Detail publikace

Reproducible analytical pipeline for using raw RNA-Seq data from non-model organisms

SCHWARZEROVÁ, J.

Originální název

Reproducible analytical pipeline for using raw RNA-Seq data from non-model organisms

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

Current biotechnological research of bacterial or archaeal genomes has huge potential due to the use of the next generation sequencing (NGS) platforms. NGS era unravelled huge analysis data for sufficiency description microorganisms with ecology potential in future. Nowadays, efforts lie in creating comprehensive pipelines that can be used for pre-processing analysis to enable effective following steps of high throughput data processing. This paper deals with design of data analysis pipeline for using raw RNA-Seq data that was applied to the Clostridium beijerinckii NRRL B-598. The bacterium is typical performer in the field of biofuels production thanks to its ability to produce butanol. Unfortunately, it is non-model organism as many other microorganisms which can be of great potential from ecological point of view. The proposed pipeline offers to take necessary steps in initial data processing that produces data of comparable quality to widely studied model organisms. Therefore, it can be combined with following pipelines for gene regulatory network inference, which was up to date matter of non-model organisms.

Klíčová slova

RNA-Seq; Next generation sequencing; Clostridium beijerinckii NRRL B-598; Transcriptome

Autoři

SCHWARZEROVÁ, J.

Vydáno

23. 4. 2020

Nakladatel

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

Místo

Brno

ISBN

978-80-214-5867-3

Kniha

Proceedings of the 26th Conference STUDENT EEICT 2020

Číslo edice

1

Strany od

225

Strany do

228

Strany počet

4

URL

https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2020_sbornik_1.pdf

BibTex

@inproceedings{BUT165307,
  author="Jana {Schwarzerová}",
  title="Reproducible analytical pipeline for using raw RNA-Seq data from non-model organisms",
  booktitle="Proceedings of the 26th Conference STUDENT EEICT 2020",
  year="2020",
  number="1",
  pages="225--228",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  address="Brno",
  isbn="978-80-214-5867-3",
  url="https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2020_sbornik_1.pdf"
}