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Bioinformatics of the Brain

low. These additional application options make it more advantageous over

microarrays. The optimization of protocols, the demand for high-power com-

puter facilities, high setup costs, and complex analysis in the case of splice

variants or paralogues are some problems that still need to be overcome for

this technology [20].

8.3

Repositories

Various types of microarrays and RNA-seq technology were employed in hopes

of identifying the genetic mechanism of diseases and disorders in wet lab ex-

periments. These studies are archived in several online repositories.

The National Center for Biotechnology Information’s (NCBI) Gene ex-

pression omnibus (GEO) is the most widely used public functional ge-

nomics data repository that has both array and sequence-based data

(https://www.ncbi.nlm.nih.gov/geo/). Here researchers can search for studies

done on any disease that comes to mind. There are currently 4348 datasets,

206863 series, 25300 platforms and 6640900 samples in this repository (as of

August 2023). All the brain diseases and disorders discussed in the first chap-

ter of this book were searched in the GEO database and a chart was drawn

with the number of experiments (number of series) done for each brain dis-

ease/disorder (Figure 8.2). Here, we can see that among the three groups of

diseases and disorders investigated in this book, major transcriptomic research

was done on brain tumors, with gliomas being the leading disease group. The

second mostly experimented brain disease group is the neurodegenerative dis-

eases, with Alzheimer’s Disease (AD) leading the group. Here, we should also

highlight that numerous genes have been linked to autism, despite the fact that

there aren’t as many studies about this complex condition in GEO database.

ArrayExpress (https://www.ebi.ac.uk/biostudies/arrayexpress) is another

public repository that stores data from high-throughput functional ge-

nomics experiments such as gene expression, methylation profiling, chromatin

immunoprecipitation assays, RNA-seq, and single-cell RNA-seq (scRNA-

seq) [21]. There is also The DNA Data Bank of Japan (DDBJ) Center

(https://www.ddbj.nig.ac.jp) which has developed the Genomic Expression

Archive (GEA) for functional genomics data obtained from microarray and

high-throughput sequencing studies [22]. The data can be downloaded from

these repositories freely.

8.4

Data Analysis and Visualization Tools

The data obtained from wet lab experiments employing microarray and RNA-

seq technology needs to be analyzed to give comprehensible meaning to