Welcome to the brain interactive sequencing analysis tool (BRAIN-sat)

BRAIN-sat is an interactive online platform that contains preprocessed data to enables analyses of public available studies.
This preprocessing enables the interactive analyses as searching for genes, quantitative and differentially expression analysis.
For more information about the features of BRAIN-sat, clickfor the tutorial.

If you have suggestions or questions regarding BRAIN-sat, please feel free to contact us.
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CelltypeRegionOrganismAuthorTitleYear
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).









B.A.sc. M.L. Dubbelaar B.A.sc. M.L. Brummer Prof. Dr. B.J.L. Eggen Prof. Dr. H.W.G.M. Boddeke

University Medical Center Groningen
Department of Neuroscience, section Medical Physiology
Antonius Deusinglaan 1
9713 AV Groningen
The Netherlands

Data Processing

The compute 5 pipeline from MOLGENIS was used to process the data. This pipeline contains several other features that were used to obtain results for BRAIN-sat. Aligning was done with HISAT2. FASTQC was used to perform a quality check on obtained datasets. Several preprocessing steps were performed with Picard and Samtools. HTSeq was used to obtain the counts for the datasets.

Analyses

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

Visualization BRAIN-sat

The set-up of MOLGENIS and several javascript packages where used in order to develop BRAIN-sat. The sorting of the table content was done with the use of sorttable. D3js was used in order to develop the interactive images of the QE data and the implementation of html2canvas and jsPDF make sure that these images can be downloaded.
Plotly was used to generate the interactive images of the single cell data and the differential expression vulcano scatterplot of the bulk RNA data.

Datasets

Butovsky et al. (2013) Pubmed Data
Chiu et al. (2013) Pubmed Data
Galatro et al. (2013) Pubmed Data
Gosselin et al. (2013) Pubmed Data
Hanamsagar et al. (2013) Pubmed Data
Matcovitch-Natan et al. (2013) Pubmed Data
Zhang et al. (2014) Pubmed Data

Citation

  • Holtman et al. (2015). Glia Open Access Database (GOAD): A comprehensive gene expression encyclopedia of glia cells in health and disease.
    Glia 63:1495–1506 doi: 10.1002/glia.22810 Pubmed

Acknowledgements

We would like to thank the following people for the contribution of BRAIN-SAT:
For supervising students from the Hanzehogeschool, we would like to thank M.A. Noback and R. Wedema.
S. N. Dubbelaar for the creation of the BRAIN-SAT logo.