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Airway obstruction is fatal but common among burn patients in the early period after inhalation injury, during which most tracheotomies are performed within 48 h post-injury. Inflammation is common in laryngoscopy; however, the re...
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Airway obstruction is fatal but common among burn patients in the early period after inhalation injury, during which most tracheotomies are performed within 48 h post-injury. Inflammation is common in laryngoscopy; however, the related gene expression has rarely been studied. In this study, we obtained the data of healthy control and patient samples collected within 8-48 hours post-injury from the Gene Expression Omnibus database and classified them into 10 inhalation-injury patients, 6 burn-only, and 10 healthy controls. Differential gene expression was identified between the patient groups; however, principal component analysis and cluster analysis indicated a similarity between groups. Furthermore, enrichment analysis, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analyses showed no significant differences in immune regulation and cell adjustment between the patient groups; but differences were shown when comparing either patient group to the healthy control group, including prominent regulation in inflammatory cells, infection, and cell adjustment. Thus, the gene expression in inhalation injury and burn-only patients does not significantly differ in the early period after injury, especially in inflammation, indicating the absence of specific diagnostic markers or anti-inflammatory treatment in inhalation injury patients, with the potential to identify more subtle differences. Further research is warranted.
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Motivation: Testing for pathway enrichment is an important aspect in the analysis of untargeted metabolomics data. Due to the unique characteristics of untargeted metabolomics data, some key issues have not been fully addressed in...
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Motivation: Testing for pathway enrichment is an important aspect in the analysis of untargeted metabolomics data. Due to the unique characteristics of untargeted metabolomics data, some key issues have not been fully addressed in existing pathway testing algorithms: (i) matching uncertainty between data features and metabolites; (ii) lacking of method to analyze positive mode and negative mode liquid chromatography-mass spectrometry (LC/MS) data simultaneously on the same set of subjects; (iii) the incompleteness of pathways in individual software packages. Results: We developed an innovative R/Bioconductor package: metabolic pathway testing with positive and negative mode data (metapone), which can perform two novel statistical tests that take matching uncertainty into consideration-(i) a weighted gene set enrichment analysis-type test and (ii) a permutation-based weighted hypergeometric test. The package is capable of combining positive- and negative-ion mode results in a single testing scheme. For comprehensiveness, the built-in pathways were manually curated from three sources: Kyoto Encyclopedia of Genes and Genomes, Mummichog and The Small Molecule Pathway Database.
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After being proposed by Lloret et al. in 2011, the resilience components resistance, recovery, resilience and relative resilience became highly popular for studying tree growth responses to disturbances and extreme weather events....
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After being proposed by Lloret et al. in 2011, the resilience components resistance, recovery, resilience and relative resilience became highly popular for studying tree growth responses to disturbances and extreme weather events. As the 'Lloret indices', however, have conceptual limitations, various additional indices to characterize tree resilience have been discussed since then, namely: recovery period, total growth reduction, average recovery rate, and average growth reduction. In pointRes 2.0, a major update of the R-package pointRes, these new indices have now been implemented. Besides convenient functions for calculating and plotting resilience indices, two new functions for calculating pointer years using (i) the interval trend method, and (ii) a 'z-transformation of site chronology'-approach have been included as well. This technical note illustrates pointRes' new functionalities.
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In this paper we present the RMCriteria package to support the decision making system in the R software environment for statistical computing and graphics. The RMCriteria is a support decision system that implements all PROMETHEE ...
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In this paper we present the RMCriteria package to support the decision making system in the R software environment for statistical computing and graphics. The RMCriteria is a support decision system that implements all PROMETHEE family methods and also graphical and sensitivity analysis assisting the analysts to make their own decision process and also facilitating the analysis of the decisions.
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We introduce the R-package 'birdring', which provides a collection of R-functions to help with the analysis of ring re-encounter data. At present, it contains functions to read EURING data into R, to draw maps for visualising reco...
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We introduce the R-package 'birdring', which provides a collection of R-functions to help with the analysis of ring re-encounter data. At present, it contains functions to read EURING data into R, to draw maps for visualising recovery data, to re-code EURING code into interpretable names, and to calculate the loxodromic and orthodromic distances between two encounter locations. The package also allows spatially different re-encounter probabilities to be estimated using the division-coefficient method. A function to obtain the proportional overlap between prior and posterior distributions facilitates parameter estimability, which is often an issue in mark-recapture models. The package is a work-in-progress and we welcome additional contributions of functions for the analysis of ring re-encounter data.
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Cognitive diagnosis models (CDMs) have increasingly been applied in education and other fields. This article provides an overview of a widely used CDM, namely, the G-DINA model, and demonstrates a hands-on example of using multipl...
