# Correlation analysis * [What is Correlation analysis?](#what-is-correlation-analysis) * [Running Correlation analysis](#running-correlation-analysis) * [Feature many-to-one correlation](#feature-many-to-one-correlation) * [Correlation analysis advanced options](#correlation-analysis-advanced-options) * [Correlation across assays](#correlation-across-assays) * [Correlation across assays analysis options](#correlation-across-assays-analysis-options) ## What is Correlation analysis? *Correlation analysis* is a statistical test that lets you rank features by their correlation with numeric attributes using Pearson (linear), Spearman (rank), or Kendall (tau) correlation. ## Running Correlation analysis We recommend normalizing you data prior to running *Correlation analysis*, but it can be invoked on any counts data node. * Click the counts data node * Click the **Statistics** section in the toolbox * Click **Correlation** * Choose the method to use for correlation analysis (Figure 1)

Figure 1. Choose the method to use for correlation analysis

## Feature many-to-one correlation When multiple numeric factors are added, the correlation analysis will perform each factor with a feature in the data node independently. If you are interested in particular features, use the **Search features** box to add one or more. * Select the factors and interactions to include in the statistical test (Figure 2).

Figure 2. Select the factors and interactions to include

* Click **Next** * It is optional to apply a lowest coverage filter or configure the advanced settings * Click **Finish** to run *Correlation analysis* produces a *Correlation* data node; double-click to open the task report (Figure 3) which is similar to the [ANOVA/LIMMA-trend/LIMMA-voom](/partek-flow/user-manual/task-menu/differential-analysis/anova-limma-trend-limma-voom.md) and [GSA](/partek-flow/user-manual/task-menu/differential-analysis/gsa.md) task reports and includes a table with features on rows and statistical results on columns.

Figure 3. Correlation analysis task report

Each numeric attribute includes p-value, adjusted p-value columns (FDR step up and/or Storey q-value if included), and a partial correlation value. Each interaction will have p-value and adjusted p-value columns (FDR step up and/or Storey q-value if included). Each feature includes ![](/files/iLAkSnsHkGwPSKOi6Kzq) [chromosome view](https://github.com/illumina-swi/partek-docs/blob/main/docs/partek-flow/user-manual/task-menu/visualizations/chromosome-view/chromosome-view.md), ![](/files/9paWCc6zuaScP0wveuZe) [dot plot](https://github.com/illumina-swi/partek-docs/blob/main/docs/partek-flow/user-manual/task-menu/visualizations/dot-plot.md), ![](/files/8qm0VxNRwFXSDitcgf7a) [correlation plot](https://github.com/illumina-swi/partek-docs/blob/main/docs/partek-flow/user-manual/task-menu/visualizations/correlation-plot.md), and extra details ![](/files/t7uxCXYXazTD4uKk6yFK) buttons in the *View* column. ### Correlation analysis advanced options #### Low value filter *Low-value filter* allows you to specify criteria to exclude features that do not meet the requirements for the calculation. If there is a filter feature task performed in the upstream analysis, the default of this filter is set to **None**, otherwise, the default is **Lowest average coverage** is set to **1**. *Lowest average coverage*: the computation will exclude a feature if its geometric mean across all samples is below the specified value *Lowest maximum coverage*: the computation will exclude a feature if its maximum across all samples is below the specified value *Minimum coverage*: the computation will exclude a feature if its sum across all samples is below the specified value *None*: include all features in the computation #### Multiple test correction Multiple test correction can be performed on the p-values of each comparison, with **FDR step-up** being the default. If you check the *Storey q-value*, an extra column with q-values will be added to the report. #### Use only reliable estimation results There are situations when a model estimation procedure does not fail outright but still encounters some difficulties. In this case, it can even generate p-value and fold change on the comparisons, but they are not reliable, i.e. they can be misleading. Therefore, the default of *Use only reliable estimation results* is set **Yes**. #### Correlation type Sets the type of correlation used to calculate the correlation coefficient and p-value. Options are *Pearson (linear)*, *Spearman (rank)*, *Kendall (tau)*. Default is **Pearson (linear)**. ## Correlation across assays *Correlation across assays* should be used to perform correlation analysis across different modalities (e.g. ATAC-Seq enriched regions vs. RNA-Seq expression) for multiomics data analysis. * Select the data node to be compared to the node that the task has been invoked from using the **Select data node** button * Modify any parameters (Figure 4) * Click **Finish**

Figure 4. Correlation across assays can be performed with multiomic data

### Correlation across assays analysis options #### Correlation and similarity measures *Features within same chromosome*: this option will restrict feature comparison to the chromosome location *All features in one data node vs all features in the other data node*: this option will perform the comparison using all combinations without location constraint *Pearson*: linear correlation: ![](/files/6nbDZm7u7ZAiNXfQPsjz) *Spearman*: rank correlation: ![](/files/80lVkYg0buo8kpgtBpRJ) #### Report correlation pairs *P-value*: select a cut-off value for significance and only those pairs that meet the criteria will be reported *abs(Correlation coefficient)*: select a cutoff for reporting the absolute value of the correlation coefficient (represented by the symbol r) where a perfect relationship is 1 and no relationship is 0 *Correlation across assays* produces a *Correlation pair list* data node; double-click to open the table (Figure 5). The table can be sorted and filtered using the column titles.

Figure 5. Correlation across assays table

Click ![](/files/K1KOynDtv2QObBwKWbMK) *View correlation plot* to open the correlation plot for each comparison. Scroll to the bottom of the table to ![](/files/KRiLAUoypMFHnfT8Iile) download the full table report. ## Additional Assistance If you need additional assistance, please visit [our support page](http://www.partek.com/support) to submit a help ticket or find phone numbers for regional support. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://help.partek.illumina.com/partek-flow/user-manual/task-menu/correlation/correlation-analysis.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.