> For the complete documentation index, see [llms.txt](https://shivom.gitbook.io/documentation/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://shivom.gitbook.io/documentation/pipelines/genetic-correlation.md).

# Genetic Correlation

## Genetic correlation and heritability

A **genetic correlation** is the proportion of variance that two traits share due to genetic causes, the correlation between the genetic influences on a trait and the genetic influences on a different trait estimating the degree of pleiotropy or causal overlap.\
**Heritability** is a measure of how well differences in people’s genes account for differences in their traits.\
The tool chosen is **LDSC** (<https://github.com/bulik/ldsc>), a command-line tool for estimating heritability and genetic correlation from GWAS summary statistics.

### Workflow

Estimation of genetic correlation in European GWAS by utilizing pre-computed LD Scores.

**LDSC** performs:

1. LD Score regression intercept for a 1st GWAS Summary Statistics;
2. SNP-heritability for 1st Summary Statistics;
3. Genetic correlation between 1st and subsequent Summary Statistics.

#### User Journey

A few simple steps are needed to run this pipeline:

1. select *Genetic Correlation pipeline* from Pipelines section;
2. upload your input files;
3. provide other parameters for the genetic correlation and the job name and finally runs the analysis;

then, you will be redirected to the results page.

![](/files/-MDz9dNZhPrTvfZ6JDaz)

The first thing to do is to load your **Summary statistics Files**, which can be:

1. GWAS Summary Statistics files;
2. European GWAS pre-computed LD scores;
3. SNP-list of alleles;
4. Sample sizes for each Summary Statistics;
5. Sample and Population Prevalence for stratification of summary stats along with genetic and heritability intercept for regression calculations.

Let's take a look at the **parameters**:

* **Number of Samples**: Total no. of sample size (cases+control) for each summary statistics file provided;&#x20;
* **Phenotype**: Phenotype name of the summary stats trait;
* **Sample Prevalence**: Value used for sample stratification respective to summary statistics; *optional, default: NULL;*
* **Population Prevalence**: Value used for population stratification respective to summary statistics; *optional, default: NULL;*
* **Intercept**: Value used for genetic covariance regression respective to summary statistics; *optional, default: NULL;*
* **h2\_intercept**: Value used for heritability regression respective to summary statistics; *optional, default: NULL;*

![](/files/-MDz9y6rSabgKv983Vcc)

* **LDScore**: Pre-calculated LDScore for 1000 European genome; *input value to be chosen from Dropdown menu with default values;*
* **SNP**: Whole Genome reference SNPs;
* **Use-Intercept**: User input switch to use no-intercept parameter for calculating genetic correlation in LDSC function; *optional, default: switch on.*

![](/files/-MDzA1Di7ETBBRK72ztM)

### Results

Once you have chosen the pipeline to be used, uploaded the data file and set all the parameters, you can start your analysis using the *Run Analysis* box; at this point, you will be redirected to the *Dashboard*, where you can keep an eye on which works are *In Progress*, which are *Completed*, and choose to carry out a new analysis.&#x20;

![](/files/-ME3S3HQbJfzDdiKFdRV)

By clicking on your *JobName*, you will have access to a page where you can monitor all the processes involved in your analysis.

![](/files/-ME3Rj_M3uekxa18wcRx)

Now, selecting the *Results* box on the right, let's take a look at the demo results obtained using the Default Parameters Set:

**Correlation plot** is generated indicating the correlation between 1st summary stats and latter other summaries.&#x20;

![](/files/-MDzBD7lRfT4SlHS30MQ)

This example examines the evidence for the genetic correlation between psychological diseases Neuroticism, Depressive symptom and Subjective Well-Being for 10K and fills samples.

**Input files:** summary statistics folder consisting of the following files:

1. Neuroticism\_Full.txt
2. DS\_Full.txt
3. SWB\_Full.txt
4. SWB\_10K.txt

Whole-genome reference SNP list for European ancestral and Pre-computed LD scores.

**Genetic correlation results**

![](/files/-MDzCbN0EqTae7WJSIxh)

The *Interactive Graph* option also provides an alternative visualization method:

![](/files/-ME8bNm0OhvAmhry--bO)

Finally, using the *Export* box, you will be able to download the results of your analysis in a *.pdf* format file.

#### Reference

1. [**Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses**](https://pubmed.ncbi.nlm.nih.gov/27089181/)
2. [**Heritability and Genetic Correlation**](https://github.com/bulik/ldsc/wiki/Heritability-and-Genetic-Correlation)