Extracting novel hypotheses and findings from RNA-seq data
Reviewartikel, 2020

Over the past decade, improvements in technology and methods have enabled rapid and relatively inexpensive generation of high-quality RNA-seq datasets. These datasets have been used to characterize gene expression for several yeast species and have provided systems-level insights for basic biology, biotechnology and medicine. Herein, we discuss new techniques that have emerged and existing techniques that enable analysts to extract information from multifactorial yeast RNA-seq datasets. Ultimately, this minireview seeks to inspire readers to query datasets, whether previously published or freshly obtained, with creative and diverse methods to discover and support novel hypotheses.

lncRNA

RNA-seq data analysis

yeast

transcriptome

GO term analysis

phylostratigraphy

Författare

Tyler Doughty

Chalmers, Biologi och bioteknik, Systembiologi

Eduard Kerkhoven

Chalmers, Biologi och bioteknik, Systembiologi

FEMS Yeast Research

1567-1356 (ISSN) 1567-1364 (eISSN)

Vol. 20 2 foaa007

Ämneskategorier

Bioinformatik (beräkningsbiologi)

Bioinformatik och systembiologi

Genetik

DOI

10.1093/femsyr/foaa007

PubMed

32009158

Mer information

Senast uppdaterat

2020-03-31