scholarly journals Nonlinear Dependence in the Discovery of Differentially Expressed Genes

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
J. R. Deller ◽  
Hayder Radha ◽  
J. Justin McCormick ◽  
Huiyan Wang
Keyword(s):  
Microarray Data ◽  
Estimation Error ◽  
Detection Algorithm ◽  
Differentially Expressed ◽  
Nonlinear Dependence ◽  
Data Sets ◽  
Entropy Maximization ◽  
Type 1 Error ◽  
The Moment ◽  
Third Moment

Microarray data are used to determine which genes are active in response to a changing cell environment. Genes are “discovered” when they are significantly differentially expressed in the microarray data collected under the differing conditions. In one prevalent approach, all genes are assumed to satisfy a null hypothesis, ℍ0, of no difference in expression. A false discovery (type 1 error) occurs when ℍ0 is incorrectly rejected. The quality of a detection algorithm is assessed by estimating its number of false discoveries, F. Work involving the second-moment modeling of the z-value histogram (representing gene expression differentials) has shown significantly deleterious effects of intergene expression correlation on the estimate of F. This paper suggests that nonlinear dependencies could likewise be important. With an applied emphasis, this paper extends the “moment framework” by including third-moment skewness corrections in an estimator of F. This estimator combines observed correlation (corrected for sampling fluctuations) with the information from easily identifiable null cases. Nonlinear-dependence modeling reduces the estimation error relative to that of linear estimation. Third-moment calculations involve empirical densities of 3×3 covariance matrices estimated using very few samples. The principle of entropy maximization is employed to connect estimated moments to F inference. Model results are tested with BRCA and HIV data sets and with carefully constructed simulations.

Identification of Candidate Genetic Markers and a Novel 4-genes Diagnostic Model in Osteoarthritis through Integrating Multiple Microarray Data

2020 ◽  
Vol 23 (8) ◽  
pp. 805-813
Author(s):  
Ai Jiang ◽  
Peng Xu ◽  
Zhenda Zhao ◽  
Qizhao Tan ◽  
Shang Sun ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Microarray Data ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Functional Enrichment ◽  
Joint Disease ◽  
Support Vector ◽  
Diagnostic Model ◽  
Data Sets

Background: Osteoarthritis (OA) is a joint disease that leads to a high disability rate and a low quality of life. With the development of modern molecular biology techniques, some key genes and diagnostic markers have been reported. However, the etiology and pathogenesis of OA are still unknown. Objective: To develop a gene signature in OA. Method: In this study, five microarray data sets were integrated to conduct a comprehensive network and pathway analysis of the biological functions of OA related genes, which can provide valuable information and further explore the etiology and pathogenesis of OA. Results and Discussion: Differential expression analysis identified 180 genes with significantly expressed expression in OA. Functional enrichment analysis showed that the up-regulated genes were associated with rheumatoid arthritis (p < 0.01). Down-regulated genes regulate the biological processes of negative regulation of kinase activity and some signaling pathways such as MAPK signaling pathway (p < 0.001) and IL-17 signaling pathway (p < 0.001). In addition, the OA specific protein-protein interaction (PPI) network was constructed based on the differentially expressed genes. The analysis of network topological attributes showed that differentially upregulated VEGFA, MYC, ATF3 and JUN genes were hub genes of the network, which may influence the occurrence and development of OA through regulating cell cycle or apoptosis, and were potential biomarkers of OA. Finally, the support vector machine (SVM) method was used to establish the diagnosis model of OA, which not only had excellent predictive power in internal and external data sets (AUC > 0.9), but also had high predictive performance in different chip platforms (AUC > 0.9) and also had effective ability in blood samples (AUC > 0.8). Conclusion: The 4-genes diagnostic model may be of great help to the early diagnosis and prediction of OA.

