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CLRNASeq for RNA-Seq Analysis
CLRNASeq is a robust standalone software (Windows and MAC based) developed specifically for discovering, profiling and quantifying RNA transcripts. With an intuitive interface and point and click menu options, users are given the power to run differential gene expression, metabolic pathway analyses and more instantaneously
Key Features of CLRNASeq
  • Intuitive point and click interface empowering researchers to easily perform complex analyses on their computer without the need to rely on bioinformatics specialists or a dedicated infrastructure
  • Perform differential gene expression analysis between any two selected samples (DEG Browser)
  • Identify key metabolic pathways and functional categories of two differentially expressed RNA-Seq samples through the KEGG, eggNOG and gene ontology browsers
  • Point, click and create highly sophisticated and publication ready charts, graphs and statistical tables
  • Export raw sequence data and pertinent statistics as excel, text or FASTA files for further downstream analyses
Watch a video demo of CLRNASeq™ Main Browser

The main browser lists all the genes in the reference genome, and with a quick glance at the heat map users can check expression levels across various samples. Set other filters such as expression level, functional category or gene ontology to focus in on genes of interest
Differentially Expressed Gene (DEG) Browser

The user friendly DEG browser uses the TMM and RLE statistical methods to determine differentially expressed genes between two samples. Point, click and set p-value thresholds to filter in on genes that are differentially expressed at a higher confidence level.
Mapping Browser

The mapping browser allows users to visually compare transcript gene expression patterns across multiple samples mapped to a reference genome. Easily browse annotated information for each gene based on the KEGG and eggNOG databases.
Expression Profile Browser

In addition to RPKM, also browse expression levels normalized using TMM and RLE algorithms.
KEGG Browser

With the KEGG database directly embedded in CLRNASeq™, our interactive browser enables you to perform metabolic pathway analysis with one click. Easily find metabolic pathways that are differentially expressed between two RNA samples of your choice, then set more stringent p-value thresholds to reduce false discoveries.
eggNOG Browser

The eggNOG browser allows you to find differentially expressed functional categories between any two RNA samples, based on the eggNOG database. CLRNASeq automatically identifies active and inactive functional categories with the click of a button.
Clustering Browser

The clustering browser allows you to easily group genes with similar expression patterns using three of the most popular clustering algorithms, hierarchical, K-means, SOM.

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Data generated by ChunLab is for research purposes only. It is not intended for diagnostic use.
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