Qlucore Omics Explorer is an easy to use software program well suited for analysis of DNA methylation data.
Qlucore Omics Explorer is a D.I.Y next-generation bioinformatics software for research in life science, biotech, food and plant industries, as well as academia. The powerful visualization-based data analysis tool with inbuilt powerful statistics delivers immediate results and provides instant exploration and visualization of big data.
Analyze DNA methylation data
DNA methylation is a type of chemical modification of DNA that can be inherited and subsequently removed without changing the original DNA sequence. As such, it is part of the epigenetic code and is also the best characterized epigenetic mechanism. Research has shown that DNA methylation is manifested in a number of important biological processes and human diseases including cancer. The program is well suited as well for analysis of Illumina DNA methylation and cancer data.
In Qlucore Omics Explorer a number of different analyses can be done.
- Check data for outliers by visual inspection using sample Principal Component Analysis (PCA) plots.
- Perform statistical filtering using ANOVA to enhance results. Unwanted dependencies can be removed with one mouse click.
- Generate a list of genes that classifies data based on a selection of statistical tests: f-test, t-tests or regression.
- Present results using for instance heatmaps or PCA plots.
Using Qlucore in epigenetics research studies
A range of samples including DNA from patient blood, primary tissue from tumors, and cell lines, are studied.Read more
RNA-Seq analysis using Qlucore
Performing gene expression analysis based on RNA sequencing data, in Dilated Cardiomyopathy studies.Read more
Analysis of public data using Qlucore
This case study is an example of how the use of public information from multiple sources was used to propose a new classification for glioma cancer.Read more
Interpreting Leukemia proteomics with Qlucore
In this case study Qlucore Omics Explorer is used to generate new ideas and hypotheses through exploration and analysis of proteomics data.Read more