Comparison of Galaxy and Unix tools for analyzing the exome sequencing data from syndactyly abnormalities

Thy Ngoc Nguyen; Minh Huong Huynh

doi:10.15625/2525-2518/20054

Author affiliations

Authors

Nguyen Thy Ngoc University of Science and Technology of Hanoi, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet, Càu Giay, Ha Noi, Viet Nam https://orcid.org/0000-0002-3181-9209
Huynh Minh Huong University of Science and Technology of Hanoi, Vietnam Academy of Science and Technology. 18 Hoang Quoc Viet, Cua Giay, Hà Noi, Viet Nam

DOI:

https://doi.org/10.15625/2525-2518/20054

Keywords:

Galaxy, Exome sequencing, High performance computing, syndactyly, pipeline

Abstract

Syndactyly is a congenital limb abnormality, which manifests as the fusion of digits due to incomplete separation during embryonic development, and its pathogenesis involves intricate genetic and molecular processes. Since Exome sequencing has gained widespread utilization as an invaluable tool for exploring genetic disorders during prenatal development, the Bioinformatic platforms, such as GALAXY and UNIX, play a central role in the analysis process of exome sequencing data, facilitating precise identification and interpretation of genetic variations linked to congenital abnormalities. In this study, we conducted a comparative analysis of exome sequencing data from a 1.5-year-old syndactyly patient using two platforms: GALAXY and UNIX. The UNIX platform identified a total of 275,572 variants, and the GALAXY platform identified 140,291 variants when compared with the Grch38/hg38 reference genome. A comparative analysis identified 126,848 common variants between the platforms. After filtration with the 200 syndactyly-related genes, 1,345 variants were remained. The distribution of these 1,345 variants spans the entirety of the patient's genome, with focal concentrations observed on specific chromosomes including chromosomes 2, 4, and 11. Concurrently, within the top 200 genes implicated in syndactyly, the genes FRAS1, CACNA1C, GLI2, and NOTCH1 exhibit the highest frequency of variants. These data emphasized the impact of the chosen analytical platform on genetic variation detection in congenital limb abnormalities, provided critical insights into the selection of bioinformatic tools for optimizing exome sequencing workflows in the context of limb malformations, contributed to advancements in genetic research and diagnostic methodologies.

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