AskOmics is a web software for data integration and query using the Semantic Web technologies. It helps users to convert multiple data sources (CSV/TSV files, GFF and BED annotation) into RDF triples, and perform complex queries using a user-friendly interface.

In this tutorial, we will learn the basics of AskOmics by analysing RNA-seq results. The provided datasets come from a differential expression analysis.

4 files will be used in this tutorial:

Throughout the guide, you will find Hands-on sections containing instructions to perform in order to get started with AskOmics.

To complete the tutorial, you will need an AskOmics instance. You can install your own or use this public instance.

A Galaxy Training tutorial is also available here

Account creation and management

Login or signup into AskOmics

AskOmics is a multi-user platform. To use it, you will need an account on the instance. Use the Login button on the navbar, and log in using your AskOmics credentials. If you don't have already an account, fill the signup form by clicking on signup below the login form.


Create your AskOmics account (or login with your existing one)

Once you are logged, you can use all the functionalities of AskOmics.

Manage your account

To manage your account, use the Account management tab by clicking on Your Name ▾ on the navigation bar.

You can use the forms to change your personal information.

Data integration

AskOmics will convert project specific data into RDF triples automatically. It can convert CSV/TSV, GFF and BED files.

Data upload

The first step is to upload the input files into AskOmics. Go on the Files page by clicking on Files.

You can upload files from your computer, or distant files using an URL.


Upload the files limma-voom_luminalpregnant-luminallactate, Mus_musculus.GRCm38.98.subset.gff3, symbol-ensembl.tsv and MGIBatchReport_Qtl_Subset.txt from your computer into AskOmics


You can also copy files URL and use the URL button.

Uploaded files are displayed into the files table. Filenames can be changed by clicking on it.

Files table

Next step is to convert this files into RDF triples. This step is called Integration. Integration will produce a RDF description of your data: the Abstraction.


Select the four files and click on Integrate


Detailed information regarding the Integration step can be found here.

The integration convert input files into RDF triples, and load them into an RDF triplestore. AskOmics can convert CSV/TSV, GFF3 and BED files. During the step of integration, AskOmics show a preview of each files. We can choose how the file will be integrated at this step.

More information about data integration is available here


GFF files contain genetic coordinate of entities. Each entity contained in the GFF file is displayed on the preview page. We can Select the entities that will be integrated.


  1. Search for Mus_musculus.GRCm38.98.subset.gff3 (preview)
  2. Select gene and mRNA
  3. Integrate (Private dataset)

Integration interface for GFF files


The TSV preview show an HTML table representing the TSV file. During integration, AskOmics will convert the file using the header.

The first column of a TSV file will be the entity name. Other columns of the file will be attributes of the entity. Labels of the entity and attributes will be set by the header. The column names can be edited by clicking on it.

Entity and attributes can have special types. The types are defined with the select below the header. An entity can be a start entity or an entity. A start entity mean that the entity may be used to start a query.

Attributes can take the following types:

  • Numeric: if all the values are numeric
  • Text: if all the values are strings
  • Date: if all the values are dates
  • Category: if there is a limited number of repeated values

If the entity describe a locatable element on a genome:

  • Reference: chromosome
  • Strand: strand
  • Start: start position
  • End: end position

A columns can also be a relation between the entity to another. In this case, the header have to be relationName@TargetedEntity and the type Directed or Symmetric relation. a Directed relation is a relation from this entity to the targeted one. A Symetric relation is a relation on both directions.


  1. Search for limma-voom_luminalpregnant-luminallactate (preview)
  2. Edit attribute names and types:
    • change ENTREZ ID to Differential Expression and set type to start entity
    • change SYMBOL to linkedTo@GeneLink and set type to Directed relation
    • change GENENAME to name and set type to text
    • Keep the other column names and set their types to numeric
  3. Integrate (Private dataset)

Integration interface for CSV files


  1. Search for symbol-ensembl.tsv (preview)
  2. Edit attribute names and types:
    • change symbol to GeneLink and set type to entity
    • change ensembl to linkedTo@gene and set type to Directed relation
  3. Integrate (Private dataset)

Modifying the name and type of a column


  1. Search for MGIBatchReport_Qtl_Subset.txt (preview)
  2. Edit attribute names and types:
    • change Input to QTL and set type to start entity
    • set Chr type to Reference
    • set Start type to Start
    • set End type to End
  3. Integrate (Private dataset)

Preview of the QTL file

Manage integrated datasets

Integration can take some times depending on the file size. The Datasets page show the progress.


  1. Go to Datasets page
  2. Wait for all datasets to be success

Table of datasets

The table show all integrated datasets. The status column show if the datasets are fully integrated or in the process of being integrated.


