scholarly journals Simultaneous Enrichment Analysis of all Possible Gene-sets: Unifying Self-Contained and Competitive Methods

2019 ◽  
Vol 21 (4) ◽  
pp. 1302-1312 ◽  
Author(s):  
Mitra Ebrahimpoor ◽  
Pietro Spitali ◽  
Kristina Hettne ◽  
Roula Tsonaka ◽  
Jelle Goeman
Keyword(s):  
Statistical Power ◽  
Enrichment Analysis ◽  
Mdx Mice ◽  
Biological Knowledge ◽  
P Value ◽  
Advantages And Disadvantages ◽  
Natural Connection ◽  
Special Cases ◽  
Gene Set Testing ◽  
Simultaneous Enrichment

Abstract Studying sets of genomic features is increasingly popular in genomics, proteomics and metabolomics since analyzing at set level not only creates a natural connection to biological knowledge but also offers more statistical power. Currently, there are two gene-set testing approaches, self-contained and competitive, both of which have their advantages and disadvantages, but neither offers the final solution. We introduce simultaneous enrichment analysis (SEA), a new approach for analysis of feature sets in genomics and other omics based on a new unified null hypothesis, which includes the self-contained and competitive null hypotheses as special cases. We employ closed testing using Simes tests to test this new hypothesis. For every feature set, the proportion of active features is estimated, and a confidence bound is provided. Also, for every unified null hypotheses, a $P$-value is calculated, which is adjusted for family-wise error rate. SEA does not need to assume that the features are independent. Moreover, users are allowed to choose the feature set(s) of interest after observing the data. We develop a novel pipeline and apply it on RNA-seq data of dystrophin-deficient mdx mice, showcasing the flexibility of the method. Finally, the power properties of the method are evaluated through simulation studies.

scholarly journals Statistical power of gene-set enrichment analysis is a function of gene set correlation structure

2017 ◽  
Author(s):  
David M. Swanson
Keyword(s):  
Statistical Power ◽  
Sequence Data ◽  
Enrichment Analysis ◽  
Analytical Framework ◽  
Gene Set Enrichment Analysis ◽  
Correlation Structure ◽  
Gene Set ◽  
Type 1 Error ◽  
Gene Set Testing ◽  
Supplementary Material

AbstractMotivation:We describe why statistical power for both self-contained and competitive gene-set tests is a function of the correlation structure of co-expressed genes, and why this characteristic is undesirable for gene-set analyses. Variable statistical power as a function of gene correlation structure has not been observed or studied previously. The observation is important in part because gene-set testing methodology is well-developed, yet this fundamental feature of many of its tests is unknown and has the potential to reinterpret past gene-set test results and guide future implementations, including those using sequence data. Type 1 error inflation is also amenable for study in our statistical framework; while it has been well-studied and described previously for both self-contained and competitive tests, it has less often been done in an analytical framework. Our observations apply to four commonly-used gene-set testing approaches for microarrays, including CAMERA, ROAST, SAFE, and GAGE, and a recently proposed one for RNAseq, MAST.Results:We characterize situations in which power is especially small relative to effect sizes of genes in a set for both competitive and self-contained gene-set tests. We propose three alternative tests, one of which replicates the properties of permutation-based self-contained tests, but avoids the need for even recently proposed, rotation-based approximations to permutations. The two other proposed tests have the unique property that statistical power is not a function of co-expression correlation in the gene-set and therefore is the preferred methodology. We compare our proposed tests to leading gene-set tests and apply them to an already-published study of smoking exposure on pregnant women.Contact:[email protected] Material:Online supplementary material includes additional simulation results supporting the relationship between the “mixed” and “directional” gene-set tests of ROAST and closed-form implementations of them.

scholarly journals Variance-adjusted Mahalanobis (VAM): a fast and accurate method for cell-specific gene set scoring

