37 research outputs found
chloroExtractor: extraction and assembly of the chloroplast genome from whole genome shotgun data
The chloroExtractor is a perl based program which provides a pipeline for DNA extraction of chloroplast DNA from whole genome plant data.The authors MJA and SP contributed equally to this work.
MJA was supported by a grant of the German Excellence Initiative to the Graduate School of Life Sciences, University of WĂŒrzburg
Open Science Principles for Accelerating Trait-Based Science Across the Tree of Life
Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principlesâopen data, open source and open methodsâis transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges
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Open Science principles for accelerating trait-based science across the Tree of Life.
Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges
MyoPS A Benchmark of Myocardial Pathology Segmentation Combining Three-Sequence Cardiac Magnetic Resonance Images
Assessment of myocardial viability is essential in diagnosis and treatment
management of patients suffering from myocardial infarction, and classification
of pathology on myocardium is the key to this assessment. This work defines a
new task of medical image analysis, i.e., to perform myocardial pathology
segmentation (MyoPS) combining three-sequence cardiac magnetic resonance (CMR)
images, which was first proposed in the MyoPS challenge, in conjunction with
MICCAI 2020. The challenge provided 45 paired and pre-aligned CMR images,
allowing algorithms to combine the complementary information from the three CMR
sequences for pathology segmentation. In this article, we provide details of
the challenge, survey the works from fifteen participants and interpret their
methods according to five aspects, i.e., preprocessing, data augmentation,
learning strategy, model architecture and post-processing. In addition, we
analyze the results with respect to different factors, in order to examine the
key obstacles and explore potential of solutions, as well as to provide a
benchmark for future research. We conclude that while promising results have
been reported, the research is still in the early stage, and more in-depth
exploration is needed before a successful application to the clinics. Note that
MyoPS data and evaluation tool continue to be publicly available upon
registration via its homepage
(www.sdspeople.fudan.edu.cn/zhuangxiahai/0/myops20/)
molbiodiv/biom-conversion-server: Version 1.0.4
Switch from bower to yarn
Update dependencies
Update of biojs-io-biom to version 1.0.
AliTV -interactive visualization of whole genome comparisons
ABSTRACT Whole genome alignments and comparative analysis are key methods in the quest of unraveling the dynamics of genome evolution. Interactive visualization and exploration of the generated alignments, annotations, and phylogenetic data are important steps in the interpretation of the initial results. Limitations of existing software inspired us to develop our new tool AliTV, which provides interactive visualization of whole genome alignments. AliTV reads multiple whole genome alignments or automatically generates alignments from the provided data. Optional feature annotations and phylogenetic information are supported. The user-friendly, web-browser based and highly customizable interface allows rapid exploration and manipulation of the visualized data as well as the export of publication-ready high-quality figures. AliTV is freely available at https://github.com/AliTVTeam/AliTV
AliTVâinteractive visualization of whole genome comparisons
Whole genome alignments and comparative analysis are key methods in the quest of unraveling the dynamics of genome evolution. Interactive visualization and exploration of the generated alignments, annotations, and phylogenetic data are important steps in the interpretation of the initial results. Limitations of existing software inspired us to develop our new tool AliTV, which provides interactive visualization of whole genome alignments. AliTV reads multiple whole genome alignments or automatically generates alignments from the provided data. Optional feature annotations and phylo- genetic information are supported. The user-friendly, web-browser based and highly customizable interface allows rapid exploration and manipulation of the visualized data as well as the export of publication-ready high-quality figures. AliTV is freely available at https://github.com/AliTVTeam/AliTV
Increased efficiency in identifying mixed pollen samples by meta-barcoding with a dual-indexing approach
Background
Meta-barcoding of mixed pollen samples constitutes a suitable alternative to conventional pollen identification via light microscopy. Current approaches however have limitations in practicability due to low sample throughput and/or inefficient processing methods, e.g. separate steps for amplification and sample indexing.
Results
We thus developed a new primer-adapter design for high throughput sequencing with the Illumina technology that remedies these issues. It uses a dual-indexing strategy, where sample-specific combinations of forward and reverse identifiers attached to the barcode marker allow high sample throughput with a single sequencing run. It does not require further adapter ligation steps after amplification. We applied this protocol to 384 pollen samples collected by solitary bees and sequenced all samples together on a single Illumina MiSeq v2 flow cell. According to rarefaction curves, 2,000â3,000 high quality reads per sample were sufficient to assess the complete diversity of 95% of the samples. We were able to detect 650 different plant taxa in total, of which 95% were classified at the species level. Together with the laboratory protocol, we also present an update of the reference database used by the classifier software, which increases the total number of covered global plant species included in the database from 37,403 to 72,325 (93% increase).
Conclusions
This study thus offers improvements for the laboratory and bioinformatical workflow to existing approaches regarding data quantity and quality as well as processing effort and cost-effectiveness. Although only tested for pollen samples, it is furthermore applicable to other research questions requiring plant identification in mixed and challenging samples