Welcome to the online Glia Open Access Database (GOAD)
For more information about the features of GOAD, clickfor the tutorial.
The Glia Open Access Database (GOAD) is a comprehensive web-based tool to access and analyze glia transcriptome data.
The tool has several features that can be accessed by using the drop-down menu:
Differential gene Expression (DE) Analysis
Quantitative gene Expression (QE) analysis
The Differential Expression (DE) analysis can be used to generate gene lists differentially expressed genes with the associated log fold changes and multiple testing corrected p-values between two conditions of interest (A vs. B).
After performing the DE analysis, an interactive volcano scatterplot will be generated showing the most siginificant genes (max 2000 are shown within the plot).
The volcano scatterplot can be used to search a specific gene with the use of a zoom.
Information as the LogFC and FDR values can be seen with the use of a hover function.
The table next to the scatterplot shows all of the significant genes (FDR 0.05).
The columns: Gene symbol, LogFC and FDR can be found within this table.
Genes of interest can be found with the use of the search bar on top of the table.
The DE analysis is done with the use of R, using a pairwise comparison with edgeR.
The raw dataset is filtered for genes with a ount per million (CPM) >= 2 for each row.
Gene symbols are obtained using the biomaRt package.
The Quantitative Expression (QE) analysis can be used to determine which genes are expressed in particular cell type and to what degree.
A table is obtained showing the gene symbols on the left side and the detected cell types on the right of the genesymbol.
The TPM values of the given gene in a given cell type is shown.
Transcripts Per Million (TPM) values are used to quantify gene expression in RNA sequencing data.
TPM is a modification of RPKM, respecting average invariance and elimination statistical biases from the RPKM measure.
The difference with TPM and RPKM/FPKM is that the normalization of the gene length is done first and normalization of the sequencing depth is done second.
Leading to the same number when all of the TPMs are added in each sample, which makes it easier to compare the samples.
Calculation: TPM = (normalized transcripts (RPKM|FPKM) / sum of normalized transcript) * 10^6.
A bar graph is shown when clicking on a gene of interest, showing the TPM values (TPM low, TPM high and TPM) of that gene within all of the known cell types.
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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).
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.
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.
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