2020 ◽  
Author(s):  
H. Robert Frost
Keyword(s):  
Single Cell ◽  
Statistical Power ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Specific Gene ◽  
Technical Noise ◽  
Gene Set ◽  
Pathway Gene ◽  
Gene Set Testing ◽  
A Cell

AbstractSingle cell RNA sequencing (scRNA-seq) is a powerful tool for analyzing complex tissues with recent advances enabling the transcriptomic profiling of thousands to tens-of-thousands of individual cells. Although scRNA-seq provides unprecedented insights into the biology of heterogeneous cell populations, analyzing such data on a gene-by-gene basis is challenging due to the large number of tested hypotheses, high level of technical noise and inflated zero counts. One promising approach for addressing these challenges is gene set testing, or pathway analysis. By combining the expression data for all genes in a pathway, gene set testing can mitigate the impacts of sparsity and noise and improve interpretation, replication and statistical power. Unfortunately, statistical and biological differences between single cell and bulk expression measurements make it challenging to use gene set testing methods originally developed for bulk tissue on scRNA-seq data and progress on single cell-specific methods has been limited. To address this challenge, we have developed a new gene set testing method, variance-adjusted Mahalanobis (VAM), that seamlessly integrates with the Seurat framework and is designed to accommodate the technical noise, sparsity and large sample sizes characteristic of scRNA-seq data. The VAM method computes cell-specific pathway scores to transform a cell-by-gene matrix into a cell-by-pathway matrix that can be used for both exploratory data visualization and statistical gene set enrichment analysis. Because the distribution of these scores under the null of uncorrelated technical noise has an accurate gamma approximation, inference can be performed at both the population and single cell levels. As we demonstrate using both simulation studies and real data analyses, the VAM method provides superior classification accuracy at a lower computation cost relative to existing single sample gene set testing approaches.

Perbandingan Expanded Curb-65 Terhadap Curb-65 dan Psi Dalam Memprediksi Luaran Pasien Cap

2019 ◽  
Vol 4 (3) ◽  
pp. 608
Author(s):  
Suyastri Suyastri ◽  
Irvan Medison ◽  
Deddy Herman ◽  
Russilawati Russilawati
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Prospective Study ◽  
Pneumonia Severity Index ◽  
Severity Index ◽  
Accurate Method ◽  
P Value ◽  
Pneumonia Severity ◽  
Advantages And Disadvantages ◽  
Care Decision

