Swarm-based algorithms emerged as a powerful family of optimization techniques, inspired by the collective behavior of social animals. In particle swarm optimization (PSO) the set of candidate ...solutions to the optimization problem is defined as a swarm of particles which may flow through the parameter space defining trajectories which are driven by their own and neighbors' best performances. In the present paper, the potential of particle swarm optimization for solving various kinds of optimization problems in chemometrics is shown through an extensive description of the algorithm (highlighting the importance of the proper choice of its metaparameters) and by means of selected worked examples in the fields of signal warping, estimation robust PCA solutions and variable selection.
Principal component analysis (PCA) is frequently used in genomics applications for quality assessment and exploratory analysis in high-dimensional data, such as RNA sequencing (RNA-seq) gene ...expression assays. Despite the availability of many software packages developed for this purpose, an interactive and comprehensive interface for performing these operations is lacking.
We developed the pcaExplorer software package to enhance commonly performed analysis steps with an interactive and user-friendly application, which provides state saving as well as the automated creation of reproducible reports. pcaExplorer is implemented in R using the Shiny framework and exploits data structures from the open-source Bioconductor project. Users can easily generate a wide variety of publication-ready graphs, while assessing the expression data in the different modules available, including a general overview, dimension reduction on samples and genes, as well as functional interpretation of the principal components.
pcaExplorer is distributed as an R package in the Bioconductor project ( http://bioconductor.org/packages/pcaExplorer/ ), and is designed to assist a broad range of researchers in the critical step of interactive data exploration.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Spectroscopy is widely used to characterize pharmaceutical products or processes, especially due to its desirable characteristics of being rapid, cheap, non-invasive/non-destructive and applicable ...both off-line and in-/at-/on-line. Spectroscopic techniques produce profiles containing a high amount of information, which can profitably be exploited through the use of multivariate mathematic and statistic (chemometric) techniques. The present paper aims at providing a brief overview of the different chemometric approaches applicable in the context of spectroscopy-based pharmaceutical analysis, discussing both the unsupervised exploration of the collected data and the possibility of building predictive models for both quantitative (calibration) and qualitative (classification) responses.
The interpretation of results from transcriptome profiling experiments via RNA sequencing (RNA-seq) can be a complex task, where the essential information is distributed among different tabular and ...list formats-normalized expression values, results from differential expression analysis, and results from functional enrichment analyses. A number of tools and databases are widely used for the purpose of identification of relevant functional patterns, yet often their contextualization within the data and results at hand is not straightforward, especially if these analytic components are not combined together efficiently.
We developed the GeneTonic software package, which serves as a comprehensive toolkit for streamlining the interpretation of functional enrichment analyses, by fully leveraging the information of expression values in a differential expression context. GeneTonic is implemented in R and Shiny, leveraging packages that enable HTML-based interactive visualizations for executing drilldown tasks seamlessly, viewing the data at a level of increased detail. GeneTonic is integrated with the core classes of existing Bioconductor workflows, and can accept the output of many widely used tools for pathway analysis, making this approach applicable to a wide range of use cases. Users can effectively navigate interlinked components (otherwise available as flat text or spreadsheet tables), bookmark features of interest during the exploration sessions, and obtain at the end a tailored HTML report, thus combining the benefits of both interactivity and reproducibility.
GeneTonic is distributed as an R package in the Bioconductor project ( https://bioconductor.org/packages/GeneTonic/ ) under the MIT license. Offering both bird's-eye views of the components of transcriptome data analysis and the detailed inspection of single genes, individual signatures, and their relationships, GeneTonic aims at simplifying the process of interpretation of complex and compelling RNA-seq datasets for many researchers with different expertise profiles.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Recent technological advancements have enabled the profiling of a large number of genome-wide features in individual cells. However, single-cell data present unique challenges that require the ...development of specialized methods and software infrastructure to successfully derive biological insights. The Bioconductor project has rapidly grown to meet these demands, hosting community-developed open-source software distributed as R packages. Featuring state-of-the-art computational methods, standardized data infrastructure and interactive data visualization tools, we present an overview and online book (https://osca.bioconductor.org) of single-cell methods for prospective users.
RNA sequencing (RNA-seq) is an ever increasingly popular tool for transcriptome profiling. A key point to make the best use of the available data is to provide software tools that are easy to use but ...still provide flexibility and transparency in the adopted methods. Despite the availability of many packages focused on detecting differential expression, a method to streamline this type of bioinformatics analysis in a comprehensive, accessible, and reproducible way is lacking.
We developed the ideal software package, which serves as a web application for interactive and reproducible RNA-seq analysis, while producing a wealth of visualizations to facilitate data interpretation. ideal is implemented in R using the Shiny framework, and is fully integrated with the existing core structures of the Bioconductor project. Users can perform the essential steps of the differential expression analysis workflow in an assisted way, and generate a broad spectrum of publication-ready outputs, including diagnostic and summary visualizations in each module, all the way down to functional analysis. ideal also offers the possibility to seamlessly generate a full HTML report for storing and sharing results together with code for reproducibility.
ideal is distributed as an R package in the Bioconductor project ( http://bioconductor.org/packages/ideal/ ), and provides a solution for performing interactive and reproducible analyses of summarized RNA-seq expression data, empowering researchers with many different profiles (life scientists, clinicians, but also experienced bioinformaticians) to make the ideal use of the data at hand.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•The present work provides a novel approach for the authentication of the Avola almond, labelled by the PAT mark.•Avola almonds have been analyzed by NIR spectroscopy coupled with PLS-DA or SIMCA.•· ...PLS-DA led to 100% of correct classification (in external validation) for samples belonging to the category of interest.•Variable Importance in Projection has highlighted which NIR variables contribute the most to the classification.
