Multi-Omic Data Requirements

Panome Bio offers integrated multi-omics analysis of data generated through our Next-Generation Metabolomics™ or proteomics workflows or existing customer-provided data.

Omic Supported Processed vs Raw
Metabolomics Y Either
Proteomics Y Either
Transcriptomics Y Processed (abundance, p-value)
Genomics Y Processed (variants called)

Considerations for Study Design

  • Multi-omic integration can occur both within and across sample sets. The more closely related the samples in your multi-omic analysis are, the more tightly your data sets are expected to be corelated. For example, the data from parallel metabolomic and proteomic analysis of aliquoted serum or tissue samples will integrate tightly.
  • In some situations an orthogonal sample type may provide valuable data, such as paired serum-tissue from the same organism.
  • As more analytes will be measured in a multi-omics experiments, greater sample numbers are required for sufficient statistical power. This is especially important for projects requiring data concatenation approaches.
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