<p><em>Tingkat keparahan CAP adalah poin penting pengambilan keputusan perawatan pasien. Beberapa metode telah digunakan untuk menilai tingkat keparahan pneumonia seperti Pneumonia Severity Index (PSI), CURB-65, SMART-COP dan Expanded CURB-65. Metode tersebut memiliki kelebihan dan kekurangan. Expanded CURB 65 diusulkan menjadi metode yang lebih akurat untuk mengevaluasi keparahan pneumonia dan memprediksi kematian pasien CAP. Tujuan penelitian ini memprediksi keakuratan Expanded CURB  65 dibandingkan CURB 65 dan PSI. Penelitian kohort prospektif pada pasien CAP yang dirawat di RSUP Dr. M.Djamil Padang dari April sampai Oktober 2019. Tingkat keparahan CAP pada pasien dinilai menggunakan PSI, CURB 65, Expanded CURB 65, kemudian hasilnya dievaluasi berdasarkan keparahan. Data dianalisis menggunakan regresi logistik dengan CI 95% dan nilai p &lt;0,05 dianggap signifikan. Hasil penelitian pada 90 pasien sebagian besar laki-laki usia 53 tahun dengan komorbiditas terbanyak keganasan. Uji Pearson Chi aquare menunjukkan tidak ada hubungan antara tingkat keparahan berdasarkan CURB 65 dan luaran pengobatan (CI 95%, nilai p = 0,104). Sementara, PSI dan Expanded CURB 65 memiliki hubungan yang signifikan antara tingkat keparahan dan luaran (CI 95%, p=0,081 dan CI 95%, p= 0,046, masing-masing). Analisis multivariat menemukan Expanded CURB 65 lebih akurat dalam memprediksi luaran pasien CAP rawat inap (kappa =0,108 dan AUC=0,422).</em></p><p><em><br /></em></p><p><em><em>Severity of CAP is very important for site care decision inpatients. Several methods have been used to assess the severity of pneumonia such as Pneumonia Severity Index (PSI), CURB-65, SMART-COP and Expanded CURB-65. Those methods have advantages and disadvantages. Expanded CURB 65 is proposed to be more accurate method for evaluating pneumonia severity and predicting mortality in CAP. The aim of this study was to investigate the accuracy of Expanded CURB 65 compare to CURB 65 and PSI. Cohort prospective study was conducted for CAP patients who were hospitalized at RSUP Dr. M.Djamil Padang from April to October 2019. Patients was assesed for severity using PSI, CURB 65, Expanded CURB 65, then we evaluated it’s outcome. The data were analyzed by logistic regression with CI 95% and p value &lt;0,05 considered as statistically significant. We found 90 patients that predominantly males with an average age of 53 years, and the most common comorbidity is malignancy. There was no relationship between pneumonia severity by CURB 65 and outcome (CI 95%, p=0.104). PSI and Expanded CURB 65 had significant relationship between severity and outcome (CI 95%, p=0.081and CI 95%, p=0.046, respectively). Multivariate analysis showed the expanded CURB 65 was more accurate for predicting the outcome of CAP inpatients (kappa=0.108 and AUC= 0.422).</em></em></p>

scholarly journals Gene set enrichment analysis for genome-wide DNA methylation data

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jovana Maksimovic ◽  
Alicia Oshlack ◽  
Belinda Phipson
Keyword(s):  
Dna Methylation ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Set Enrichment Analysis ◽  
Methylation Array ◽  
Gene Set ◽  
Genome Wide ◽  
Genome Methylation ◽  
Unbiased Gene ◽  
Gene Set Testing

AbstractDNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches, and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.

Abstract 392: The Plasma Proteome of Tangier Disease Patients Reveals Perturbations of Diabetic and Inflammatory Pathways

2016 ◽  
Vol 36 (suppl_1) ◽  
Author(s):  
James T McParland ◽  
Evanthia Pashos ◽  
Daniel J Rader ◽  
Marina Cuchel
Keyword(s):  
Inflammatory Response ◽  
Type Ii Diabetes ◽  
Enrichment Analysis ◽  
Nonparametric Test ◽  
Type Ii Diabetes Mellitus ◽  
Gene Set Enrichment Analysis ◽  
P Value ◽  
Type Ii ◽  
Tangier Disease ◽  
Inflammatory Pathways

Aim: The ATP-binding cassette transporter 1 (ABCA1) is a membrane protein well known for its role in cholesterol efflux and HDL formation. Recently, ABCA1 has been implicated as playing a key role in other processes, such as insulin secretion and inflammatory response. We sought to further investigate these potential roles through a quantitative proteomics approach. Specifically, we hypothesized that we could detect differential protein signatures in the plasma of Tangier patients that correspond to pathways involved in diabetes and inflammation. Methods: We used SOMAscan® technology (SomaLogic, Boulder, CO, USA) to analyze plasma collected from 5 Tangier disease patients (homozygotes or compound heterozygotes for functional ABCA1 mutations) and 7 normolipidemic controls. We tested for differences in the levels of approximately 1,000 plasma proteins using a nonparametric test (KS). We then performed Ingenuity Canonical Pathway analysis to examine if proteins linked to diabetes and inflammation pathways were significantly more likely to be differentially abundant in the plasma. We corroborated the results using Gene Set Enrichment Analysis (GSEA). Results: We found an enrichment in differentially abundant proteins involved in type II diabetes mellitus signaling (p-value=0.0002) and inflammatory pathways, such as granulocyte adhesion and diapedesis (p-value=2.2*10 -12 ). These results were also corroborated by GSEA, where gene sets corresponding to GO biological processes such as immune response (p-value=0.008) and inflammatory response (p-value=0.032) ranked at the top of the enrichment results. Conclusions: The results from this pilot study support the concept that ABCA1 is implicated in pathways affecting immune and inflammatory response and type II diabetes.

