A Best

AD Norris

B Li

Babita Singh

BS Cole

C Trapnell

D Kim

David J. Elliott

E Lin

E Sebestyén

Eduardo Eyras

ET Wang

Gerald Hysenaj

H Pimentel

J Trincado

J Vaquero-Garcia

JP Venables

Juan C. Entizne

Juan L. Trincado

KK Kim

LA Lowery

M Ankerst

M Ester

M Irimia

M Nowicka

Miha Skalic

NL Bray

PJ Rousseeuw

R Patro

R Zhang

S Anders

S Shen

V Busskamp

Y Katz

YI Li

Genome Biology

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.</p

Trincado, Juan L.

Entizne, Juan C.

Hysenaj, Gerald

Singh, Babita

Skalic, Miha

Elliott, David J.

Eyras, Eduardo

University of Dundee Online Publications

English

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

Juan Trincado (3555821)

Juan Entizne (5004413)

Gerald Hysenaj (5004410)

Babita Singh (811405)

Miha Skalic (5004407)

David Elliott (300679)

Eduardo Eyras (3024)

FigShare

Additional file 3: of SUPPA2: fast, accurate, and uncertainty-aware differential splicing analysis across multiple conditions

Crossref

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

Directory of Open Access Journals

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.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

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

Abstract

Similar works

Full text

Available Versions

University of Dundee Online Publications

FigShare

Crossref

University of Dundee Online Publications

Directory of Open Access Journals

UPF Digital Repository