Cargando…

Modeling Exon-Specific Bias Distribution Improves the Analysis of RNA-Seq Data

RNA-seq technology has become an important tool for quantifying the gene and transcript expression in transcriptome study. The two major difficulties for the gene and transcript expression quantification are the read mapping ambiguity and the overdispersion of the read distribution along reference s...

Descripción completa

Detalles Bibliográficos
Autores principales:	Liu, Xuejun, Zhang, Li, Chen, Songcan
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Public Library of Science 2015
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4598124/ https://www.ncbi.nlm.nih.gov/pubmed/26448625 http://dx.doi.org/10.1371/journal.pone.0140032

Ejemplares similares

Improving RNA-Seq expression estimation by modeling isoform- and exon-specific read sequencing rate
por: Liu, Xuejun, et al.
Publicado: (2015)

Estimation of data-specific constitutive exons with RNA-Seq data
por: Patrick, Ellis, et al.
Publicado: (2013)

Detecting differential usage of exons from RNA-seq data
por: Anders, Simon, et al.
Publicado: (2012)

Sequence-specific bias correction for RNA-seq data using recurrent neural networks
por: Zhang, Yao-zhong, et al.
Publicado: (2017)

Evaluating the bias of circRNA predictions from total RNA-Seq data
por: Wang, Jinzeng, et al.
Publicado: (2017)

Recurrent functional misinterpretation of RNA-seq data caused by sample-specific gene length bias
por: Mandelboum, Shir, et al.
Publicado: (2019)

Detection of Alu Exonization Events in Human Frontal Cortex From RNA-Seq Data
por: Florea, Liliana, et al.
Publicado: (2021)

Exon-level estimates improve the detection of differentially expressed genes in RNA-seq studies
por: Mehmood, Arfa, et al.
Publicado: (2021)

The exon quantification pipeline (EQP): a comprehensive approach to the quantification of gene, exon and junction expression from RNA-seq data
por: Schuierer, Sven, et al.
Publicado: (2016)

Improving RNA-Seq expression estimates by correcting for fragment bias
por: Roberts, Adam, et al.
Publicado: (2011)

Union Exon Based Approach for RNA-Seq Gene Quantification: To Be or Not to Be?
por: Zhao, Shanrong, et al.
Publicado: (2015)

Quantitative RNA-seq meta-analysis of alternative exon usage in C. elegans
por: Tourasse, Nicolas J., et al.
Publicado: (2017)

The identification of switch-like alternative splicing exons among multiple samples with RNA-Seq data
por: Qin, Zhiyi, et al.
Publicado: (2017)

Transcript length bias in RNA-seq data confounds systems biology
por: Oshlack, Alicia, et al.
Publicado: (2009)

PDEGEM: Modeling non-uniform read distribution in RNA-Seq data
por: Xia, Yuchao, et al.
Publicado: (2015)

Toblerone: detecting exon deletion events in cancer using RNA-seq
por: Lonsdale, Andrew, et al.
Publicado: (2023)

Biased exon/intron distribution of cryptic and de novo 3′ splice sites
por: Královičová, Jana, et al.
Publicado: (2005)

PennSeq: accurate isoform-specific gene expression quantification in RNA-Seq by modeling non-uniform read distribution
por: Hu, Yu, et al.
Publicado: (2014)

Gene ontology analysis for RNA-seq: accounting for selection bias
por: Young, Matthew D, et al.
Publicado: (2010)

Analysis of chromosomal aberrations and recombination by allelic bias in RNA-Seq
por: Weissbein, Uri, et al.
Publicado: (2016)

Gene set analysis controlling for length bias in RNA-seq experiments
por: Ren, Xing, et al.
Publicado: (2017)

A two-parameter generalized Poisson model to improve the analysis of RNA-seq data
por: Srivastava, Sudeep, et al.
Publicado: (2010)

Dynamic Model for RNA-seq Data Analysis
por: Li, Lerong, et al.
Publicado: (2015)

Anti-bias training for (sc)RNA-seq: experimental and computational approaches to improve precision
por: Davies, Philip, et al.
Publicado: (2021)

Adjusting for gene-specific covariates to improve RNA-seq analysis
por: Jeon, Hyeongseon, et al.
Publicado: (2023)

Freeze-quenched maize mesophyll and bundle sheath separation uncovers bias in previous tissue-specific RNA-Seq data
por: Denton, Alisandra K, et al.
Publicado: (2017)

Prediction of alternative isoforms from exon expression levels in RNA-Seq experiments
por: Richard, Hugues, et al.
Publicado: (2010)

Male-Biased Genes in Catfish as Revealed by RNA-Seq Analysis of the Testis Transcriptome
por: Sun, Fanyue, et al.
Publicado: (2013)

Gene dispersion is the key determinant of the read count bias in differential expression analysis of RNA-seq data
por: Yoon, Sora, et al.
Publicado: (2017)

A new approach to bias correction in RNA-Seq
por: Jones, Daniel C., et al.
Publicado: (2012)

IVT-seq reveals extreme bias in RNA sequencing
por: Lahens, Nicholas F, et al.
Publicado: (2014)

scRNA‐seq data analysis method to improve analysis performance
por: Lu, Junru, et al.
Publicado: (2023)

Sources of bias in measures of allele-specific expression derived from RNA-seq data aligned to a single reference genome
por: Stevenson, Kraig R, et al.
Publicado: (2013)

Corrigendum: Freeze-quenched maize mesophyll and bundle sheath separation uncovers bias in previous tissue-specific RNA-Seq data
por: Denton, Alisandra K, et al.
Publicado: (2018)

Reproducible inference of transcription factor footprints in ATAC-seq and DNase-seq datasets using protocol-specific bias modeling
por: Karabacak Calviello, Aslıhan, et al.
Publicado: (2019)

Analysis and Prediction of Exon Skipping Events from RNA-Seq with Sequence Information Using Rotation Forest
por: Du, Xiuquan, et al.
Publicado: (2017)

Correction of transposase sequence bias in ATAC-seq data with rule ensemble modeling
por: Wolpe, Jacob B, et al.
Publicado: (2023)

Simultaneous SNP identification and assessment of allele-specific bias from ChIP-seq data
por: Ni, Yunyun, et al.
Publicado: (2012)

Detection of single nucleotide variations in expressed exons of the human genome using RNA-Seq
por: Chepelev, Iouri, et al.
Publicado: (2009)

Modeling Site-Specific Nucleotide Biases Affecting Himar1 Transposon Insertion Frequencies in TnSeq Data Sets
por: Choudhery, Sanjeevani, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_6qq7tmmls60sln8dvj6s728d28