scholarly journals Determinants of COVID-19 Vaccine Acceptance in Six Lower- and Middle-Income Countries

2021 ◽  
Author(s):  
Adugna Kebede ◽  
Robert Kanwagi ◽  
Asrat Dibaba Tolossa ◽  
Md Abul Kalam ◽  
Thomas Davis ◽  
...  
Keyword(s):  
Perceived Risk ◽  
P Value ◽  
Negative Consequences ◽  
Vaccine Acceptance ◽  
Middle Income ◽  
Perceived Safety ◽  
Middle Income Countries ◽  
Advantages And Disadvantages ◽  
Vaccine Refusal ◽  
Behavioural Determinants

Abstract Background: While a vaccine is the only clinical preventive measure to control the infection and mortality caused by SARS-CoV-2 (COVID-19), delayed acceptance or refusal of COVID-19 vaccines may increase and prolong the threat to global public health and the economy. Identifying behavioural determinants is considered a critical step in explaining and addressing the barriers of vaccine refusal, but there is a lack of evidence around COVID-19 vaccine refusal and delay from a behavioural perspective. This study aims to identify the behavioural determinants of COVID-19 vaccine acceptance and provide recommendations to design actionable interventions to increase the uptake of the COVID-19 vaccine in six lower-and-middle income countries. Methods: Taking into consideration the Health Belief Model (HBM), Theory of Reasoned Action (TRA), and other behavioural models, a Barrier Analysis (BA) approach was employed to examine twelve potential behavioural determinants of vaccine acceptance in Bangladesh, India, Myanmar, Kenya, the Democratic Republic of Congo, and Tanzania. In all six countries, at least 45 interviews with those who intended to take the vaccine (“Acceptors”) and another 45 or more interviews with those who did not (“Non-Acceptors”) were conducted, totalling 542 interviews. Data analysis was performed to find statistically significant (a p-value of less than 0.05) differences between Acceptors and Non-acceptors and to identify which beliefs were most highly associated with acceptance and non-acceptance of the behaviour based on estimated relative risk (ERR). Results: The analysis showed that perceived social norms, perceived positive and negative consequences, perceived risk of getting COVID-19, perceived severity of COVID-19, trust in COVID-19 vaccines, perceived safety of COVID-19 vaccines, and expected access to COVID-19 vaccines had the highest association with COVID-19 vaccine acceptance in Bangladesh, Kenya, Tanzania, and DRC. Additional behavioural determinants found to be significant in both Myanmar and India were perceived self-efficacy, trust in COVID-19 information provided by leaders, perceived divine will, and perceived action efficacy of the COVID-19 vaccines. The study also identified important perceptions and beliefs around COVID-19 and its severity, advantages and disadvantages of being vaccinated, and action efficacy of the vaccine to control the spread of the virus. Conclusion: Many of the determinants found to be significant and their level of significance varied from country to country. National and local plans should include messages and activities that address the behavioural determinants found in this study in order to significantly increase the uptake of COVID-19 vaccine across these countries.

scholarly journals Formation and development of school biological education in modern Russia

2018 ◽  
Vol 7 (3) ◽  
pp. 339-343
Author(s):  
Aleksandr Alekseevich Semenov ◽  
Hirofumi Saito
Keyword(s):  
Secondary School ◽  
Inclusive Education ◽  
Extracurricular Activities ◽  
Further Education ◽  
Ecological Literacy ◽  
Biological Knowledge ◽  
Gifted Children ◽  
Physical And Mental Health ◽  
Advantages And Disadvantages ◽  
Biological Education

