GitHub - giulio-ran/Network-based-expression-analysis: In this study, a dataset of row mRNA-seq counts obtained from Type 2 Diabetes (T2D) patients was analyzed using various statistical and machine learning methods: among these, LDA was chosen as the best performing, and therefore used to obtain a list of significant genes.

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GSE159984_raw_counts_GRCh38.p13_NCBI.tsv		GSE159984_raw_counts_GRCh38.p13_NCBI.tsv
Progetto_Network-based_analysis_Beta_cells.R		Progetto_Network-based_analysis_Beta_cells.R
Project Report Giulio Randazzo Network-based Data Analysis.pdf		Project Report Giulio Randazzo Network-based Data Analysis.pdf

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In this study, a dataset of row mRNA-seq counts obtained from Type 2 Diabetes (T2D) patients was analyzed using various statistical and machine learning methods: among these, LDA was chosen as the best performing, and therefore used to obtain a list of significant genes.

statistics biostatistics network-analysis lda-model expression-analysis random-