cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/100708
title: Supporting data for "A novel k-FLBPCM method for detecting morphologically similar crops and weeds based on the combination of contour masks and Local Binary Pattern operators"

description: Weeds are a major cause of low agricultural productivity. Some weeds have morphological features similar to crops making them difficult to discriminate. This paper proposes a novel method using a combination of filtered-features extracted by combined Local Binary Pattern operators and features extracted by plant-leaf contour masks to improve the discrimination rate between broadleaf plants. Opening and closing morphological operators were applied to filter noise in plant images. The images at four stages of growth were collected using a testbed system. Mask-based Local Binary Pattern features were combined with filtered-features and a coefficient k. The classification of crops and weeds was achieved using support-vector-machine with radial basis function kernel. By investigating optimal parameters, this method reached a classification accuracy of 98.63% with four classes in the bccr-segset dataset published online in comparison with an accuracy of 91.85% attained by a previously reported method.
DOI: 10.5524/100712
title: Supporting data for "Canfam_GSD: De novo chromosome-length genome assembly of the German Shepherd Dog (Canis lupus familiaris) using a combination of long reads, optical mapping and Hi-C"

description: The German Shepherd Dog (GSD) is one of the most common breeds on earth and has been bred for its utility and intelligence. It is often first choice for police and military work, as well as protection, disability assistance and search-and-rescue. Yet, GSDs are well known to be afflicted with a range of genetic diseases that can interfere with their training. Such diseases are of particular concern when they occur later in life, and fully trained animals are not able to continue their duties. Here, we provide the draft genome sequence of a healthy German Shepherd female as a reference for future disease and evolutionary studies We generated this improved canid reference genome (CanFam_GSD) utilising a combination of Pacific Bioscience, Oxford Nanopore,, 10X Genomics, Bionano, and Hi-C technologies. The GSD assembly is approximately 80 times as contiguous as the current canid reference genome (20.9 Mb vs 0.267 Mb contig N50), containing far fewer gaps (306 vs 23,876) and fewer scaffolds (429 vs 3,310) than the current canid reference genome CanFam v3.1. Two chromosomes (4 and 35) are assembled into single scaffolds with no gaps. Benchmarking Universal Single-Copy Orthologs analyses of the genome assembly results show 93.0% of the conserved single-copy genes are complete in the GSD assembly compared to 92.2% for CanFam v3.1. Homology-based gene annotation increases this value to about 99%. Detailed examination of the evolutionary important pancreatic amylase region reveals there are most likely seven copies of the gene indicative of a duplication of four ancestral copies and the disruption of one copy. GSD genome assembly and annotation were produced with major improvement in completeness, continuity and quality over the existing canid reference. This resource will enable further research related to canine diseases, the evolutionary relationships of canids, and other aspects of canid biology.
DOI: 10.5524/100713
title: Supporting data for "Bioentity2vec: Attribute- and Behavior-driven Representation for Multi-type Relationship Prediction between Various Bioentities"

description: The explosive growth of genomic, chemical and pathological data provides new opportunities and challenges for humans to reexamine life activities in cells. However, there exist few computational models that aggregate various bioentities to comprehensively reveal the physical and functional landscape of biological system. Here, we construct a graph called Molecular Association Network (MAN) and a representation method called Bioentity2vec. Specifically, MAN is a heterogeneous attribute network consists of 18 kinds of edges (relationships) among 8 kinds of nodes (bioentities). Bioentity2vec is an algorithm that represents the nodes as vectors by integrating bioentity attribute such as RNA sequence and bioentity behavior that is the relationship between bioentities. Then, random forest classifier is applied to carry out the relationship prediction task. The proposed approach achieved promising performance on 18 relationships, with AUC of 0.9608 and AUPR of 0.9572. The results strongly prove that MAN is a network with rich topological and biological information and Bioentity2vec can adequately characterize bioentities. Generally, our method can achieve simultaneous prediction of both single-type and multi-type relationships, which bring beneficial inspiration to relevant scholars and expand the medical research paradigm.
DOI: 10.5287/bodleian:amnxrjyn8
title: Simulated bacterial genomes for evaluating SNP calling pipelines
DOI: 10.5524/100673
title: Supporting data for "Chromosomal-level genome assembly of Aldrichina grahami, a forensically important blow fly"