Russia inherited the Soviet system of science and education with its advantages and disadvantages from the Soviet Unio n period. In recent years it has experienced goals diversification as well as the content of school biological education changes. Primary school aimed propaedeutic of biological knowledge; secondary school aimed the basics of biological sciences development; secondary school at the basic level aimed the culture of knowledge of wildlife, natural-shaped and careful attitude development. The goal of the profile school is to generalize, deepen and expand biological knowledge. Moreover it is important to develop research skills and influence on the process of students proorientation in the world of biological professions. The content of biological education focuses on the problems of physical and mental health, healthy lifestyles and ecological literacy development. The authors notice that the construction and structure of the school biology course has changed. The concentric construction of the object makes it complete. A graduate of the basic secondary school receives a relatively complete biological education, which is necessary for his life and further education for professional self-determination. The biology course includes three sections: Living organisms, Human and his health and General biological regularities. The authors mention that secondary school children have Biology classes one hour less in comparison with the Soviet Unio n period. Both system-activity and student-centered approaches are the key approaches to teaching biology. They aim the subject results and universal learning activities development (personal, regulatory, communicative and cognitive). Moreover that is important to speak about the key competencies, education and socialization of students, the organization of their extracurricular activities, inclusive education and work with gifted children.

scholarly journals Evaluation of Delorme’s Procedure in the Treatment of Complete Rectal Prolapse- A Comparison with Abdominal Rectopexy (Well’s procedure)

2021 ◽  
Vol 34 (1) ◽  
pp. 40-46
Author(s):  
Md Ariful Alam Suman ◽  
Md Habibullah Sarkar ◽  
Istiak Ahmed ◽  
Sulatanul Abedin ◽  
Md Shohidul Islam ◽  
...  
Keyword(s):  
Rectal Prolapse ◽  
Hospital Stay ◽  
P Value ◽  
Complete Rectal Prolapse ◽  
Advantages And Disadvantages ◽  
Group I ◽  
Abdominal Rectopexy ◽  
Delorme’S Procedure ◽  
Group 2 ◽  
Delorme's Procedure

Background: There are versatile operative techniques for treating complete rectal prolapse. Every procedure has some advantages and disadvantages. Delorme’s procedure and abdominal rectopexy (Well’s procedure) have gained more popularity. But to determine which approach is better, it is needed to evaluate the functional outcome of both procedures. Objective: To compare the outcome of Delorme’s procedure and abdominal rectopexy to treat complete rectal prolapse. Methodology: A randomized control trial was conducted in 25 patients with complete rectal prolapse in the department of Surgery, RMCH. They were divided into two groups by randomization. Fifteen patients included in Group-I underwent Delorme’s procedure, and ten patients included in group-II underwent abdominal rectopexy (Well’s procedure). The outcome of both procedures was compared postoperatively.  Results: In group-1, we have found uneventful outcomes of 10 (66.66%) patients, and hemorrhage, minor incontinence, and retention of urine were found in 2(13.3%), 1(6.66), and 4(26.66%) patients, respectively. In group-2 patients, 5(50%) patients recovered uneventfully, whereas hemorrhage, surgical site infection, retention of urine, bladder dysfunction, and constipation were found in 2(20%), 1(10%), 1(10%), 1(10%) and 2(20%) patients respectively. The mean operation time in group-I was 92.86 min and in Group 2 was 124.00 min with a p-value of 0.001. The average post-operative hospital stay after Delorme’s procedure was <4 days in 4 patients and 4-6 days in the rest 11 patients. But the hospital stay is a little lengthier in the case of abdominal rectopexy (Well’s procedure), where seven patients were discharged within 4-6 days, and three patients were discharged after the 5th day of operation. In group I, expenditure was <7000 taka in 10 (66.66%) patients, whereas in group-2 , the cost was 10000-15000 in 7(70%) patients with a p-value of 0.001. Conclusion: We can conclude that Delorme’s procedure is comparatively safer and cost-effective than Well’s procedure, considering different vital parameters. TAJ 2021; 34: No-1: 40-46

scholarly journals Tissue-based metabolomics profiling reveals metabolic signatures and major metabolic pathways of gastric cancer

