Gene ontology analysis for RNA-seq: accounting for selection bias
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Matthew D. Young | G. Smyth | M. Kotlyar | Kristen Fortney | A. Oshlack | M. Wakefield | Matthew J. Wakefield | Kristen Fortney | Max Kotlyar | Igor Jurisica | I. Jurisica | Gordon K. Smyth | Alicia Oshlack
[1] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[2] M. Ashburner,et al. Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.
[3] D. Feldman,et al. The development of androgen-independent prostate cancer , 2001, Nature Reviews Cancer.
[4] May D. Wang,et al. GoMiner: a resource for biological interpretation of genomic and proteomic data , 2003, Genome Biology.
[5] Robert Tibshirani,et al. Transcriptional programs activated by exposure of human prostate cancer cells to androgen , 2002, Genome Biology.
[6] David Martin,et al. GOToolBox: functional analysis of gene datasets based on Gene Ontology , 2004, Genome Biology.
[7] T. Speed,et al. GOstat: find statistically overrepresented Gene Ontologies within a group of genes. , 2004, Bioinformatics.
[8] Gordon K. Smyth,et al. limma: Linear Models for Microarray Data , 2005 .
[9] Pablo Tamayo,et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[10] Rafael A. Irizarry,et al. Bioinformatics and Computational Biology Solutions using R and Bioconductor , 2005 .
[11] Paul G. Spirakis,et al. Weighted random sampling with a reservoir , 2006, Inf. Process. Lett..
[12] Thomas Lengauer,et al. Improved scoring of functional groups from gene expression data by decorrelating GO graph structure , 2006, Bioinform..
[13] Zhen Su,et al. EasyGO: Gene Ontology-based annotation and functional enrichment analysis tool for agronomical species , 2007, BMC Genomics.
[14] Mark D. Robinson,et al. Moderated statistical tests for assessing differences in tag abundance , 2007, Bioinform..
[15] R. Vossen,et al. Deep sequencing-based expression analysis shows major advances in robustness, resolution and inter-lab portability over five microarray platforms , 2008, Nucleic acids research.
[16] M. Stephens,et al. RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. , 2008, Genome research.
[17] Eric T. Wang,et al. Alternative Isoform Regulation in Human Tissue Transcriptomes , 2008, Nature.
[18] Brad T. Sherman,et al. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.
[19] E. Mardis,et al. Transcriptome-Wide Identification of Novel Imprinted Genes in Neonatal Mouse Brain , 2008, PloS one.
[20] M. Robinson,et al. Small-sample estimation of negative binomial dispersion, with applications to SAGE data. , 2007, Biostatistics.
[21] Gene W. Yeo,et al. Determination of tag density required for digital transcriptome analysis: Application to an androgen-sensitive prostate cancer model , 2008, Proceedings of the National Academy of Sciences.
[22] Cole Trapnell,et al. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome , 2009, Genome Biology.
[23] B. Williams,et al. Mapping and quantifying mammalian transcriptomes by RNA-Seq , 2008, Nature Methods.
[24] C. Pipper,et al. [''R"--project for statistical computing]. , 2008, Ugeskrift for laeger.
[25] P. Khaitovich,et al. BMC Genomics BioMed Central Methodology article Estimating accuracy of RNA-Seq and microarrays with proteomics , 2022 .
[26] M. Robinson,et al. A scaling normalization method for differential expression analysis of RNA-seq data , 2010, Genome Biology.
[27] Mats Ensterö,et al. Large-scale mRNA sequencing determines global regulation of RNA editing during brain development. , 2009, Genome research.
[28] A. Oshlack,et al. Transcript length bias in RNA-seq data confounds systems biology , 2009, Biology Direct.
[29] Mark D. Robinson,et al. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data , 2009, Bioinform..