description: Blow flies (Diptera: Calliphoridae) are the most commonly found entomological evidence in the forensic investigation. <i>A. grahami</i> with some unique biological characteristics that distinguish it from other blow flies is a blow fly species of forensic importance. Its development rate, pattern and life cycle can provide valuable information for the estimation of the minimum postmortem interval (minPMI).<br>Herein we provide a chromosomal-level genome assembly of <i>A. grahami</i> that was generated by Pacific BioSciences (PacBio) sequencing platform and chromosome conformation capture (Hi-C) technology. A total of 50.15 Gb clean reads of <i>A. grahami</i> genome were generated. Programs FALCON and Wtdbg, as the common assembly tools for PacBio long reads, were utilized to construct the genome of <i>A. grahami</i> which resulted in an assembly of 600 Mb and 1604 contigs with N50 size of 1.93 Mb. We predicted 12823 protein-coding genes, 99.8% of that was functionally annotated based on de novo genome (SRA: PRJNA513084) and transcriptome (SRA: SRX5207346) of <i>A. grahami</i>. According to the co-analysis with 10 other insect species, the clustering and phylogenetic reconstruction of the gene families were performed. Using Hi-C sequencing, a chromosomal-level assembly of 6 chromosomes was generated with scaffold N50 of 104.7 Mb. Of these scaffolds, nearly 96.4% were anchored to the total <i>A. grahami</i> genome contig bases.<br>The present study provides a robust genome reference of the <i>A. grahami</i> which supplements vital genetic information for the nonhuman forensic genomics, and facilitates the future research of <i>A. grahami</i> and other necrophagous blow fly species used in forensic medicine.
DOI: 10.5524/100677
title: Supporting data for "Genome and population sequencing of a chromosome-level genome assembly of Chinese tapertail anchovy (<i>Coilia nasus</i>) provides novel insights into migratory adaptation"

description: Seasonal migration is one of the most spectacular events in nature; however, detailed mechanisms related to this interesting phenomenon have not been investigated in detail. Chinese tapertail anchovy, <i>Coilia nasus</i> , is a valuable migratory fish of high economic importance and special migratory dimorphism (with certain individuals as non-migratory residents). <br> In this study, an 870.0 Mb highquality genome was assembled by the combination of Illumina and PacBio sequencing. 812.1 Mb of scaffolds were linked to 24 chromosomes using a high-density genetic map from a family of 104 full siblings and their parents. In addition, population sequencing of 96 representative individuals from diverse areas along the putative migration path confirmed the involvement of 150 genes in migratory adaption. Based on integrative genomic and transcriptomic analyses, we determined that three Ca 2+ - related pathways are critical for the promotion of migratory adaption. A large number of molecular markers were also identified, which distinguished migratory individuals and non-migratory freshwater residents. <br>We assembled a chromosome-level genome for the Chinese tapertail anchovy. The genome provided a valuable genetic resource for understanding migratory adaption and population genetics, and will benefit the aquaculture and management of this economically important fish.
DOI: 10.5524/100684
title: Supporting data for "Prognostic Model for Multiple Myeloma Progression Integrating Gene Expression and Clinical Features"