scholarly journals miRNA Expression Characterizes Histological Subtypes and Metastasis in Penile Squamous Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1480
Author(s):  
Hiresh Ayoubian ◽  
Joana Heinzelmann ◽  
Sebastian Hölters ◽  
Oybek Khalmurzaev ◽  
Alexey Pryalukhin ◽  
...  
Keyword(s):  
Microarray Data ◽  
Expression Patterns ◽  
Hpv Infection ◽  
Differentially Expressed ◽  
Histological Subtypes ◽  
Specific Expression ◽  
Tissue Samples ◽  
Qrt Pcr ◽  
Differentially Expressed Mirnas ◽  
The Impact

Although microRNAs are described as promising biomarkers in many tumor types, little is known about their role in PSCC. Thus, we attempted to identify miRNAs involved in tumor development and metastasis in distinct histological subtypes considering the impact of HPV infection. In a first step, microarray analyses were performed on RNA from formalin-fixed, paraffin-embedded tumor (22), and normal (8) tissue samples. Microarray data were validated for selected miRNAs by qRT-PCR on an enlarged cohort, including 27 tumor and 18 normal tissues. We found 876 significantly differentially expressed miRNAs (p ≤ 0.01) between HPV-positive and HPV-negative tumor samples by microarray analysis. Although no significant differences were detected between normal and tumor tissue in the whole cohort, specific expression patterns occurred in distinct histological subtypes, such as HPV-negative usual PSCC (95 differentially expressed miRNAs, p ≤ 0.05) and HPV-positive basaloid/warty subtypes (247 differentially expressed miRNAs, p ≤ 0.05). Selected miRNAs were confirmed by qRT-PCR. Furthermore, microarray data revealed 118 miRNAs (p ≤ 0.01) that were significantly differentially expressed in metastatic versus non-metastatic usual PSCC. The lower expression levels for miR-137 and miR-328-3p in metastatic usual PSCC were validated by qRT-PCR. The results of this study confirmed that specific miRNAs could serve as potential diagnostic and prognostic markers in single PSCC subtypes and are associated with HPV-dependent pathways.

scholarly journals Identification of Genes Expressed in Hyperpigmented Skin Using Meta-Analysis of Microarray Data Sets

2015 ◽  
Vol 135 (10) ◽  
pp. 2455-2463 ◽  
Author(s):  
Lanlan Yin ◽  
Sergio G. Coelho ◽  
Julio C. Valencia ◽  
Dominik Ebsen ◽  
Andre Mahns ◽  
...  
Keyword(s):  
Microarray Data ◽  
Meta Analysis ◽  
Data Sets

scholarly journals Day-time identification of summer hailstorm cells from MSG data

2013 ◽  
Vol 1 (5) ◽  
pp. 5453-5498 ◽  
Author(s):  
A. Merino ◽  
L. López ◽  
J. L. Sánchez ◽  
E. García-Ortega ◽  
E. Cattani ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Deep Convection ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Phase Method ◽  
Data Sets ◽  
Liquid Water Path ◽  
Two Phase ◽  
Logistic Regression Models ◽  
Ebro Valley

Abstract. Identifying deep convection is of paramount importance, as it may be associated with extreme weather that has significant impact on the environment, property and the population. A new method, the Hail Detection Tool (HDT), is described for identifying hail-bearing storms using multi-spectral Meteosat Second Generation (MSG) data. HDT was conceived as a two-phase method, in which the first step is the Convective Mask (CM) algorithm devised for detection of deep convection, and the second a Hail Detection algorithm (HD) for the identification of hail-bearing clouds among cumulonimbus systems detected by CM. Both CM and HD are based on logistic regression models trained with multi-spectral MSG data-sets comprised of summer convective events in the middle Ebro Valley between 2006–2010, and detected by the RGB visualization technique (CM) or C-band weather radar system of the University of León. By means of the logistic regression approach, the probability of identifying a cumulonimbus event with CM or a hail event with HD are computed by exploiting a proper selection of MSG wavelengths or their combination. A number of cloud physical properties (liquid water path, optical thickness and effective cloud drop radius) were used to physically interpret results of statistical models from a meteorological perspective, using a method based on these "ingredients." Finally, the HDT was applied to a new validation sample consisting of events during summer 2011. The overall Probability of Detection (POD) was 76.9% and False Alarm Ratio 16.7%.

