gianluca sottile | Università degli Studi di Palermo (original) (raw)

Papers by gianluca sottile

Scientific Reports

Statistical tests of differential expression usually suffer from two problems. Firstly, their sta... more Statistical tests of differential expression usually suffer from two problems. Firstly, their statistical power is often limited when applied to small and skewed data sets. Secondly, gene expression data are usually discretized by applying arbitrary criteria to limit the number of false positives. In this work, a new statistical test obtained from a convolution of multivariate hypergeometric distributions, the Hy-test, is proposed to address these issues. Hy-test has been carried out on transcriptomic data from breast and kidney cancer tissues, and it has been compared with other differential expression analysis methods. Hy-test allows implicit discretization of the expression profiles and is more selective in retrieving both differential expressed genes and terms of Gene Ontology. Hy-test can be adopted together with other tests to retrieve information that would remain hidden otherwise, e.g., terms of (1) cell cycle deregulation for breast cancer and (2) “programmed cell death” f...

Stochastic Environmental Research and Risk Assessment

Understanding the structure of precipitation and its separation into stratiform and convective co... more Understanding the structure of precipitation and its separation into stratiform and convective components is still today one of the important and interesting challenges for the scientific community. Despite this interest and the advances made in this field, the classification of rainfall into convective and stratiform components is still today not trivial. This study applies a novel criterion based on a clustering approach to analyze a high temporal resolution precipitation dataset collected for the period 2002–2018 over the Sicily (Italy). Starting from the rainfall events obtained from this dataset, the developed methodology makes it possible to classify the rainfall events into four different classes, which can be related to the convective and stratiform components of the events on the basis of their hyetograph shapes and average intensities. The results show that the occurrence of stratiform events is always much higher than the convective ones, especially in the winter and spri...

Computational Statistics & Data Analysis, 2022

Additional file 6: Table S2. List of 107 potential candidate genes under directional selection in... more Additional file 6: Table S2. List of 107 potential candidate genes under directional selection in the Valle del Belice sheep breed.

Additional file 3: Figures S3, S4, S5, S6. Plot of SNP occurrences (%) in ROH against the genomic... more Additional file 3: Figures S3, S4, S5, S6. Plot of SNP occurrences (%) in ROH against the genomic regions of QTL for OAR chromosomes with the highest inbreeding coefficient (OAR 2, 4, 11, 23).

Additional file 2: Figure S2. Total number of runs of homozygosity (ROH) longer than 1Â Mb and to... more Additional file 2: Figure S2. Total number of runs of homozygosity (ROH) longer than 1Â Mb and total length of genome (Mb) covered by ROH segments per individual. Observed (black) vs simulated (red) data.

Additional file 1: Figure S1. Mean sum of runs of homozygosity (ROH) per animal estimated within ... more Additional file 1: Figure S1. Mean sum of runs of homozygosity (ROH) per animal estimated within four different generation categories. ROH were mapped according to their genetic positions (i.e. linkage map positions). ROH length (lÂ cM) within each category was determined using 100/2Â g, replacing g with the number of generations of interest.

Hidden Markov models (HMMs) have been successfully applied in various disciplines, including biol... more Hidden Markov models (HMMs) have been successfully applied in various disciplines, including biology, speech recognition, economics/finance, climatology, psychology and medicine. They combine immense flexibility with relative mathematical simplicity and computational tractability, and as a consequence have become increasingly popular as general-purpose models for time series data. In this talk, I will first introduce the basic HMM machinery and showcase the practical application of HMMs using intuitive examples. I will then demonstrate how the HMM machinery can be combined with penalized splines to allow for flexible nonparametric inference in general-purpose HMM-type classes of models. The focus of the presentation will lie on practical aspects of nonparametric modelling in these frameworks, with the methods being illustrated in economic and ecological real data examples, featuring, inter alia, the famous wild haggis animal, blue whales and the well-known Lydia Pinkham sales data.

Modeling quantile regression coefficients functions permits describing the coefficients of a quan... more Modeling quantile regression coefficients functions permits describing the coefficients of a quantile regression model as parametric functions of the order of the quantile. This approach has numerous advantages over standard quantile regression, in which different quantiles are estimated one at the time: it facilitates estimation and inference, improves the interpretation of the results, and is statistically efficient. On the other hand, it poses new challenges in terms of model selection. We describe a penalized approach that can be used to identify a parsimonious model that can fit the data well. We describe the method, and analyze the dataset that motivated the present paper. The proposed approach is implemented in the qrcmNP package in R. Abstract I coefficienti di una regressione quantilica sono funzioni iniettive dell’ordine del quantile. L’approccio standard è quello di stimare i quantili uno alla volta. Un metodo alternativo è quello di esprimere la forma funzionale dei coefficienti usando un modello parametrico. Questo approccio ha numerosi vantaggi: semplifica le procedure di stima e inferenza, migliora l’interpretazione dei risultati, e risulta statisticamente efficiente. Al tempo stesso, pone nuove sfide in termini di selezione del modello. La nostra proposta è quella di usare un metodo penalizzato che permetta di identificare un modello parsimonioso che rappresenti correttamente la funzione quantilica. In questo articolo descriviamo il metodo, e analizziamo il dataset che ha motivato il lavoro. L’approccio proposto è stato implementato nel pacchetto R qrcmNP.