description: Multiple Myeloma (MM) is a hematological cancer caused by abnormal accumulation of monoclonal plasma cells in bone marrow. With the increase in treatment options, risk-adapted therapy is becoming more and more important. Survival analysis is commonly applied to study progression or other events of interest and stratify the risk of patients. In this study, we present the current state-of-the-art model for MM prognosis and the molecular biomarker set for stratification: the winning algorithm in the 2017 Multiple Myeloma DREAM Challenge, Sub-Challenge 3. Specifically, we built a non-parametric complete hazard ranking model to map the right-censored data into a linear space, where commonplace machine learning techniques, such as Gaussian process regression and random forests, can play their roles. Our model integrated both the gene expression profile and clinical features to predict the progression of MM. Compared with conventional models, such as Cox model and Random Survival Forests, our model achieved higher accuracy in 3 within-cohort predictions. In addition, it showed robust predictive power in cross-cohort validations. Key molecular signatures related to MM progression were identified from our model, which may function as the core determinants of MM progression and provide important guidance value for future research and clinical practice. Functional enrichment analysis and mammalian gene-gene interaction network revealed crucial biological processes and pathways involved in MM progression. We present the current state-of-the-art prognostic model for Multiple Myeloma integrating gene expression and clinical features validated in independent test set.
DOI: 10.5524/100694
title: Supporting data for "Genomic diversity affects the accuracy of bacterial SNP calling pipelines"

description: Accurately identifying SNPs from bacterial sequencing data is an essential requirement for using genomics to track transmission and predict important phenotypes such as antimicrobial resistance. However, most previous performance evaluations of SNP calling have been restricted to eukaryotic (human) data. Additionally, bacterial SNP calling requires choosing an appropriate reference genome to align reads to, which, together with the bioinformatic pipeline, affects the accuracy and completeness of a set of SNP calls obtained.<br>This study evaluates the performance of 209 SNP calling pipelines using a combination of simulated data from 254 strains of 10 clinically common bacteria and real data from environmentally-sourced and genomically diverse isolates within the genera Citrobacter, Enterobacter, Escherichia and Klebsiella. <br>We evaluated the performance of 209 SNP calling pipelines, aligning reads to genomes of the same or a divergent strain. Irrespective of pipeline, a principal determinant of reliable SNP calling was reference genome selection. Across multiple taxa, there was a strong inverse relationship between pipeline sensitivity and precision, and the Mash distance (a proxy for average nucleotide divergence) between reads and reference genome. The effect was especially pronounced for diverse, recombinogenic, bacteria such as Escherichia coli, but less dominant for clonal species such as Mycobacterium tuberculosis. <br>The accuracy of SNP calling for a given species is compromised by increasing intra-species diversity. When reads were aligned to the same genome from which they were sequenced, among the highest performing pipelines was Novoalign/GATK. By contrast, when reads were aligned to particularly divergent genomes, the highest-performing pipelines often employed the aligners NextGenMap or SMALT, and/or the variant callers LoFreq, mpileup or Strelka.
DOI: 10.5524/100695
title: Supporting data for "Evaluating the Genome and Resistome of Extensively Drug-Resistant Klebsiella pneumoniae using Native DNA and RNA Nanopore Sequencing"

description: Klebsiella pneumoniae frequently harbours multidrug resistance and current diagnostics struggle to rapidly identify appropriate antibiotics to treat these bacterial infections. The MinION device can sequence native DNA and RNA in real-time, providing an opportunity to compare the utility of DNA and RNA for prediction of antibiotic susceptibility. However, the effectiveness of bacterial direct RNA sequencing and base-calling has not previously been investigated. This study interrogated the genome and transcriptome of four extensively drug-resistant (XDR) K. pneumoniae clinical isolates, however, further antimicrobial susceptibility testing identified three isolates as pandrug-resistant (PDR). The majority of acquired resistance (75%) resided on plasmids including several megaplasmids (100 kbp). DNA sequencing detected most resistance genes (70%) within 2 hours of sequencing. Neural-network based base-calling of direct RNA achieved up to 86% identity rate, although 23% of reads could be aligned. Direct RNA sequencing (with approximately 6 times slower pore translocation) was able to identify (within 10 hours) 35% of resistance genes, including those associated with resistance to aminoglycosides, -lactams, trimethoprim and sulphonamide and also quinolones, rifampicin, fosfomycin and phenicol in some isolates. Direct RNA sequencing also identified the presence of operons containing up to 3 resistance genes. Polymyxin-resistant isolates showed a heightened transcription of phoPQ (2-fold) and the pmrHFIJKLM operon (8-fold). Expression levels estimated from direct RNA sequencing displayed strong correlation (Pearson: 0.86) compared to qRT-PCR across eleven resistance genes. Overall, MinION sequencing rapidly detected the XDR/ PDR K. pneumoniae resistome and direct RNA sequencing provided accurate estimation of expression levels of these genes.
DOI: 10.5524/100716
title: Supporting data for "Multi-omics Visualization Platform: An extensible Galaxy plug-in for multi-omics data visualization and exploration"