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Cognitive diagnosis models (CDMs) have increasingly been applied in education and other fields. This article provides an overview of a widely used CDM, namely, the G-DINA model, and demonstrates a hands-on example of using multiple R packages for a series of CDM analyses. This overview involves a step-by-step illustration and explanation of performing Q-matrix evaluation, CDM calibration, model fit evaluation, item diagnosticity investigation, classification reliability examination, and the result presentation and visualization. Some limitations of conducting CDM analysis in R are also discussed.
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Mass spectrometry imaging (MSI) consist of spatially located spectra with thousands of peaks. Only a fraction of these peaks corresponds to unique monoisotopic peaks, as mass spectra include isotopes, adducts and fragments of comp...
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Mass spectrometry imaging (MSI) consist of spatially located spectra with thousands of peaks. Only a fraction of these peaks corresponds to unique monoisotopic peaks, as mass spectra include isotopes, adducts and fragments of compounds. Current peak annotation solutions depend on matching MS features to compounds libraries. We present rMSIannotation, a peak annotation algorithm to annotate carbon isotopes and adducts in metabolomics and lipidomics imaging mass spectrometry datasets without using supporting libraries. rMSIannotation measures and evaluates the intensity ratio between carbon isotopic peaks and models their distribution across the m/z axis of the compounds in the Human Metabolome Database. Monoisotopic peak selection is based on the isotopic likelihood score (ILS) made of three components: image morphology correlation, validation of isotopic intensity ratios, and peak centroid mass deviation. rMSIannotation proposes pairs of peaks that can be adducts based on three scores: isotopic pattern coherence, image correlation and mass error. We validated rMSIannotation with three MALDI-MSI datasets which were manually annotated by experts, and compared the annotations obtained with rMSIannotation and with the METASPACE annotation platform. rMSIannotation replicated more than 90% of the manual annotation reported in FT-ICR datasets and expanded the list of annotated compounds with additional monoisotopic peaks and neutral masses. Finally, we evaluated isotopic peak annotation as a data reduction method for MSI by comparing the results of PCA and k-means segmentation before and after removing non-monoisotopic peaks. The results show that monoisotopic peaks retain most of the biologic variance in the dataset. (C) 2021 The Authors. Published by Elsevier B.V.
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This study aims to describe the various capabilities of the simmer package for R, particularly when running a discrete event simulation model. It then develops a technique for building effective DES simulation models that accurate...
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This study aims to describe the various capabilities of the simmer package for R, particularly when running a discrete event simulation model. It then develops a technique for building effective DES simulation models that accurately represent real systems and examines the simulation output on this simmer, both in statistical summary form and parameter estimation. The literature review method with descriptive and exploratory methodologies was employed in this study. When starting with simple models and progressing to more complicated forms step by step while explaining the system with a flow chart, model development is more successful. It is simple to replicate simulations in order to obtain standard error values for model parameter estimators. Creating a discrete event simulation in stages.
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Recent advances in understanding the symbiotic interactions between bacteria and fruit flies have shown that they are relevant for mass rearing and the sterile insect technique (SIT). SIT involves mass production and release of st...
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Recent advances in understanding the symbiotic interactions between bacteria and fruit flies have shown that they are relevant for mass rearing and the sterile insect technique (SIT). SIT involves mass production and release of sterile insects that would copulate with their wild conspecifics and thus decrease the population growth rate. The irradiation process used to sterilize mass-reared flies can modify the diversity and structure of the midgut bacterial communities, which could affect sterile male survival, flight capacity, and sexual competitiveness. Our aim was to compare bacterial communities in the midgut of wild and mass-reared Anastrepha obliqua (Macquart) males irradiated at 0, 60, and 80 Gy. After adult's emergence, their midguts were dissected, DNA was extracted, and high-throughput sequencing of the V3-V4 region of the 16S rDNA gene was performed. A total of 11 phyla, 17 classes, 47 families, and 52 genera of bacteria were identified. The most representative phylum was Proteobacteria and the predominant family was Enterobacteriaceae. We found that wild males had a different intestinal bacterial community from mass-reared males. In addition, irradiation at 60 and 80 Gy caused changes in the diversity and structure of the midgut microbiota of these sterile males, suggesting that mass rearing and irradiation cause artificial selection of the bacterial communities in the gut of A. obliqua males.
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Background and objectives: We introduce the R-package GenomicTools to perform, among others, a Multi-factor Dimensionality Reduction (MDR) for the identification of SNP-SNP interactions. The package further provides a new class of...
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Background and objectives: We introduce the R-package GenomicTools to perform, among others, a Multi-factor Dimensionality Reduction (MDR) for the identification of SNP-SNP interactions. The package further provides a new class of tests for an (exploratory) Quantitative Trait Loci analysis that overcomes some of the limitations of other popular (e)QTL approaches. Popular (e) QTL approaches that use linear models or ANOVA are often based on over-simplified models that have weak statistical properties and which are not robust against outlying observations.
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