2021 ◽  
Author(s):  
Yaqin Wang ◽  
Wenchao Chen ◽  
Kun Li ◽  
Gang Wu ◽  
Wei Zhang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Predictive Ability ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Pentose Phosphate ◽  
P Value ◽  
Pathway Enrichment Analysis ◽  
Dodecanoic Acid ◽  
Orthogonal Projections ◽  
Latent Structures

Abstract Purpose This study was aimed to screen differential metabolites between gastric cancer (GC) and paracancerous (PC) tissues and find new biomarkers of GC. Methods GC (n = 28) and matched PC (n = 28) tissues were collected and LC-MS/MS analyses were performed to detect metabolites of GC and PC tissues in positive and negative models. Principal component analysis (PCA) and orthogonal projections to latent structures-discriminate analysis (OPLS-DA) were conducted to describe distribution of origin data and general separation and estimate the robustness and the predictive ability of our mode. Differential metabolites were screened based on criterion of variables with p value < 0.05 and VIP (variable importance in the projection) > 1.0. Receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic power of differential metabolites. Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed to search for metabolite pathways and MetaboAnalyst was used for pathway enrichment analysis. Results Several metabolites were significantly changed in GC group compared with PC group. Thirteen metabolites with high VIP were chose and among which 1-methylnicotinamide, dodecanoic acid and sphinganine possessed high AUC values (AUC > 0.8) indicating an excellent discriminatory ability on GC. Pathways such as pentose phosphate pathway and histidine metabolism were focused based on differential metabolites demonstrating their effects on progress of GC. Conclusions In conclusion, we investigated the tissue-based metabolomics profile of GC and several differential metabolites and signaling pathways were focused. Further study is needed to verify those results.

On “Field Significance” and the False Discovery Rate

2006 ◽  
Vol 45 (9) ◽  
pp. 1181-1189 ◽  
Author(s):  
D. S. Wilks
Keyword(s):  
False Discovery Rate ◽  
Statistical Power ◽  
Statistical Significance ◽  
Significance Test ◽  
P Value ◽  
Test Statistic ◽  
Global Test ◽  
Additional Advantage ◽  
Counting Procedure ◽  
False Discovery

Abstract The conventional approach to evaluating the joint statistical significance of multiple hypothesis tests (i.e., “field,” or “global,” significance) in meteorology and climatology is to count the number of individual (or “local”) tests yielding nominally significant results and then to judge the unusualness of this integer value in the context of the distribution of such counts that would occur if all local null hypotheses were true. The sensitivity (i.e., statistical power) of this approach is potentially compromised both by the discrete nature of the test statistic and by the fact that the approach ignores the confidence with which locally significant tests reject their null hypotheses. An alternative global test statistic that has neither of these problems is the minimum p value among all of the local tests. Evaluation of field significance using the minimum local p value as the global test statistic, which is also known as the Walker test, has strong connections to the joint evaluation of multiple tests in a way that controls the “false discovery rate” (FDR, or the expected fraction of local null hypothesis rejections that are incorrect). In particular, using the minimum local p value to evaluate field significance at a level αglobal is nearly equivalent to the slightly more powerful global test based on the FDR criterion. An additional advantage shared by Walker’s test and the FDR approach is that both are robust to spatial dependence within the field of tests. The FDR method not only provides a more broadly applicable and generally more powerful field significance test than the conventional counting procedure but also allows better identification of locations with significant differences, because fewer than αglobal × 100% (on average) of apparently significant local tests will have resulted from local null hypotheses that are true.

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