Cuffdiff 2 is a transcript-level differential expression analysis tool that accurately estimates gene and transcript expression levels from RNA-seq data, accounting for variability across replicate libraries. It identifies differentially expressed transcripts and genes, revealing changes in splicing and promoter preferences. The tool was validated using lung fibroblasts in response to HOXA1 loss, showing significant expression changes in thousands of transcripts and isoform switching in key regulators. Cuffdiff 2 outperforms other methods in accuracy and reduces false positives, especially in complex gene annotations. It performs well across various RNA-seq designs, including benchtop sequencers like the Illumina MiSeq. The tool also identifies key cell cycle regulators and isoform changes in response to HOXA1 loss, demonstrating its utility in understanding gene regulation. Cuffdiff 2 provides robust differential analysis at both gene and transcript levels, enabling comprehensive insights into transcriptome dynamics. It is accurate across different experimental conditions and is suitable for large-scale genomic studies. The tool is integrated into a single workflow, allowing for efficient and accurate differential expression analysis. Cuffdiff 2 addresses key challenges in RNA-seq analysis, including count uncertainty and overdispersion, by modeling fragment counts with a beta-negative binomial distribution. It is particularly effective in detecting differential expression in genes with complex splicing patterns. The tool has been validated against microarray data and other RNA-seq methods, showing high accuracy and reliability. Cuffdiff 2 is a valuable resource for researchers seeking to understand gene regulation at the transcript level.Cuffdiff 2 is a transcript-level differential expression analysis tool that accurately estimates gene and transcript expression levels from RNA-seq data, accounting for variability across replicate libraries. It identifies differentially expressed transcripts and genes, revealing changes in splicing and promoter preferences. The tool was validated using lung fibroblasts in response to HOXA1 loss, showing significant expression changes in thousands of transcripts and isoform switching in key regulators. Cuffdiff 2 outperforms other methods in accuracy and reduces false positives, especially in complex gene annotations. It performs well across various RNA-seq designs, including benchtop sequencers like the Illumina MiSeq. The tool also identifies key cell cycle regulators and isoform changes in response to HOXA1 loss, demonstrating its utility in understanding gene regulation. Cuffdiff 2 provides robust differential analysis at both gene and transcript levels, enabling comprehensive insights into transcriptome dynamics. It is accurate across different experimental conditions and is suitable for large-scale genomic studies. The tool is integrated into a single workflow, allowing for efficient and accurate differential expression analysis. Cuffdiff 2 addresses key challenges in RNA-seq analysis, including count uncertainty and overdispersion, by modeling fragment counts with a beta-negative binomial distribution. It is particularly effective in detecting differential expression in genes with complex splicing patterns. The tool has been validated against microarray data and other RNA-seq methods, showing high accuracy and reliability. Cuffdiff 2 is a valuable resource for researchers seeking to understand gene regulation at the transcript level.