ArticlebioRxiv : the preprint server for biology2025
Analysis of 3'-seq data from multiple
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
3-prime end sequencing (3'-seq) is a high-throughput sequencing technique that is used to specifically quantify the changes in 3'-end formation of transcripts in bacterial cells, which is increasingly being utilized to address fundamental questions regarding transcription termination and pausing across a range of different bacterial species. However, the growing number of 3'-seq studies is accompanied by an increase in study-specific 3'-seq data analysis approaches. Thus, differences in a number of factors including: experimental design, data collection approaches, analysis methodologies, and interpretation decisions, make it challenging to confidently compare results derived from different studies, even those that were performed on the same organism. To assess the potential severity of these discrepancies, we used PIPETS, a statistically robust and genome-annotation agnostic 3'-seq analysis package, to study
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.