Avola almond is part of the “Traditional Italian Agri-food Product” (PAT) list, as established by The Italian Ministry of agricultural food, forestry and tourism policies; this endorsement testifies its status as a high added-value product, and, consequently, it highlights the need of analytical methodologies suitable for its authentication. For these reasons, in the present study, the possibility of developing a non-destructive approach, aimed at distinguishing almonds cultivated in the Avola area from others presenting a different geographical origin, has been investigated. To fulfil this purpose, 227 almonds, cultivated in the Avola area or in other Italian territories, have been analysed by near infrared (NIR) spectroscopy coupled with Partial Least Squares-Discriminant Analysis (PLS-DA) and Soft Independent Modelling of Class Analogies (SIMCA). The two tested approaches achieved satisfactory results (in external validation) indicating both of them would represent a suitable tool for the purpose of the study.
Abstract
Lipidomics is advantageous in the study of sebum perturbations occurring in acne. An extended evaluation of the sebum lipid profiles in acne-prone sebaceous areas is lacking in dark skin. ...Yet, there is a void space in understanding how the building blocks of sebum lipids, i.e. individual fatty acids (FAs), are intertwined with acne-prone skin. We aimed to determine the sebum lipidome in facial areas of adolescents with and without acne in Nigeria. A cross-sectional analytical study was conducted in 60 adolescents/young adults divided in 30 acne patients (15F, 15M) and 30 age and sex-matched controls. Sebum samples obtained from foreheads and cheeks were analysed separately by gas chromatography–mass spectrometry (GCMS) and thin layer chromatography (HPTLC). Distributions of sebum components were investigated with multivariate ANOVA-simultaneous component analysis (ASCA). Sebum incretion in acne was paralleled by significantly higher abundance of triglycerides, wax esters, and squalene together with monounsaturated FAs (MUFAs), and straight chain saturated FAs (SFAs), especially those with odd-carbon chain, i.e. C13:0, C15:0, and C17:0. Profiling weight/weight percentage of individual components revealed that, in acne, the free FAs (FFAs) array was shifted towards higher relative abundance of the SFAs C15:0, C16:0, and C17:0 and lower percentage of the anteiso-branched FFAs with 12, 14, 16, and 18 carbons. In acne patients, MUFAs and PUFAs were quantitatively increased and decreased on foreheads and cheeks, respectively. Relative abundance of fatty alcohols was decreased in acne independent on the site. The results indicated that acne associates with site-specific derangement of the pathways regulating the balance among odd straight-chain and branched-chain SFAs, MUFAs, which included sapienate (C16:1n-10), PUFAs, and squalene.
During early embryogenesis, microglia arise from yolk sac progenitors that populate the developing central nervous system (CNS), but how the tissue-resident macrophages are maintained throughout the ...organism’s lifespan still remains unclear. Here, we describe a system that allows specific, conditional ablation of microglia in adult mice. We found that the microglial compartment was reconstituted within 1 week of depletion. Microglia repopulation relied on CNS-resident cells, independent from bone-marrow-derived precursors. During repopulation, microglia formed clusters of highly proliferative cells that migrated apart once steady state was achieved. Proliferating microglia expressed high amounts of the interleukin-1 receptor (IL-1R), and treatment with an IL-1R antagonist during the repopulation phase impaired microglia proliferation. Hence, microglia have the potential for efficient self-renewal without the contribution of peripheral myeloid cells, and IL-1R signaling participates in this restorative proliferation process.
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•Microglia repopulate within 5 days of depletion•Under defined host conditions, microglia can be replaced by BM cells•Without preconditioning, they renew themselves locally by massive proliferation•IL-1R1 on microglia is involved in self-renewal and maintenance
Microglia arise from yolk sac progenitors that populate the developing central nervous system (CNS), but how these cells are maintained in the adult remains unclear. Waisman and colleagues show via a genetic approach that after ablation, microglia repopulation is driven by local progenitors in response to IL-1R signaling.
An innovative procedure to classify oat and groat kernels based on coupling hyperspectral imaging (HSI) in the near infrared (NIR) range (1006–1650nm) and chemometrics was designed, developed and ...validated. According to market requirements, the amount of groat, that is the hull-less oat kernels, is one of the most important quality characteristics of oats. Hyperspectral images of oat and groat samples have been acquired by using a NIR spectral camera (Specim, Finland) and the resulting data hypercubes were analyzed applying Principal Component Analysis (PCA) for exploratory purposes and Partial Least Squares-Discriminant Analysis (PLS-DA) to build the classification models to discriminate the two kernel typologies. Results showed that it is possible to accurately recognize oat and groat single kernels by HSI (prediction accuracy was almost 100%). The study demonstrated also that good classification results could be obtained using only three wavelengths (1132, 1195 and 1608nm), selected by means of a bootstrap-VIP procedure, allowing to speed up the classification processing for industrial applications. The developed objective and non-destructive method based on HSI can be utilized for quality control purposes and/or for the definition of innovative sorting logics of oat grains.
► A new method for identification of oat and groat kernels by NIR-HSI was developed. ► The study was applied to improve quality of oat products. ► Different chemometric strategies were applied to the oats spectral data. ► Oat and groat kernels were correctly classified also selecting only 3 wavelengths. ► HSI is a powerful non-destructive technique to extract features from sample surface.
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