MOIRAI: A compact workflow system for CAGE analysis

Akira Hasegawa; Carsten Daub; Piero Carninci; Yoshihide Hayashizaki; Timo Lassmann

doi:10.1186/1471-2105-15-144

MOIRAI: A compact workflow system for CAGE analysis

Akira Hasegawa, Carsten Daub, Piero Carninci, Yoshihide Hayashizaki, Timo Lassmann

Research output: Contribution to journal › Article › peer-review

50 Citations (Scopus)

Abstract

Background: Cap analysis of gene expression (CAGE) is a sequencing based technology to capture the 5' ends of RNAs in a biological sample. After mapping, a CAGE peak on the genome indicates the position of an active transcriptional start site (TSS) and the number of reads correspond to its expression level. CAGE is prominently used in both the FANTOM and ENCODE project but presently there is no software package to perform the essential data processing steps. Results: Here we describe MOIRAI, a compact yet flexible workflow system designed to carry out the main steps in data processing and analysis of CAGE data. MOIRAI has a graphical interface allowing wet-lab researchers to create, modify and run analysis workflows. Embedded within the workflows are graphical quality control indicators allowing users assess data quality and to quickly spot potential problems. We will describe three main workflows allowing users to map, annotate and perform an expression analysis over multiple samples.Conclusions: Due to the many built in quality control features MOIRAI is especially suitable to support the development of new sequencing based protocols.Availiability: The MOIRAI source code is freely available at http://sourceforge.net/projects/moirai/.

Original language	English
Article number	144
Journal	BMC Bioinformatics
Volume	15
Issue number	1
DOIs	https://doi.org/10.1186/1471-2105-15-144
Publication status	Published - 16 May 2014
Externally published	Yes

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title = "MOIRAI: A compact workflow system for CAGE analysis",

abstract = "Background: Cap analysis of gene expression (CAGE) is a sequencing based technology to capture the 5' ends of RNAs in a biological sample. After mapping, a CAGE peak on the genome indicates the position of an active transcriptional start site (TSS) and the number of reads correspond to its expression level. CAGE is prominently used in both the FANTOM and ENCODE project but presently there is no software package to perform the essential data processing steps. Results: Here we describe MOIRAI, a compact yet flexible workflow system designed to carry out the main steps in data processing and analysis of CAGE data. MOIRAI has a graphical interface allowing wet-lab researchers to create, modify and run analysis workflows. Embedded within the workflows are graphical quality control indicators allowing users assess data quality and to quickly spot potential problems. We will describe three main workflows allowing users to map, annotate and perform an expression analysis over multiple samples.Conclusions: Due to the many built in quality control features MOIRAI is especially suitable to support the development of new sequencing based protocols.Availiability: The MOIRAI source code is freely available at http://sourceforge.net/projects/moirai/.",

keywords = "CAGE, Next generation sequencing, Pipeline",

author = "Akira Hasegawa and Carsten Daub and Piero Carninci and Yoshihide Hayashizaki and Timo Lassmann",

note = "Funding Information: This work was supported by a Research Grant from the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) to the RIKEN Center for Life Science Technologies, a research grant for RIKEN Omics Science Center from MEXT to YH and a grant of the Innovative Cell Biology by Innovative Technology (Cell Innovation Program) from the MEXT, Japan to YH.",

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T2 - A compact workflow system for CAGE analysis

AU - Hasegawa, Akira

AU - Daub, Carsten

AU - Carninci, Piero

AU - Hayashizaki, Yoshihide

AU - Lassmann, Timo

N1 - Funding Information: This work was supported by a Research Grant from the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) to the RIKEN Center for Life Science Technologies, a research grant for RIKEN Omics Science Center from MEXT to YH and a grant of the Innovative Cell Biology by Innovative Technology (Cell Innovation Program) from the MEXT, Japan to YH.

PY - 2014/5/16

Y1 - 2014/5/16

N2 - Background: Cap analysis of gene expression (CAGE) is a sequencing based technology to capture the 5' ends of RNAs in a biological sample. After mapping, a CAGE peak on the genome indicates the position of an active transcriptional start site (TSS) and the number of reads correspond to its expression level. CAGE is prominently used in both the FANTOM and ENCODE project but presently there is no software package to perform the essential data processing steps. Results: Here we describe MOIRAI, a compact yet flexible workflow system designed to carry out the main steps in data processing and analysis of CAGE data. MOIRAI has a graphical interface allowing wet-lab researchers to create, modify and run analysis workflows. Embedded within the workflows are graphical quality control indicators allowing users assess data quality and to quickly spot potential problems. We will describe three main workflows allowing users to map, annotate and perform an expression analysis over multiple samples.Conclusions: Due to the many built in quality control features MOIRAI is especially suitable to support the development of new sequencing based protocols.Availiability: The MOIRAI source code is freely available at http://sourceforge.net/projects/moirai/.

AB - Background: Cap analysis of gene expression (CAGE) is a sequencing based technology to capture the 5' ends of RNAs in a biological sample. After mapping, a CAGE peak on the genome indicates the position of an active transcriptional start site (TSS) and the number of reads correspond to its expression level. CAGE is prominently used in both the FANTOM and ENCODE project but presently there is no software package to perform the essential data processing steps. Results: Here we describe MOIRAI, a compact yet flexible workflow system designed to carry out the main steps in data processing and analysis of CAGE data. MOIRAI has a graphical interface allowing wet-lab researchers to create, modify and run analysis workflows. Embedded within the workflows are graphical quality control indicators allowing users assess data quality and to quickly spot potential problems. We will describe three main workflows allowing users to map, annotate and perform an expression analysis over multiple samples.Conclusions: Due to the many built in quality control features MOIRAI is especially suitable to support the development of new sequencing based protocols.Availiability: The MOIRAI source code is freely available at http://sourceforge.net/projects/moirai/.

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MOIRAI: A compact workflow system for CAGE analysis

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