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Alternative promoter usage generates different transcripts by selecting different transcription start sites (TSS) upstream of a gene, leading to diverse transcriptomes. This mechanism can regulate processes like alternative splicing, tissue specificity, and gene activation during development. To study differential TSS usage, various assays (CAGE, RAMPAGE, STRIPE-seq) and normalization methods (MOR, TMM, TPM, Power normalization) are used. Clustering methods (distance-based, density-based parametric) group TSS into transcription start regions (TSR). Preliminary results show that different assays produce similar TSS abundance data after normalization, except for nanocage, and that the choice of normalization method does not affect downstream analysis. However, different clustering methods yield vastly different results, which could impact biological claims based on TSR usage. Future work includes studying the origin of discrepancies in clusters, implementing a more accurate clustering method, and applying statistical techniques to analyze tissue-specific TSRs.