Bioinformatic software miRNA analysis

Using instant visualization you can analyze miRNA data faster and more easily.

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 fast and interactive visualization-based data analysis tool with inbuilt powerful statistics delivers immediate results and provides instant exploration and visualization of a wide range of omics data including miRNA.


miRNA Analysis

miRNA (also written microRNA or µRNA) are non-coding RNA that are not translated into proteins. Instead they normally control the translation of mRNA. Profiling miRNA levels using microarrays is becoming a widely used technique.

With Qlucore Omics Explorer, a researcher can easily examine and analyze data from miRNA (microRNA) experiments. Data can be generated either by microarrays or for instance by RNA-seq and NGS techniques.

Key functionalities:

  • Check data for outliers by visual inspection using sample Principal Component Analysis (PCA) plots.
  • Perform statistical analysis using ANOVA.
  • Remove unwanted factors (batches) with a single mouse click.
  • Use hierarchical clustering or PCA to indentify subgroups.
  • Generate a list of miRNA that classifies data based on a selection of statistical tests: F-test, t-tests or regression.
  • Work with variable PCA plots to find correlation and networks among selected miRNA.

Does it work on my data?

Answer the four quick questions below and find out if you can use Qlucore on your data. 

For more details about supported data formats and data import see Data Import or Contact us with questions.

Case studies

Using Qlucore in epigenetics research studies

Cancer Genetics Program at the Hospital for Sick Children (SickKids) in Toronto, Canada.

A range of samples including DNA from patient blood, primary tissue from tumors, and cell lines, are studied.

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Analysis of public data using Qlucore

Beijing Normal University, China

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.

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RNA-seq case study

RNA-Seq analysis using Qlucore

Stanford University, US

Performing gene expression analysis based on RNA sequencing data, in Dilated Cardiomyopathy studies.

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Interpreting Leukemia proteomics with Qlucore

UT MD Anderson Cancer Center in Houston, Texas, US

In this case study Qlucore Omics Explorer is used to generate new ideas and hypotheses through exploration and analysis of proteomics data.

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Short introduction video

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