description: Proteogenomics integrates genomics, transcriptomics and mass spectrometry (MS)- based proteomics data to identify novel protein sequences arising from gene and transcript sequence variants. Proteogenomic data analysis requires integration of disparate omic software tools, as well as customized tools to view and interpret results. The flexible Galaxy platform has proven valuable for proteogenomic data analysis. Here, we describe a novel Multi-omics Visualization Platform (MVP) for organizing, visualizing and exploring proteogenomic results, adding a critically needed tool for data exploration and interpretation.<br>MVP is built as an HTML Galaxy plugin, primarily based on Javascript. Via the Galaxy API, MVP uses SQlite databases as input -- a custom datatype (mzSQlite) containing MS-based peptide identification information, a variant annotation table, and a coding sequence table. Users can interactively filter identified peptides based on sequence and data quality metrics, view annotated peptide MS data, visualize protein-level information, along with genomic coordinates. Peptides that pass the user-defined thresholds can be sent back to Galaxy via the API for further analysis; processed data and visualizations can also be saved and shared. MVP leverages the Integrated Genomics Viewer JavaScript (IGVjs) framework, enabling interactive visualization of peptides and corresponding transcript and genomic coding information within the MVP interface.<br>MVP provides a powerful, extensible platform for automated, interactive visualization of proteogenomics results within the Galaxy environment, adding a unique and critically needed tool for empowering exploration and interpretation of results. The platform is extensible, providing a basis for further development of new functionalities for proteogenomic data visualization.
DOI: 10.5524/100670
title: Supporting data for "Refgenie: a reference genome resource manager"

description: Reference genome assemblies are essential for high-throughput sequencing analysis projects. Typically, genome assemblies are stored on disk alongside related resources; for example, many sequence aligners require the assembly to be indexed. The resulting indexes are broadly applicable for downstream analysis, so it makes sense to share them. However, there is no simple tool to do this. To this end, we introduce refgenie, a reference genome assembly asset manager. Refgenie makes it easier to organize, retrieve, and share genome analysis resources. In addition to genome indexes, refgenie can manage any files related to reference genomes, including sequences and annotation files. Refgenie includes a command-line interface and a server application that provides a RESTful API, so it is useful for both tool development and analysis.
DOI: 10.5524/100671
title: Supporting data for "Benchmark of lncRNA Quantification for RNA-Seq of Cancer Samples"

description: Long non-coding RNAs (lncRNAs) are emerging as important regulators of various biological processes. While many studies have exploited public resources such as RNA-Seq data in The Cancer Genome Atlas (TCGA) to study lncRNAs in cancer, it is crucial to choose the optimal method for accurate expression quantification. 

In this study, we compared the performance of pseudoalignment methods Kallisto and Salmon, alignment-based transcript quantification method RSEM, and alignment-based gene quantification methods HTSeq and featureCounts, in combination with read aligners STAR, Subread, and HISAT2, in lncRNA quantification, by applying them to both unstranded and stranded RNA-Seq datasets. Full transcriptome annotation, including protein-coding and noncoding RNAs, greatly improves the specificity of lncRNA expression quantification. Pseudoalignment methods and RSEM outperform HTSeq and featureCounts for lncRNA quantification at both sample- and gene-level comparison, regardless of RNA-Seq protocol type, choice of aligners and transcriptome annotation. Pseudoalignment methods and RSEM detect more lncRNAs and correlate highly with simulated ground truth. On the contrary, HTSeq and featureCounts often underestimate lncRNA expression. Antisense lncRNAs are poorly quantified by alignment-based gene quantification methods, which can be improved using stranded protocols and pseudoalignment methods. 

