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Next Generation Sequencing (NGS) for quantitative transcriptomic analysis of colorectal tumor cell lines and their ENU mutants

GSE176264 Mus musculus Expression profiling by high throughput sequencing 4 samples Submitted 2024/06/07 Platform GPL19057
Summary
Purpose: To understand differences of gene expression profiles between colorectal cell lines and their ENU mutants. Methods: RNA profiles were generated by deep sequencing using Illumina Next-seq. Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (GRCm38 release-95). Conclusions: Our study represents the detailed differential transcriptomic analysis using ENU mutants of colorectal tumors, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
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Direct links to NCBI, no account and no request form: the whole study as GSE176264_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 4 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA735655 and SRA study SRP323003. Searching any of these in the dataset finder brings you back here.

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