{key = 'gepia2'; text = 'GEPIA2 is an updated version of the Gene Expression Profiling Interactive Analysis (GEPIA) server that provides comprehensive tools and resources for analyzing gene expression data in cancer research.'}

I have extracted key information from your provided text as follows:

1. GEPIA2: This is a web-based platform designed to facilitate large-scale analysis of RNA-Seq data, with particular emphasis on understanding the molecular mechanisms underlying various types of cancers.

2. Features:

- Local package: Users can download and install a python package called `gepia` for faster access to the GEPIA2 functions.

- Custom data upload: Researchers can upload their own cancer RNA-Seq data to perform analyses such as identifying molecular subtypes, TCGA immune subtyping, pan-cancer subtype classification, etc.

3. Analytical Tools:

- Signature score analysis: This function helps users analyze the prevalence of specific gene signatures in different samples and provides tools for correlation analysis and survival analysis.

- Cancer subtypes comparison: Users can select their preferred cancer subtype(s) or compare multiple subtypes based on various parameters such as expression levels, survival rates etc.

4. Usage:

- GEPIA2 supports both bulk RNA-Seq data and single-cell RNA-seq (scRNA-seq) data analysis.

- It allows users to perform differential gene expression analyses between different groups of samples or across time points within the same sample.

5. Advantages:

* Easy-to-use interface: The platform is designed with non-bioinformaticians in mind, making it accessible even for those without extensive computational experience.

* Extensive databases integration: GEPIA2 integrates multiple public cancer omics data sets including TCGA and GTEx to facilitate comparison of results across different studies.

6. Future Prospects:

- Continuous updates with new features and tools will further enhance the capabilities of GEPIA2 in facilitating cutting-edge research in cancer genomics.

- The platform aims to become a valuable resource for researchers worldwide by providing an open-access, user-friendly environment where scientists can share their findings and collaborate on understanding the complex biology underlying various cancers.

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