Abstract
The genome-wide analysis of gene transcription using RNA sequencing (RNA-seq) has become the method of choice for characterizing and understanding transcriptional regulation in yeasts. RNA-seq has largely supplanted microarray based approaches in recent years due to improved accuracy and flexibility in the high-throughput identification and quantification of transcripts. The improvements associated with a sequencing approach compared to one based on hybridization, however, are accompanied by new experimental considerations related to both the collection and the analysis of the transcriptome data. Consensus approaches for processing and analysing the RNA-seq data in particular have yet to be arrived at, and it is possible to feel overwhelmed when surveying all the software tools that have been developed and recommended for these tasks. This chapter considers these issues in the context of providing general guidelines to help achieve best practice in yeast RNA-seq studies, and recommends a small number of the best performing tools that are currently available.
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Hesketh, A.R. (2019). RNA Sequencing Best Practices: Experimental Protocol and Data Analysis. In: Oliver, S.G., Castrillo, J.I. (eds) Yeast Systems Biology. Methods in Molecular Biology, vol 2049. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9736-7_7
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DOI: https://doi.org/10.1007/978-1-4939-9736-7_7
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