CD Genomics is able to use directed acyclic graph analysis services for medical and clinical research to help customers identify confounders and sources of bias.
Introduction of Directed Acyclic Graph (DAG)Analysis Service
A directed acyclic graph is a directed graph with no loops in the graph. It consists of nodes and connections between nodes with one-way arrows. Because directed acyclic graphs can describe preference or dependency relationships in a natural way, they are widely used in bioinformatics analysis. A directed acyclic graph is a theory-driven method for screening independent variables, which constructs causal networks based on theoretical causal relationships. Arrows are used to represent causal relationships, with arrows emitting objects as causes and arrows pointing to outcomes.
Figure 1. Directed acyclic graph (DAG) model of hospital-acquired venous thromboembolism (HA-VTE) in children. (Campos LR, et al., 2020)
Applications
A directed acyclic graph illustrates a specific set of assumptions that may be incorrect and can help provide an opportunity for customers to decide which potential impacts to take into account. Our researchers rely on the visual presentation of a directed acyclic graph to help customers infer which variables need to be controlled for in the statistical analysis and which variables may cause additional bias when controlled for in the analysis.
Directed Acyclic Graph (DAG)Analysis Content
- The mediating variables, confounding variables, and correlation variables are all factors to be considered when constructing the directed acyclic graph.
- The principle of independent variable screening based on directed acyclic graph theory is that intermediate variables cannot be included and confounding factors must be included.
- Topological sorting. The process of constructing a topological sequence for a directed graph becomes topological ordering. Topological sorting is often used to "sort" tasks with dependencies.
We are able to use directed acyclic graph (DAG)analysis services to help our customers achieve high throughput data analysis in multi-omics. For questions about analysis content, project cycle, and pricing, please click online inquiry.
How It Works
CD Genomics is a professional bioinformatics service provider with years of experience in NGS and long-read sequencing (PacBio SMRT and Oxford Nanopore platforms) data, proteomics and metabolomics data analysis, integrated analysis services, database construction, and other bioinformatics solutions.
CD Genomics has professional bioinformatics experts who have successfully provided directed acyclic graph (DAG)analysis services to researchers in many different fields. Our professional skills and enthusiasm will provide you with high-quality analysis services. If you are interested in our services, please contact us for more details.
Reference
- Campos LR, et al. Risk factors for the development of hospital-acquired pediatric venous thromboembolism-Dealing with potentially causal and confounding risk factors using a directed acyclic graph (DAG) analysis. PLoS One. 2020 Nov 13; 15(11): e0242311.
