SUPPA2: fast, accurate, and uncertainty-aware differential splicing analysis across multiple conditions

Juan L. Trincado; Juan C. Entizne; Gerald Hysenaj; Babita Singh; Miha Skalic; David J. Elliott; Eduardo Eyras

doi:10.1186/s13059-018-1417-1

SUPPA2: fast, accurate, and uncertainty-aware differential splicing analysis across multiple conditions

Juan L. Trincado, Juan C. Entizne, Gerald Hysenaj, Babita Singh, Miha Skalic, David J. Elliott, Eduardo Eyras (Lead / Corresponding author)

Plant Sciences

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342 Citations (Scopus)

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Abstract

Despite the many approaches to study differential splicing from RNA-seq, many challenges remain unsolved, including computing capacity and sequencing depth requirements. Here we present SUPPA2, a new method that addresses these challenges, and enables streamlined analysis across multiple conditions taking into account biological variability. Using experimental and simulated data, we show that SUPPA2 achieves higher accuracy compared to other methods, especially at low sequencing depth and short read length. We use SUPPA2 to identify novel Transformer2-regulated exons, novel microexons induced during differentiation of bipolar neurons, and novel intron retention events during erythroblast differentiation.

Original language	English
Article number	40
Pages (from-to)	1-11
Number of pages	11
Journal	Genome Biology
Volume	19
DOIs	https://doi.org/10.1186/s13059-018-1417-1
Publication status	Published - 23 Mar 2018

Keywords

Alternative splicing
Biological variability
Differential splicing
Differentiation
RNA-seq
Uncertainty

ASJC Scopus subject areas

Ecology, Evolution, Behavior and Systematics
Genetics
Cell Biology

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10.1186/s13059-018-1417-1Licence: CC BY

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This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Final published version, 1.51 MBLicence: CC BY

Cite this

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title = "SUPPA2: fast, accurate, and uncertainty-aware differential splicing analysis across multiple conditions",

abstract = "Despite the many approaches to study differential splicing from RNA-seq, many challenges remain unsolved, including computing capacity and sequencing depth requirements. Here we present SUPPA2, a new method that addresses these challenges, and enables streamlined analysis across multiple conditions taking into account biological variability. Using experimental and simulated data, we show that SUPPA2 achieves higher accuracy compared to other methods, especially at low sequencing depth and short read length. We use SUPPA2 to identify novel Transformer2-regulated exons, novel microexons induced during differentiation of bipolar neurons, and novel intron retention events during erythroblast differentiation.",

keywords = "Alternative splicing, Biological variability, Differential splicing, Differentiation, RNA-seq, Uncertainty",

author = "Trincado, {Juan L.} and Entizne, {Juan C.} and Gerald Hysenaj and Babita Singh and Miha Skalic and Elliott, {David J.} and Eduardo Eyras",

note = "This work was supported by the MINECO and FEDER with grants BIO2014–52566-R and BIO2017–85364-R, by AGAUR with grants SGR2014–1121 and SGR2017–1020, by BBSRC (BB/P006612/1), and by Breast Cancer Now (2014NovPR355). GH is a BBSRC-funded PhD student.",

year = "2018",

month = mar,

day = "23",

doi = "10.1186/s13059-018-1417-1",

language = "English",

volume = "19",

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journal = "Genome Biology",

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T2 - fast, accurate, and uncertainty-aware differential splicing analysis across multiple conditions

AU - Trincado, Juan L.

AU - Entizne, Juan C.

AU - Hysenaj, Gerald

AU - Singh, Babita

AU - Skalic, Miha

AU - Elliott, David J.

AU - Eyras, Eduardo

N1 - This work was supported by the MINECO and FEDER with grants BIO2014–52566-R and BIO2017–85364-R, by AGAUR with grants SGR2014–1121 and SGR2017–1020, by BBSRC (BB/P006612/1), and by Breast Cancer Now (2014NovPR355). GH is a BBSRC-funded PhD student.

PY - 2018/3/23

Y1 - 2018/3/23

N2 - Despite the many approaches to study differential splicing from RNA-seq, many challenges remain unsolved, including computing capacity and sequencing depth requirements. Here we present SUPPA2, a new method that addresses these challenges, and enables streamlined analysis across multiple conditions taking into account biological variability. Using experimental and simulated data, we show that SUPPA2 achieves higher accuracy compared to other methods, especially at low sequencing depth and short read length. We use SUPPA2 to identify novel Transformer2-regulated exons, novel microexons induced during differentiation of bipolar neurons, and novel intron retention events during erythroblast differentiation.

AB - Despite the many approaches to study differential splicing from RNA-seq, many challenges remain unsolved, including computing capacity and sequencing depth requirements. Here we present SUPPA2, a new method that addresses these challenges, and enables streamlined analysis across multiple conditions taking into account biological variability. Using experimental and simulated data, we show that SUPPA2 achieves higher accuracy compared to other methods, especially at low sequencing depth and short read length. We use SUPPA2 to identify novel Transformer2-regulated exons, novel microexons induced during differentiation of bipolar neurons, and novel intron retention events during erythroblast differentiation.

KW - Alternative splicing

KW - Biological variability

KW - Differential splicing

KW - Differentiation

KW - RNA-seq

KW - Uncertainty

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SN - 1474-7596

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SP - 1

EP - 11

JO - Genome Biology

JF - Genome Biology

M1 - 40

ER -

SUPPA2: fast, accurate, and uncertainty-aware differential splicing analysis across multiple conditions

Abstract

Keywords

ASJC Scopus subject areas

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