Welcome to the online Glia Open Access Database (GOAD)

For more information about the features of GOAD, clickfor the tutorial.



Quantitative Expression (QE) analysis can be used to determine which genes are expressed in particular cell type and to what degree.
Differential Expression (DE) analysis can be used to generate gene lists containing differentially expressed genes with the associated log fold changes and multiple testing corrected p-values between two conditions of interest (A vs. B).

University Medical Center Groningen
Department of Neuroscience, section Medical Physiology
Antonius Deusinglaan 1
9713 AV Groningen
The Netherlands
Marissa Dubbelaar
Bart Eggen
Erik Boddeke

Data Processing

The compute 5 pipeline from MOLGENIS was used to process the data. This pipeline contained several other features that where used to obtain results for GOAD. Aligning was done with the use of HISAT. FASTQC was used to perform a quality check upon the obtained datasets. Several preprocessing steps for HTSeq with the use of Picard and Samtools. In the end HTSeq was used to obtain the counts for the datasets.


The interactive analyses are done with the use of R. The filtering of low expression genes is done with the use of DAFS: a data-adaptive flag method. EdgeR is used in order to generate the differential expression lists and to obtain the quantitative gene information, and scatterD3 was used to create the interactive volcano scatterplot.

Visualization GOAD

The set up of MOLGENIS and several javascript packages where used in order to develop GOAD. The sorting of the table content was done with the use of sorttable. D3js was used in order to develop the interactive images and the implementation of html2canvas and jsPDF make sure that these images can be downloaded.