scholarly journals Pedestrian detection algorithm based on improved muti-scale feature fusion

2021 ◽  
Vol 2078 (1) ◽  
pp. 012008
Author(s):  
Hui Liu ◽  
Keyang Cheng
Keyword(s):  
Clustering Algorithm ◽  
Feature Fusion ◽  
Pedestrian Detection ◽  
Detection Algorithm ◽  
Data Sets ◽  
False Detection ◽  
Scale Feature ◽  
Multi Scale ◽  
Dilated Convolution ◽  
Small Targets

Abstract Aiming at the problem of false detection and missed detection of small targets and occluded targets in the process of pedestrian detection, a pedestrian detection algorithm based on improved multi-scale feature fusion is proposed. First, for the YOLOv4 multi-scale feature fusion module PANet, which does not consider the interaction relationship between scales, PANet is improved to reduce the semantic gap between scales, and the attention mechanism is introduced to learn the importance of different layers to strengthen feature fusion; then, dilated convolution is introduced. Dilated convolution reduces the problem of information loss during the downsampling process; finally, the K-means clustering algorithm is used to redesign the anchor box and modify the loss function to detect a single category. The experimental results show that the improved pedestrian detection algorithm in the INRIA and WiderPerson data sets under different congestion conditions, the AP reaches 96.83% and 59.67%, respectively. Compared with the pedestrian detection results of the YOLOv4 model, the algorithm improves by 2.41% and 1.03%, respectively. The problem of false detection and missed detection of small targets and occlusion has been significantly improved.

scholarly journals Comparative functional genomic analysis of Alzheimer’s affected and naturally aging brains

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8682
Author(s):  
Yi-Shian Peng ◽  
Chia-Wei Tang ◽  
Yi-Yun Peng ◽  
Hung Chang ◽  
Chien-Lung Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Microarray Data ◽  
Gene List ◽  
Amyloid Β ◽  
Differentially Expressed ◽  
Gene Expression Microarray ◽  
Expression Microarray ◽  
Functional Genomic Analysis ◽  
Gene Expression Microarray Data

Background Alzheimer’s disease (AD) is a prevalent progressive neurodegenerative human disease whose cause remains unclear. Numerous initially highly hopeful anti-AD drugs based on the amyloid-β (Aβ) hypothesis of AD have failed recent late-phase tests. Natural aging (AG) is a high-risk factor for AD. Here, we aim to gain insights in AD that may lead to its novel therapeutic treatment through conducting meta-analyses of gene expression microarray data from AG and AD-affected brain. Methods Five sets of gene expression microarray data from different regions of AD (hereafter, ALZ when referring to data)-affected brain, and one set from AG, were analyzed by means of the application of the methods of differentially expressed genes and differentially co-expressed gene pairs for the identification of putatively disrupted biological pathways and associated abnormal molecular contents. Results Brain-region specificity among ALZ cases and AG-ALZ differences in gene expression and in KEGG pathway disruption were identified. Strong heterogeneity in AD signatures among the five brain regions was observed: HC/PC/SFG showed clear and pronounced AD signatures, MTG moderately so, and EC showed essentially none. There were stark differences between ALZ and AG. OXPHOS and Proteasome were the most disrupted pathways in HC/PC/SFG, while AG showed no OXPHOS disruption and relatively weak Proteasome disruption in AG. Metabolic related pathways including TCA cycle and Pyruvate metabolism were disrupted in ALZ but not in AG. Three pathogenic infection related pathways were disrupted in ALZ. Many cancer and signaling related pathways were shown to be disrupted AG but far less so in ALZ, and not at all in HC. We identified 54 “ALZ-only” differentially expressed genes, all down-regulated and which, when used to augment the gene list of the KEGG AD pathway, made it significantly more AD-specific.