Considering the consistency with ground truth and computational resources, pseudoalignment methods Kallisto or Salmon in combination with full transcriptome annotation is our recommended strategy for RNA-Seq analysis for lncRNAs.
DOI: 10.5524/100674
title: <b>RETRACTION:</b>Supporting data for "Dissection of soybean populations according to selection signatures based on whole-genome sequences"

description: <b>In December 2019, GigaScience published the article Dissection of soybean populations according to selection signatures based on whole-genome sequences, by Jae-Yoon Kim and colleagues: DOI:10.1093/gigascience/giz151. In 2020, the editors received credible information about attribution problems with the source of the data in the article and subsequently alerted the readers with a statement of concern: DOI:10.1093/gigascience/giaa040. A full institutional investigation has now been completed, which has concluded that research misconduct was carried out. As a result, this article has now been retracted:DOI:10.1093/gigascience/giab038 by the editors and authors. <br>GigaDB has deleted the data associated with the original publication. Correctly attributed and labeled data is now available in NCBI and can be accessed from PRJNA555366.<br>All files have been permanently deleted from GigaDB servers as of 13 May 2021.</b>
DOI: 10.5524/100676
title: Supporting data for "A draft genome sequence of the elusive giant squid, Architeuthis dux"

description: The giant squid (Architeuthis dux; Steenstrup, 1857) is an enigmatic giant mollusk with a circumglobal distribution in the deep ocean, except in the high Arctic and Antarctic waters. The elusiveness of the species makes it difficult to study. Thus, having a genome assembled for this deep-sea dwelling species will allow unlocking several pending evolutionary questions. We present a draft genome assembly that includes 200 Gb of Illumina reads, 4 Gb of Moleculo synthetic long-reads and 108 Gb of Chicago libraries, with a final size matching the estimated genome size of 2.7 Gb, and a scaffold N50 of 4.8 Mb. We also present an alternative assembly including 27 Gb raw reads generated using the Pacific Biosciences platform. In addition, we sequenced the proteome of the same individual and RNA from three different tissue types from three other species of squid species (Onychoteuthis banksii, Dosidicus gigas, and Sthenoteuthis oualaniensis) to assist genome annotation. We annotated 33,406 protein coding genes supported by evidence and the genome completeness estimated by BUSCO reached 92%. Repetitive regions cover 49.17% of the genome. This annotated draft genome of A. dux provides a critical resource to investigate the unique traits of this species, including its gigantism and key adaptations to deep-sea environments.
DOI: 10.5524/100678
title: Supporting data for "Chromosome-level genome assembly reveals the unique genome evolution of swimming crab (Portunus trituberculatus)"

description: The swimming crab, <i>Portunus trituberculatus</i>, is an important commercial species in China and is widely distributed in the coastal waters of Asia-Pacific countries. Despite increasing interest in swimming crab research, a high quality chromosome-level genome is still missing. <br>Here, we assembled the first chromosome-level reference genome of <i>P. trituberculatus</i> by combining the short reads, Nanopore long reads, and Hi-C data. The genome assembly size was 1.00 Gb with a contig N50 length of 4.12 Mb. In addition, BUSCO assessment indicated that 94.7% of core eukaryotic genes were present in the genome assembly. Approximately 54.52% of the genome was identified as repetitive sequences, with a total of 16,796 annotated protein-coding genes. In addition, we anchored contigs into chromosomes and identified 50 chromosomes with a N50 length of 21.80 Mb by Hi-C technology. <br>We anticipate that this chromosome-level assembly of the <i>P. trituberculatus</i> genome will not only promote study of basic development and evolution but also provide important resources for swimming crab reproduction.