Genomic Analysis


These are the guidelines of the new Genomic Analysis Application, currently named Next-GPAP. This module is currently in Beta Version and not accessible by all users. You may need special credentials to access it. Please contact for further information.

The Genomic Analysis module enables analysis of genomic experiments in GPAP.


Use Cases

There are different uses cases:

  1. Case / Family Analysis

  2. Cohort Analysis

  3. Search Across All

Case Analysis

This is the scenario in which a single case or a family of individuals can be analyzed. You can start creating your own study by adding a name, a description and a permission:

  • Public to make the study visible to all yours

  • Share with groups to make the study visible only with users that are sharing your GPAP groups

  • Private, the study will be only visible to you

After creating the study, you will be navigated through four different steps:

  1. Select experiments to analyze: here you can search for experiments or individuals by selecting an option in the radio-buttons. By default, the family members are collected and added to the analysis. A list of Experiments is displayed and included in the analysis. You can then click Next

  2. Review Phenotypic and Genetic Information: This step allows you to review the clinical and phenotypic information of the individuals.

  3. Inheritance Mode: you can select a predefined inheritance mode that takes into account the affect status of each individual. You can also create your worn customization by selecting “Custom”. In this inheritance mode you can edit the affected status of the individuals.

  4. Apply Variant and Gene Filters: you can now create a query by selecting variant and gene filters from the form. For more information about the filters, please read the dedicated section.

Selecting experiments/participants

You can select experiments or participants by searching for different IDs: the local or GPAP Experiment ID, the local or PhenoStore ID. By default, the family members for a found participant will be included in the analysis. You can disable this option. You can also remove participants from the analysis. An overview with detailed information for the participants is displayed in Step 2 Review Phenotypic and Genetic Information


Selecting inheritance mode

To facilitate the configuration of the inheritance of analyzed participants, the genomics application offers two main options in step 3:
  • The user can benefit of simulated configurations of different types of inheritances based on the recorded affected status of the individuals

  • Custom configuration, in which the user can select the genotype and quality settings to explore hypotheses


Example of simulated inheritance - Autosomal Dominant


Example of Custom Inheritance. The user can change the affected status of the individuals, the genotype and the quality settings.


Quality Settings



To be completed.

Cohort Analysis

In this scenario, a cohort created in the CohortApp can be analyzed. A study is automatically created.

There are four different steps :
  1. Select Cohort to analyze or create a new cohort: this section option will redirect to the GPAP CohortApp where you can create and save a cohort that will then appear in the dropdown for “Cohorts ready for analysis”

  2. Configure inheritance mode: after selecting a cohort, you can configure an inheritance mode, same as the “Custom” in the Case Analysis scenario.

  3. Select Genes: it is mandatory to select at least one gene for this analysis. This steps allows you to select from different lists (please read dedicated section).

  4. In the last step, you can apply variant filters. This is highly recommended to narrow down your search and minimize the computational effort.

Search Across All


This use case may suffer of performance issue when millions of variants are found

In this scenario, you will search across all experiments in our created in the CohortApp can be analyzed. A study is automatically created.

There are four different steps :
  1. Configure inheritance mode: after selecting a cohort, you can configure an inheritance mode, same as the “Custom” in the Case Analysis scenario.

  2. Select Genes: it is mandatory to select at least one gene for this analysis. This steps allows you to select from different lists (please read dedicated section).

  3. In the last step, you can apply variant filters. Same for the Cohort Analysis, this is highly recommended to narrow down your search and minimize the computational effort.


The genomics analysis provides different filters that can be used to narrow down results and to identify harmful/potentially harmful variants. You find two main classes of filters in the Genomic Analysis Module: Variant Prioritization filters and Genes. We explain these in more details.

