Multiomics offers a holistic view of biology

Integrating methods for deeper insights and discoveries

What is multiomics?

Multiomics (multiple omics) provides an integrated approach to power discovery across multiple levels of biology. By combining data from genomics, transcriptomics, epigenetics, and proteomics, researchers can achieve a more comprehensive understanding of molecular changes contributing to normal development, cellular response, and disease.

Multiomics can also combine separate omic data from past experiments, known as in-silico multiomics, to efficiently analyze novel biological relationships. Regardless of the method chosen, Illumina offers solutions powered by NGS to enable your next multiomics studies and analyses.

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Multiomics is revolutionizing research

Learn why these research leaders decided to use multiomics in their work.

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Multiomics multiplies your discovery power

See how you can use multiomics to better connect genotype to phenotype and obtain a full cellular readout not found through single omics approaches.

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Expand your research across multiple omes


Focus on the structure, function, evolution, mapping, and editing of information coded within an organism’s DNA.


Study the complete set of RNA transcripts produced by the genome.


Evaluate protein expression for a better understanding of cellular function and prediction of therapeutic responses.


Examine heritable changes in gene expression activity caused by factors other than DNA changes.

Leveraging bulk to targeted methodologies for more powerful discoveries

Perform multiomic experiments using NGS-based solutions to find novel links between biological entities, identify biomarkers, profile mutations and other phenotypes, and improve discovery of new therapies. Illumina offers comprehensive solutions across biological resolutions from broad bulk analysis to targeted single cells. For more details, visit our multiomic methods comparison guide.

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Comprehensively analyze bulk cell populations or tissue sections

Explore how pooling cells or tissue populations can be used to analyze protein and transcriptional activity within a single workflow using bulk epitope and nucleic acid sequencing (BEN-Seq).

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Achieve high resolution data with single-cell analysis

Measure gene regulatory networks and gain insights into cell heterogeneity by combining transcriptomics and epigenomics in a singular molecular readout using ATAC-Seq found in this technical note.

See how cellular indexing of transcriptomes and epitopes sequencing (CITE-Seq) can provide proteomic and transcriptomic data in a single run powered by NGS.

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Spatially map transcriptional activity in tissues

Learn key benefits of spatial transcriptomics, which localizes gene expression within intact tissues for a better understanding of structure and activity.

Simplify analysis for multiomic interpretation and insight

Following sequencing, data analysis provides the key step to allow biological interpretation of samples. In general, the multiomics data analysis pipeline consists of three phases, with available software for each step. The approach used will depend on the research objective and the omes you are studying.

Primary Analysis

Also referred to as base calling, primary analysis coverts data into base sequences (A, T, C, or G) as a raw data file in binary base call (BCL) format and is performed automatically on Illumina sequencers.

Secondary Analysis

The BCL sequence file format requires conversion to FASTQ format for use with Illumina, user-developed, or third-party secondary analysis tools. Illumina DRAGEN Secondary Analysis features tools for every step of most secondary analysis pipelines.

Tertiary Analysis

Correlation Engine is an interactive knowledge base where users can put their private multiomic data into biological context with highly curated public multiomic data.

Make more discoveries with the NovaSeq X Series and 25B Flow Cell

Step up your multiomics research with the NovaSeq X Series combined with the 25B Flow Cell. Achieve high-quality data with low-cost workflows to accelerate and broaden your research.​

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Additional Resources

Advancing cancer research with multiomics

Learn how researchers at the Ontario Institute for Cancer Research and United Health Network are linking the causes and consequences of complex phenotypes through multiomics to enable discoveries that weren’t possible before.

Success with single-cell multiomics

Leading experts in single-cell multiomics share their successful experiences using multiomics as well as how they overcame challenges and visualized data.

Multiomics with NGS-based proteomics

Explore how multiomics can now include proteomics using NGS-powered solutions from Illumina.