements between closely-related species living in sympatry"

description: The genomic processes enabling speciation and species coexistence in sympatry are still largely unknown. Here we describe the whole genome sequence of three closely-related species from the butterfly genus <i>Morpho : Morpho achilles</i> (Linnaeus, 1758), <i>M. helenor</i> (Cramer, 1776) and <i>M. deidamia</i> (Hübner, 1819). These large blue butterflies are emblematic species of the Amazonian rainforest. They live in sympatry in a wide range of their geographical distribution and display parallel diversification of dorsal wing colour pattern, suggesting local mimicry. By sequencing, assembling and annotating their genomes, we aim at uncovering pre-zygotic barriers preventing gene flow between these sympatric species. We found a genome size of 480 Mb for the three species and a chromosomal number ranging from 2n = 54 for <i>M. deidamia</i> to 2n = 56 for <i>M. achilles</i> and <i>M. helenor</i>. We also detected inversions on the sex chromosome Z that were differentially fixed between species, suggesting that chromosomal rearrangements may contribute to their reproductive isolation. The annotation of their genomes allowed us to recover in each species at least 12,000 protein-coding genes and to discover duplications of genes potentially involved in pre-zygotic isolation like genes controlling colour discrimination (<i>L-opsin</i>). Altogether, the assembly and the annotation of these three new reference genomes open new research avenues into the genomic architecture of speciation and reinforcement in sympatry, establishing <i>Morpho</i> butterflies as a new eco-evolutionary model.
DOI: 10.5524/102363
title: Genomic data of non-bloodsucking leech, <i>Whitmania pigra</i>

description: <i>Whitmania pigra</i> is a widely distributed non-bloodsucking macrophagous freshwater leech found in East Asia, with an annual consumption of nearly 1,000 tons of dry bodies for curing blood stasis syndrome.<br> Here we present the genome, which has an estimated genome size of 181.4Mb, scaffold N50 of 16.2Mb, contig N50 of 50.4Mb and 18,540 genes. This dataset includes the following data: repetitive sequences, gene and functional annotations, annotation of ncRNAs, prediction of secreted proteins, divergence time & transcriptome analysis.