Variant Filters

The filters are the following:

Variant Type:
  • Variant class (as defined by SnpEff

  • ClinVar Classification : ClinVar aggregates information about genomic variation and its relationship to human health

  • Variant Type (SNV or Indel)

  • Tagged Variants ( filter by tagged variants from all Experiments or only selected)

  • Transcript Biotype (Coding, RNA, other)


  • 1000Genomes AF

  • Internal Frequency

SNV Effect Predictions:
  • Mutation Taster

  • SIFT

  • Polyphen2 hvar

  • CADD Prediction

Position Specific and Run of Homozygosity
  • Chromosome, Start Position and End Position

  • Upload Bed File

  • Upload Coordinate file

  • Minimum run of homozygosity length

Gene Filters

Genes can be found and searched from different sections. Genes can be intersected or merged. The Gene List selected can be cleared anytime The sections and the filters are the following:

Variant Dashboard

Once you run the first query of one or more analyses, the variants matching the applied filters and inheritance will be displayed in the variant dashboard. Variants are listed in a dedicated table. In this dashboard, the user can find different tools to work on the analysis, to explore results and to refine the search through an interactive and iterative approach. We present here the different elements of the interface.

Study Toolbar:
  • New Analysis: to create a new analysis, edit the experiments genotypes and create new queries

  • Save (Study): if a number on it is shown, it means that there are queries unsaved in your work

  • Current Work: to review the current list of analyses and queries

  • Share Study: to share your (saved) work with other users via a predefined link. You need to save a study beforehand to be able to share a study

  • View Participants/Experiment Information: review the main information of the analyzed participants

  • Analysis Status: it shows if the experiments have been already analyzed / solved and allows to change the analysis status for a specific experiment

  • Edit Query Name: it is possible to change the name of the current query at any time.

  • Number of variants in current query: displayed next to the query name

Toolbar of Variant Table:
  • New Query: it is possible to create a new query at any time, applying variant filters or creating gene lists

  • Summary of results: shows a visual summary of relevant information of the collected variants

  • Plugins: list of integrated plugins that can be used by taking the variants as input

  • Export: it allows to export a maximum of 1000 variants

  • View Applied Filters: you can revisit the applied filters of the current query

Variant Table:
  • Variants as Rows

  • Transcripts on demand

Variant Row

In the Variant table each row is a variant retrieved from the GPAP database. We show information for the following fields:

Gene and Variant Info:
  • Gene Name

  • Transcript BioType

  • Effect Impact

  • Nucleotide Change

  • Aminoacid Change

  • Consequence

Clinical Association:
  • OMIM

  • ClinVar

  • VarSome

Population Info:
  • Internal Frequency

  • GnomAD AF

  • CADD Pred.

  • SIFT Pred

  • PolyPhen2 Hvar Pred.

  • Mutation Taster Pred.


Also, there is more information on demand when you select a variant - see image below. Expanding the Variant Row, the transcripts associated to the variant are displayed. The main information for each transcript is shown in the Figure below.


Label and Tag a variant

When selecting a variant, two main operations are provided: Label and Tag. You can label a variant to Follow Up and to label it as Important for futher analysis. This is a personal annotation and it is not going to be shared beyond the study that you are working on. Tagging a variant is different. You tag a variant within the GPAP Platform. Other users may be able to see you tag and may see an icon as shown in the Figure above in which a variant is tagged.

Tagging a variant in details: When selecting a variant, and clicking on tag, you will see the dialog below. Some information are already filled in from the variant details. Other fields require your action. Select the sample, the transcript, the type of inheritance, zygosity, clinical significance and interpretation. Also you can specify whether this is a causative variant or not. If Causative you will be also requested to update the Solved Status of the Participant if you are the owner of the case.

After tagging, the tag will be made visible within the GPAP Platform.


From one Analysis/Query to the other

After running queries or creating new analyses, you will see the tabs on top of your variant table, expanding. You can create multiple analyses and queries to test your hypotheses. You can also go back and forth, revisiting the results you obtained by applying different queries. This may help you understanding the variants and finding something interesting! You can also directly discard queries or analyses by clicking on the X button in each tab of analysis or query. By clicking on the View Applied Filters you can see which filters were applied in each query. In the Query Tab, in parenthesis you can find the number of variants found for that query. Creating a new Query, will add a new tab under the current analysis.


Save, load and share a study

A study can be saved anytime. When saving a study, you can enter/edit the name of the study, add a description and set the visibility of the study. Once a study is saved, you can save again at anytime to store new queries and to update information like name, description and visibility.


When deleting a query and an analysis, the deletion is irreversible and there is no need to save to finalize this change.

After a study is saved, you can shared it with the corresponding link provided from the specific Share option.

A study can be deleted from your homepage in the application. See below.