Statistical Modelling, 2021

Quantile regression (QR) has gained popularity during the last decades, and is now considered a s... more Quantile regression (QR) has gained popularity during the last decades, and is now considered a standard method by applied statisticians and practitioners in various fields. In this work, we applied QR to investigate climate change by analysing historical temperatures in the Arctic Circle. This approach proved very flexible and allowed to investigate the tails of the distribution, that correspond to extreme events. The presence of quantile crossing, however, prevented using the fitted model for prediction and extrapolation. In search of a possible solution, we first considered a different version of QR, in which the QR coefficients were described by parametric functions. This alleviated the crossing problem, but did not eliminate it completely. Finally, we exploited the imposed parametric structure to formulate a constrained optimization algorithm that enforced monotonicity. The proposed example showed how the relatively unexplored field of parametric quantile functions could offer ...

Journal of Applied Statistics, 2020

Students' migration mobility is the new form of migration: students migrate to improve their skil... more Students' migration mobility is the new form of migration: students migrate to improve their skills and become more valued for the job market. The data regard the migration of Italian Bachelors who enrolled at Master Degree level, moving typically from poor to rich areas. This paper investigates the migration and other possible determinants on the Master Degree students' performance. The Clustering of Effects approach for Quantile Regression Coefficients Modelling has been used to cluster the effects of some variables on the students' performance for three Italian macro-areas. Results show evidence of similarity between Southern and Centre students, with respect to the Northern ones.

Current Alzheimer Research, 2020

Objective: To evaluate in 419 stroke-free cognitively normal subjects (CN) aged 45-82 years cover... more Objective: To evaluate in 419 stroke-free cognitively normal subjects (CN) aged 45-82 years covering during a long prospective study (11.54 ± 1.47 years) the preclinical to dementia spectrum: 1) the distribution of small vessel disease (V) and brain atrophy (A) aggregated as following: V−/A−, V−/A+, V+/A−, V+/A+; 2) the relationship of these imaging classes with individual apolipoprotein E (APOE) genotypes; 3) the risk of progression to Alzheimer Disease (AD) of the individual APOE genotypes. Methods: Participants underwent one baseline (t0), and 4 clinical and neuropsychological assessments (t1,t2,t3, and t4). Brain MRI was performed in all subjects at t0, t2, t3 and t4.. White matter hyperintensities were assessed through two visual rating scales. Lacunes were also rated. Subcortical and global brain atrophy were determined through the bicaudate ratio and the lateral ventricle to brain ratio, respectively. APOE genotypes were determined at t0 in all subjects. Cox proportional haza...

Statistics and Computing, 2020

In many applied fields, such as genomics, different types of data are collected on the same syste... more In many applied fields, such as genomics, different types of data are collected on the same system, and it is not uncommon that some of these datasets are subject to censoring as a result of the measurement technologies used, such as data generated by polymerase chain reactions and flow cytometer. When the overall objective is that of network inference, at possibly different levels of a system, information coming from different sources and/or different steps of the analysis can be integrated into one model with the use of conditional graphical models. In this paper, we develop a doubly penalized inferential procedure for a conditional Gaussian graphical model when data can be subject to censoring. The computational challenges of handling censored data in high dimensionality are met with the development of an efficient Expectation-Maximization algorithm, based on approximate calculations of the moments of truncated Gaussian distributions and on a suitably derived two-step procedure alternating graphical lasso with a novel block-coordinate multivariate lasso approach. We evaluate the performance of this approach on an extensive simulation study and on gene expression data generated by RT-qPCR technologies, where we are able to integrate network inference, differential expression detection and data normalization into one model.

