Clariom Assays for Fast Transcriptome Profiling

Although critical to impactful expression studies, analysis and interpretation of transcriptomic data to identify RNA biomarkers—especially from deep RNA-seq approaches—can be one of the biggest challenges to finding answers. Progress can be slow, resulting in extra time, money, and bioinformatics resources spent just to crunch data.  Applied Biosystems Clariom microarray solutions are built on the latest transcriptome knowledge to accelerate RNA biomarker discovery even from challenging samples and without the need for specialized bioinformatics skills.

• Free, simple, and quick data analysis—Transcriptome Analysis Console (TAC) Software easily analyzes transcriptomic data from all of our Clariom assays, quickly and at no additional cost.
• Deep and broad transcriptome analysis—Clariom D assays enable rapid discovery of coding and long non-coding genes, exons, splice variants, and rare transcripts.
• Simple and swift discovery—Clariom S assays provide easy identification of gene-level signatures and pathways from well-annotated genes.
• Robust expression results from challenging samples—Reagents are available for analysis of as little as 100 pg input RNA, FFPE tissue, and whole blood.

Request software demo         Request transcriptome profiling project costs

Don’t wait for answers

Take data analysis into your own hands and reduce the amount of time you spend waiting for results.  Free of charge TAC Software, provided with Clariom assays, is designed for the biologist and allows you to go from raw data to insights in minutes.

• Data QC to pathway analysis in a few clicks
• User-friendly, dynamic, and powerful  tools to analyze complex experimental designs and splicing events
• mRNA–miRNA interaction visualizations and exploration in a single software

Let us show you just how quickly you can get answers by requesting a short software demo.

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1. Generate robust data from large numbers of challenging samples.

Clariom Pico assays produce highly reproducible transcriptome-wide data from as little as 100 pg total RNA, and with TAC Software you can process complex data sets with over 1000 samples. 

• Clariom D and Clariom S Arrays are available in single sample cartridges
• Clariom S Arrays are also available in multi-sample array plates

Analysis setup wizard

2. Set up your analysis approach.

Import raw data from your Clariom assay experiment and select the type of expression analysis you want to perform.

• Gene- or exon-level expression, or both
• Choose from multiple analysis parameters or let the software choose for you

Signal box plot

3. Check your experiment worked.

QC your data with simple pass/fail tables and graphs.

• Standard QC metrics in dynamic visualization tools
• Positive vs negative AUC plots
• PCA plots
• Signal box plots

Sample comparison setup wizard

4. Compare samples in multiple ways.

Set up multiple levels of analysis and multi-way comparisons.

• Simple natural-language comparison setup wizard
• Assign sample attributes to analyze the data in different ways

Venn diagram

5. Find out how many genes have been differentially expressed.

Assess the number of genes that have been up- and down-regulated and what is causing the differential expression.

• Global data summarization reports
• Gene lists and Venn diagrams
• Sources of variation graphs 

Hierarchical cluster

6. Explore which genes have changed.

Quickly drill down to explore key genes, transcripts, or exons that have significantly changed using interactive and dynamic tables and graphs.

• Scatter plots
• Volcano plots
• Chromosomal views
• Hierarchical clustering

Table and scatter plot dynamically linked to show specific genes after filtering to select a particular pathway

7. Concentrate on genes and pathways of interest.

Simply filter out the data you do not want to see and focus on those of most value to you.

• Comprehensive and customizable filters
• Pick out genes and pathways based on your annotation criteria

Pathway analysis with WikiPathways integration

8. Understand which pathways have been impacted.

Take a broader view and understand how and which biological pathways have been significantly differentially expressed across the transcriptome.

• Data analysis through WikiPathways integration

mRNA-miRNA interaction network

9. Explore the effect of miRNA expression on mRNA.

Go beyond gene expression and explore the role of gene regulation by combining Clariom assay data with GeneChip miRNA 4.0 Assay expression data.

• miRNA-mRNA interaction network visualizations