Once all the data of interest is integrated (converted to RDF graphs), its time to query them. Querying RDF data is done by using the SPARQL language. Fortunately, AskOmics provides a user-friendly interface to build SPARQL queries without having to learn the SPARQL language.

More information about the query building process is available here

Query builder overview

Simple query

The first step to build a query is to choose a start point for the query.

List of startpoints


  1. Go to Ask! page
  2. Select the Differential Expression entity
  3. Start!

Once the start entity is chosen, the query builder is displayed.

The query builder is composed of a graph. Nodes represents entities and links represents relations between entities. The selected entity is surrounded by a red circle. Links and other entities are dotted and lighter because there are not instantiated.

The query builder

On the right, attributes of the selected entity are displayed as attribute boxes. Each boxes have an eye icon. Open eye mean the attribute will be displayed on the results.


  1. Display logFC and adj.P.val by clicking on the eye icon
  2. Run & preview

Preview of results

Run & preview launch the query with a limit of 30 rows returned. We use this button to get an idea of the results returned.

Filter on attributes

Next query will search for all over-expressed genes. Genes are considered over-expressed if the log fold change is > 2. We are only interested by significant results (Adj P value ≤ 0.05)


  1. Filter logFC with > 2
  2. Filter adj.P.val with 0.05
  3. Run & preview

Results show only significantly over-expressed genes.

Filter on relations

Now that we have our genes if interest, we will link these genes to the reference genome to get information about the location.

To constraint on a relation, we have to click on any suggested nodes linked to our entity of interest.


  1. First, hide Label, logFC and adj.P.val of Differential Expression
  2. Instantiate GeneLink, and hide Label
  3. Instantiate gene
  4. Run & preview

Results now show the Ensembl id of our over-expressed genes. We have now access to all the information about the gene entity containing on the GFF file. For example, we can filter on chromosome and display chromosome and strand to get information about the gene location.


  1. Show reference and strand using the eye icon
  2. Filter reference to select X and Y chromosomes (use ctrl+click to multiple selection)
  3. Run & preview

Use FALDO ontology to query on the position of elements on the genome.

The FALDO ontology describe sequence features's positions and regions. AskOmics use the FALDO ontology to represent entity positions.
All entities extracted from GFF and BED files use this ontology, in addition to any entity extracted from a CSV/TSV file with a reference, strand, start and end columns.

The FALDO ontology is used in AskOmics to perform special queries between 2 FALDO entities. These queries are:

  • Entity is included in another entity
  • Entity is overlapping another entity

On the query builder interface, FALDO entities are represented with a green circle and FALDO relations have a green arrow.


  1. First, remove the reference filter (unselect X and Y using ctrl+click)
  2. Hide strand and reference using the eye
  3. Instantiate QTL
  4. Click on the link between gene and QTL to edit the relation
  5. check that the relation is gene included in QTL on the same reference with strict ticked
  6. Run & preview

To go further, we can filter on QTL to refine the results.


  1. Go back to the QTL node
  2. Show the Name attribute using the eye icon
  3. Filter the name with a regexp with growth
  4. Run & preview

From now, our query is "All Genes that are over-expressed (logFC > 2 and FDR ≤ 0.05) and located on a QTL that are related to growth" This is the results that we are looking for. We can now save it.


  1. Run & save
  2. Go to the Results page

Results management

The results page store the saved queries. A table show some useful information about the queries. Query name can be edited by clicking on it.


  1. Click on the name and enter Over-expressed genes on a growth QTL
  2. Press the Enter key

Table of results

The Action column contain buttons to perform certain action:

  • Preview: Show a results preview on the bottom of the table
  • Download: Download the results (TSV file)
  • Edit: Edit the query with the query builder
  • SPARQL: Access the generated SPARQL query for the result

For more information about the Results page, please head here


  1. Download the results file on your computer using the Download button.

The Edit button can be used to simply replay the query after changing some parameters.


  1. Edit the query, and replace "growth" with another term of interest (such as "anxiety").
  2. Preview the results

Advanced queries

Advanced queries, including UNION and MINUS SPARQL queries are also available to further your queries.
Please head here for more information.


By using the 'Abstraction' button on the navigation bar, you can see the whole abstraction (all nodes and relations) as a 2D/3D graph. You can click on a node to focus on it.

In '2D' mode, hovering over a node or a link will show all related nodes.


In this tutorial we have seen how to use the AskOmics Interactive Tool, building a complex SPARQL query to interrogate 4 different datasets and answer a biological question.

This tutorial was a brief overview of AskOmics's functionalities. Please check the other categories on the left-side for more information.