Introduction/Background Over the past decade, next-generation sequencing has emerged as a pivotal tool in laboratories worldwide for both diagnostics and research of oncological malignancies, including gynaecological. However, the exponential growth of sequencing data has presented a challenge in terms of timely and accurate mathematical and statistical analysis. Consequently, bioinformatics has gained prominence as an indispensable component of research in various biochemical fields.

Methodology We devised a bioinformatics workflow aimed at optimizing RNA sequencing (RNASeq) outcomes. The initial steps involve data pre-processing, such as quality control of raw data, data trimming, alignment and quantification. Leveraging the R programming language in R Studio, we conducted diverse analyses using packages such as DESeq2, Cluster Profiler, WGCNA, and others to reveal changes in transcriptome landscape as well as visualize pathways affected by this deregulation or co-expression gene networks.

Results Our efforts culminated in the successful creation of a robust pipeline for in-depth RNASeq data analysis. We identified differentially expressed genes and conducted gene set enrichment analyses, and utilized several plot types provided by the ggplot2 package. Moreover, we determined modules of genes indicating co-expression, which enable us to comprehend the connections between genes in depth. These analyses allowed us to discern patterns in gene expression, enabling us to contextualize information about gene dysregulation within a biologically relevant framework.

Conclusion In summary, the effective analysis of deep RNASeq data necessitates the use of appropriate bioinformatics tools. Our established workflow proved instrumental in conducting efficient analyses and extracting valuable information about gynaecological malignancies, thereby enhancing our understanding of gene dysregulation in the broader biological context. Supported by the Czech Health Research Council grant no. NU22–08-00186, the Grant Agency of Charles University, projects no. 164323 and COOPERATIO Surgical Disciplines no. 207035, ’Maternal and Childhood Care’.

Disclosures This study is supported by the Czech Health Research Council grant no. NU22–08-00186, the Grant Agency of Charles University, projects no. 164323 and COOPERATIO Surgical Disciplines no. 207035, ’Maternal and Childhood Care’.