scholarly journals Low and high grade glioma segmentation in multispectral brain MRI data

2018 ◽  
Vol 10 (1) ◽  
pp. 110-132 ◽  
Author(s):  
László Szilágyi ◽  
David Iclănzan ◽  
Zoltán Kapás ◽  
Zsófia Szabó ◽  
Ágnes Győrfi ◽  
...  
Keyword(s):  
Early Stage ◽  
Brain Mri ◽  
High Grade Glioma ◽  
Detection Algorithm ◽  
Gabor Wavelet ◽  
Low Grade ◽  
Data Sets ◽  
Morphological Operations ◽  
High Grade ◽  
Mass Screening System

Abstract Several hundreds of thousand humans are diagnosed with brain cancer every year, and the majority dies within the next two years. The chances of survival could be easiest improved by early diagnosis. This is why there is a strong need for reliable algorithms that can detect the presence of gliomas in their early stage. While an automatic tumor detection algorithm can support a mass screening system, the precise segmentation of the tumor can assist medical staff at therapy planning and patient monitoring. This paper presents a random forest based procedure trained to segment gliomas in multispectral volumetric MRI records. Beside the four observed features, the proposed solution uses 100 further features extracted via morphological operations and Gabor wavelet filtering. A neighborhood-based post-processing was designed to regularize and improve the output of the classifier. The proposed algorithm was trained and tested separately with the 54 low-grade and 220 high-grade tumor volumes of the MICCAI BRATS 2016 training database. For both data sets, the achieved accuracy is characterized by an overall mean Dice score > 83%, sensitivity > 85%, and specificity > 98%. The proposed method is likely to detect all gliomas larger than 10 mL.

scholarly journals Os desafios atuais mais fundos à vida religiosa

2019 ◽  
Vol 64 (255) ◽  
pp. 638
Author(s):  
José María Vigil
Keyword(s):  
Religious Life ◽  
Present Situation ◽  
Symbolic Capital ◽  
Spatial Dimensions ◽  
The Moment ◽  
Third Moment

O artigo de José Maria Vigil, Claretiano, enumera, no momento “Ver”, os mais fundos desafios que a Vida Religiosa (VR) enfrenta em nossa época. A seguir, no momento “Julgar”, chama a atenção para as profundas e céleres mudanças que estão ocorrendo nesta “época-eixo”, tanto na dimensão temporal como na espacial. Num terceiro momento, o do “Agir”, identifica as tarefas que acredita poder deduzir desta situação para a VR. Em particular, sugere: a) recuperar a teologia da VR; b) recuperar a antropologia da vida radical; e c) adequar o capital simbólico da VR. Concluindo, sintetiza suas propostas em duas grandes tarefas: 1) “desabsolutizar o cristocentrismo da VR”, e 2) “reinocentralizar a VR”. Reflexão pertinente quando se pensa na “refundação” da VR!Abstract: The article by José Maria Vigil, a Claretian, lists, in the moment “See”, the gravest challenges faced by the Religious Life (RL) in our times. In the moment “Judge” he calls attention to the deep and fast changes that are taking place in this “axle-age” both in the temporal and in the spatial dimensions. In a third moment – that of “Act” – he identifies the tasks that, in his opinion, should be carried out by the RL in the present situation. In particular, he suggests: a) rescue the theology of the RL; b) rescue the anthropology of the radical life; c) adjust the symbolic capital of the RL. In the conclusion, he synthesizes his proposals into two large tasks, namely: 1) “make the Christ-centrism of the RL less absolute” and 2) “make the RL more Kingdom-centric”. A pertinent idea when one thinks of the “re-founding” of the RL!

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