> For the complete documentation index, see [llms.txt](https://help.bioinsight.illumina.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.bioinsight.illumina.com/icm/analyses/analysis-functionality/task-menu/biological-interpretation/correlation-engine-bioset-correlation.md). # Correlation Engine bioset correlation ## What is Correlation Engine bioset correlation? While Correlation Engine (CE) meta-analysis answers "does my signature replicate across studies?", bioset correlation answers a complementary question: "which specific studies show the strongest pairwise concordance with my signature?". The output of this task produces granular, study-level evidence for your findings by computing pairwise correlation scores between the gene/protein signature and CE's 201K+ public biosets. {% hint style="warning" %} Connected Multiomics V1.3 uses the Disease atlas Biosets from CE. Future release versions will include additional public Biosets and private Bioset libraries. {% endhint %} ## Performing the CE bioset correlation task * Single-click any gene/protein signature from these types of result nodes: differential analysis results (feature lists), QTL hits, MOFA factor loadings, SNF cluster markers, WGCNA module genes, or manually curated gene lists * In the context-sensitive toolbox select **Biological interpretation** > **Correlation Engine bioset correlation**

Select the **Correlation Engine bioset correlation** task from the toolbox

* Select the **Organism** using the drop-down or begin typing the name * Select the **Correlation Engine project** or choose Other to enter a custom project name * Enter a **Correlation Engine study name** that will be created for the analysis within the selected project * Click **Next**

* **Select one or more contrasts** to use for Correlation Engine analysis. If multiple contrasts are selected, an analysis will be performed for each contrast and an enrichment table will be produced for each contrast * **Select feature identifier** by choosing the column that contains the gene identifiers to use for the analysis * Click **Next**

* Choose which atlas to determine study correlation against * (Optional) Choose to filter the results by organism or data type * Leave **Filter by organism** and **Filter by data type** unchecked to include all organisms and data types in the results. * Click **Finish**

Result configuration for the task. Leave all filters unchecked to include all organisms and data types in the results

The task produces a Correlation Engine meta analysis results node (circle).

## Viewing the Correlation Engine bioset correlation results * Double-click to open the Correlation Engine bioset correlation task report

Correlation Engine bioset correlation report

{% hint style="warning" %} In the above image, study 4692148 shows up 3 times, because there are 3 biosets each with their own score against the query. There are some biosets from other studies that intermingle in the ranks. Study 4692148 get's a score = 100 because that is the best score of any of its biosets and that score is the best of all. {% endhint %} The table can be **downloaded** by clicking

. The report list includes studies rank ordered by the strongest **Bioset score**. The columns can be **sorted** and **filtered** using text and operators such as >= or <= in the numeric columns. Clicking a **Bioset ID** will take you to the Bioset in Correlation Engine and clicking a **Study ID** will take you to the study in CE. Illumina has developed the *Running Fisher* algorithm for CE use. See more details in our technical note: [Data Correlation Details: Enrichment Analysis](https://www.illumina.com/content/dam/illumina-marketing/documents/products/technotes/technote-data-correlation-enrichment.pdf) **P-value** is the bioset-bioset *Running Fisher* p-value **Correlation direction** is the overall direction of the majority of genes as either positive/up or negative/down The results can be viewed in the Data viewer by clicking

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