Abstract:
RNA-Seq has enabled the detection of novel transcripts and offers a genome
wide analysis of gene fusions, single nucleotide variation and indels. This type of com-
putational RNA-Seq analysis requires a researcher to select appropriate softwares and
efficiently utilize their options to obtain required results. Majority of these softwares
operate on command-line interface which adds to another layer of complexity for
those with limited programming skills. Several interfaces have already been devel-
oped to facilitate researchers but only a few cover all the steps for RNA-Seq analysis.
There is a need to design a desktop interface that can perform data analysis locally
without the security concerns that are posed by web interfaces. An interactive desk-
top interface, GUITAR has been developed for RNA-Seq data analysis using python
desktop framework called Tkinter. GUITAR eliminates the need for understanding
command-line syntax along with programming knowledge. It incorporates 10 most
renowned bioinformatics tools which perform all the required steps of RNA-Seq data
analysis from downloading raw data to differential expression. At this stage GUITAR
can only perform differential expression using DESeq2 and Ballgown on test data.
Three RNA sequencing datasets of psoriasis disease were used a case study. Psoriasis
is an autoimmune and genetic disease classified by inflammation of skin with raised
scaly patches due to rapid growth of epidermal cells in skin tissues. RNA-Seq analysis
was performed on these datasets and differentially expressed genes were identified.
Pathway analysis was performed using common differentially expressed genes in
order to find out key factors that trigger the autoimmune response. In future we aim
to provide user the option to perform differential expression using his own data and
select his required normalization, standardization and plotting options. We also aim
to increase the diversity of bioinformatics tools incorporated into GUITAR which
can make it a tool of choice for performing ChIP-Seq and whole genome sequencing
analysis.
