The article "Improving RNA-Seq expression estimates by correcting for fragment bias" by Adam Roberts, Cole Trapnell, Julie Donaghey, John L Rinn, and Lior Pachter addresses the issue of non-uniform distribution of cDNA fragments within transcripts, which can lead to biased expression estimates in RNA-Seq data. The authors propose a likelihood-based approach to correct for both positional and sequence-specific biases in fragment distribution. They demonstrate that this correction improves the correlation of expression estimates with independently performed qRT-PCR data and enhances the replicability of results across different libraries and sequencing technologies. The method is validated using benchmark datasets and compared with existing methods, showing superior performance in terms of correlation and robustness to various library preparation protocols and sequencing platforms. The authors also discuss the implications of bias correction for differential expression analysis and the choice of modeling approaches. The software implementing their method, Cufflinks, is freely available and can be integrated into RNA-Seq data processing pipelines to improve the accuracy of expression estimates.The article "Improving RNA-Seq expression estimates by correcting for fragment bias" by Adam Roberts, Cole Trapnell, Julie Donaghey, John L Rinn, and Lior Pachter addresses the issue of non-uniform distribution of cDNA fragments within transcripts, which can lead to biased expression estimates in RNA-Seq data. The authors propose a likelihood-based approach to correct for both positional and sequence-specific biases in fragment distribution. They demonstrate that this correction improves the correlation of expression estimates with independently performed qRT-PCR data and enhances the replicability of results across different libraries and sequencing technologies. The method is validated using benchmark datasets and compared with existing methods, showing superior performance in terms of correlation and robustness to various library preparation protocols and sequencing platforms. The authors also discuss the implications of bias correction for differential expression analysis and the choice of modeling approaches. The software implementing their method, Cufflinks, is freely available and can be integrated into RNA-Seq data processing pipelines to improve the accuracy of expression estimates.