Computational Statistics, 2018

In this paper, we propose a new method for finding similarity of effects based on quantile regres... more In this paper, we propose a new method for finding similarity of effects based on quantile regression models. Clustering of effects curves (CEC) techniques are applied to quantile regression coefficients, which are one-to-one functions of the order of the quantile. We adopt the quantile regression coefficients modeling (QRCM) framework to describe the functional form of the coefficient functions by means of parametric models. The proposed method can be utilized to cluster the effect of covariates with a univariate response variable, or to cluster a multivariate outcome. We report simulation results, comparing our approach with the existing techniques. The idea of combining CEC with QRCM permits simplifying computation and interpretation of the results, and may improve the ability to identify clusters. We illustrate a variety of applications, highlighting the advantages and the usefulness of the described method.

Journal of Allergy and Clinical Immunology, 2020

This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Goals  To develop a methodology capable to separate heavy (short duration and high intensity) fr... more Goals  To develop a methodology capable to separate heavy (short duration and high intensity) from light (high duration and low intensity) rainfall events.  To verify if the heavy and light rainfall events can be always led to convective and stratiform events, respectively, or if necessary to introduce new classes to classify mixed and/or unresolved rainfall. HEAVY LIGHT MIXED / UNRESOLVED

Animals, 2020

Through the development of the high-throughput genotyping arrays, molecular markers and genes rel... more Through the development of the high-throughput genotyping arrays, molecular markers and genes related to phenotypic traits have been identified in livestock species. In poultry, plumage color is an important qualitative trait that can be used as phenotypic marker for breed identification. In order to assess sources of genetic variation related to the Polverara chicken breed plumage colour (black vs. white), we carried out a genome-wide association study (GWAS) and a genome-wide fixation index (FST) scan to uncover the genomic regions involved. A total of 37 animals (17 white and 20 black) were genotyped with the Affymetrix 600 K Chicken single nucleotide polymorphism (SNP) Array. The combination of results from GWAS and FST revealed a total of 40 significant markers distributed on GGA 01, 03, 08, 12 and 21, and located within or near known genes. In addition to the well-known TYR, other candidate genes have been identified in this study, such as GRM5, RAB38 and NOTCH2. All these gen...

Animal Genetics, 2019

Nero Siciliano (Sicilian Black, SB) is a local pig breed generally of uniform black color. In add... more Nero Siciliano (Sicilian Black, SB) is a local pig breed generally of uniform black color. In addition to this officially recognized breed, there are animals showing morphological characteristics resembling the SB but with gray hair (Sicilian Grey, SG). The SG, compared with the SB, also shows a more compact structure with greater transverse diameters, higher average daily gains and lower thickness of the back fat. In this study, using the Illumina PorcineSNP60 BeadChip, we run genome-wide analyses to identify regions that may explain the phenotypic differences between SB (n = 21) and SG (n = 27) individuals. Combining the results of the two case-control approaches (GWAS and FST ), we identified two significant regions, one on SSC5 (95 401 083 bp) and one on SSC15 (55 051 435 bp), which contains several candidate genes related to growth traits in pig. The results of the Bayesian population differentiation approach identified a marker near the MGAT4C, a gene associated with average daily gain in pigs. Finally, scanning the genome for runs of homozygosity islands, we found that the two groups have different runs of homozygosity islands, with several candidate genes involved in coat color (in SG) or related to different pig performance traits (in SB). In summary, the two analyzed groups differed for several phenotypic traits, and genes involved in these traits (growth, meat traits and coat color) were detected. This study provided another contribution to the identification of genomic regions involved in phenotypic variability in local pig populations.

Current Alzheimer Research, 2019

Background:Mild Parkinsonian Signs (MPS) have been associated with Mild Cognitive Impairment (MCI... more Background:Mild Parkinsonian Signs (MPS) have been associated with Mild Cognitive Impairment (MCI) types with conflicting results.Objective:To investigate the association of individual MPS with different MCI types using logistic ridge regression analysis, and to evaluate for each MCI type, the association of MPS with caudate atrophy, global cerebral atrophy, and the topographical location of White Matter Hyperintensities (WMH), and lacunes.Methods:A cross-sectional study was performed among 1,168 subjects with different types of MCI aged 45-97 (70,52 ± 9,41) years, who underwent brain MRI. WMH were assessed through two visual rating scales. The number and location of lacunes were also rated. Atrophy of the caudate nuclei and global cerebral atrophy were assessed through the bicaudate ratio, and the lateral ventricles to brain ratio, respectively. Apolipoprotein E (APOE) genotypes were also assessed. Using the items of the motor section of the Unified Parkinson’s Disease Rating Scale...

Journal of Animal Breeding and Genetics, 2019

, Z. H. (2017). Comparative analysis on genome-wide DNA methylation in longissimus dorsi muscle b... more , Z. H. (2017). Comparative analysis on genome-wide DNA methylation in longissimus dorsi muscle between Small Tailed Han and Dorper × Small Tailed Han crossbred sheep.