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Causality inference
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Observational study investigated the association between pernicious anemia (PA) and cancers. However, with the exception of gastric cancer, the results are mostly contradictory. The purpose of this study was to investigate the potential causal relationship between PA and cancers through bidirectional two-sample Mendelian randomized (MR) analysis.
9p
vishanshan
27-06-2024
3
1
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Previous studies have observed a link between immunophenotypes and lung cancer, both of which are closely associated with genetic factors. However, the causal relationship between them remains unclear
9p
vikoch
27-06-2024
1
1
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Coronary artery disease (CAD) remains the leading cause of mortality worldwide despite enormous efforts devoted to its prevention and treatment. While many genetic loci have been identified to associate with CAD, the intermediate causal risk factors and etiology have not been fully understood. This study assesses the causal effects of 37 heritable clinical factors on CAD in East Asian and European populations.
15p
viellison
28-03-2024
5
2
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There has been a growing appreciation recently that mutagenic processes can be studied through the lenses of mutational signatures, which represent characteristic mutation patterns attributed to individual mutagens.
15p
vicwell
29-02-2024
7
1
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Demonstrate how observational causal inference methods can generate insights into the impact of chronic disease combinations on patients’ 30-day hospital readmissions. Multi-hypothesis causal analysis, a new methodological tool, generates meaningful insights from health care claims data, guiding the design of care and intervention programs.
9p
visteverogers
24-06-2023
5
2
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To compare the original synthetic control (OSC) method with alternative approaches (Generalized [GSC], Micro [MSC], and Bayesian [BSC] synthetic control methods) and re-evaluate the impact of a significant restructuring of urgent and emergency care in Northeast England, which included the opening of the UK's first purpose-built specialist emergency care hospital.
13p
vigamora
25-05-2023
8
2
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Many QTL studies have two common features: (1) often there is missing marker information, (2) among many markers involved in the biological process only a few are causal. In statistics, the second issue falls under the headings “sparsity” and “causal inference”.
19p
vinarcissa
21-03-2023
2
1
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Increasingly available multilayered omics data on large populations has opened exciting analytic opportunities and posed unique challenges to robust estimation of causal effects in the setting of complex disease phenotypes.
7p
vihagrid
30-01-2023
7
3
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Biological pathways play an important role in the occurrence, development and recovery of complex diseases, such as cancers, which are multifactorial complex diseases that are generally caused by mutation of multiple genes or dysregulation of pathways.
12p
vihagrid
30-01-2023
6
3
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Rates of preterm birth are substantial with significant inequalities. Understanding the role of risk factors on the pathway from maternal socioeconomic status (SES) to preterm birth can help inform interventions and policy. This study therefore aimed to identify mediators of the relationship between maternal SES and preterm birth, assess the strength of evidence, and evaluate the quality of methods used to assess mediation.
20p
viferrari
28-11-2022
8
2
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Longitudinal studies are crucial for discovering causal relationships between the microbiome and human disease. We present MITRE, the Microbiome Interpretable Temporal Rule Engine, a supervised machine learning method for microbiome time-series analysis that infers human-interpretable rules linking changes in abundance of clades of microbes over time windows to binary descriptions of host status, such as the presence/absence of disease.
15p
vielonmusk
30-01-2022
13
0
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Finding a causal gene is a fundamental problem in genomic medicine. We present a causal inference framework, CoCoA-diff, that prioritizes disease genes by adjusting confounders without prior knowledge of control variables in single-cell RNA-seq data.
23p
viarchimedes
26-01-2022
17
0
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DNA methylation is a key epigenetic modification in human development and disease, yet there is limited understanding of its highly coordinated regulation. Here, we identify 818 genes that affect DNA methylation patterns in blood using large-scale population genomics data.
24p
viarchimedes
26-01-2022
7
1
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We propose a new computational framework, probabilistic transcriptome-wide association study (PTWAS), to investigate causal relationships between gene expressions and complex traits. PTWAS applies the established principles from instrumental variables analysis and takes advantage of probabilistic eQTL annotations to delineate and tackle the unique challenges arising in TWAS.
26p
viarchimedes
26-01-2022
13
0
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In recent years, many methods have been developed for discovering causal relationships from observed data. However, as an important kind of causes existing in many causal systems, combined causes (e.g. multi-factor causes consisting of two or more component variables that individually might not be a cause) have not received enough attention.
13p
guernsey
28-12-2021
12
0
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Age-adjusted US total pediatric cancer incidence rates (TPCIR) rose 49% 1975–2015 for unknown reasons. Prenatal cannabis exposure has been linked with several pediatric cancers which together comprise the majority of pediatric cancer types. We investigated whether cannabis use was related spatiotemporally and causally to TPCIR.
33p
vianrose2711
27-04-2021
13
1
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The literature has suggested that financial development and electricity consumption are key determinants of economic growth. However, existing studies usually was applied the frequentist inference, which is an outdated estimator. By applying the Bayesian approach via the Metropolis-Hasting and Gibbs samplers as the MCMC methods, the study aims to re-examine the impact of financial development and electricity consumption on economic growth in ASEAN+6 countries from 1980 to 2016.
8p
caygaocaolon11
18-04-2021
16
2
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The issue of causation is one of the major challenges for epidemiologists who aim to understand the association between an exposure and an outcome to explain disease patterns and potentially provide a basis for intervention. Suitably designed experimental studies can offer robust evidence of the causal relationships. The experimental studies, however, are not popular, difficult or even unethical and impossible to conduct; it would be desirable if there is a methodology for reducing bias or strengthening the causal inferences drawn from observational studies.
5p
nguyenmyhuyen90
04-03-2021
15
2
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Finding the relationship between two quantitative variables without being able to infer causal relationships Correlation is a statistical technique used to determine the degree to which two variables are related. In this chapter provides knowledge of correlation & regression.
53p
larachdumlanat124
28-11-2020
8
0
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Knockdown or overexpression of genes is widely used to identify genes that play important roles in many aspects of cellular functions and phenotypes. Because next-generation sequencing generates high-throughput data that allow us to detect genes, it is important to identify genes that drive functional and phenotypic changes of cells.
14p
vikentucky2711
26-11-2020
5
0
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