Search Results - "SMYTH, K"

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  1. 1

    The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads by Liao, Yang, Smyth, Gordon K, Shi, Wei

    Published in Nucleic acids research (07-05-2019)
    “…Abstract We present Rsubread, a Bioconductor software package that provides high-performance alignment and read counting functions for RNA-seq reads. Rsubread…”
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  2. 2

    featureCounts: an efficient general purpose program for assigning sequence reads to genomic features by Liao, Yang, Smyth, Gordon K, Shi, Wei

    Published in Bioinformatics (01-04-2014)
    “…Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the…”
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  3. 3

    The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote by Liao, Yang, Smyth, Gordon K, Shi, Wei

    Published in Nucleic acids research (01-05-2013)
    “…Read alignment is an ongoing challenge for the analysis of data from sequencing technologies. This article proposes an elegantly simple multi-seed strategy,…”
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  4. 4

    ELDA: Extreme limiting dilution analysis for comparing depleted and enriched populations in stem cell and other assays by Hu, Yifang, Smyth, Gordon K.

    Published in Journal of immunological methods (15-08-2009)
    “…ELDA is a software application for limiting dilution analysis (LDA), with particular attention to the needs of stem cell assays. It is the first limiting…”
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  5. 5

    csaw: a Bioconductor package for differential binding analysis of ChIP-seq data using sliding windows by Lun, Aaron T L, Smyth, Gordon K

    Published in Nucleic acids research (18-03-2016)
    “…Chromatin immunoprecipitation with massively parallel sequencing (ChIP-seq) is widely used to identify binding sites for a target protein in the genome. An…”
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  6. 6

    edgeR: a Bioconductor package for differential expression analysis of digital gene expression data by Robinson, Mark D., McCarthy, Davis J., Smyth, Gordon K.

    Published in Bioinformatics (01-01-2010)
    “…It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics…”
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  7. 7

    ROBUST HYPERPARAMETER ESTIMATION PROTECTS AGAINST HYPERVARIABLE GENES AND IMPROVES POWER TO DETECT DIFFERENTIAL EXPRESSION by Phipso, Belinda, Lee, Stanley, Majewski, Ian J., Alexander, Warren S., Smyth, Gordon K.

    Published in The annals of applied statistics (01-06-2016)
    “…One of the most common analysis tasks in genomic research is to identify genes that are differentially expressed (DE) between experimental conditions…”
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  8. 8

    voom: precision weights unlock linear model analysis tools for RNA-seq read counts by Law, Charity W, Chen, Yunshun, Shi, Wei, Smyth, Gordon K

    Published in Genome biology (03-02-2014)
    “…New normal linear modeling strategies are presented for analyzing read counts from RNA-seq experiments. The voom method estimates the mean-variance…”
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  9. 9

    Testing significance relative to a fold-change threshold is a TREAT by McCarthy, Davis J., Smyth, Gordon K.

    Published in Bioinformatics (15-03-2009)
    “…Motivation: Statistical methods are used to test for the differential expression of genes in microarray experiments. The most widely used methods successfully…”
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  10. 10

    Gene ontology analysis for RNA-seq: accounting for selection bias by Young, Matthew D, Wakefield, Matthew J, Smyth, Gordon K, Oshlack, Alicia

    Published in Genome biology (04-02-2010)
    “…We present GOseq, an application for performing Gene Ontology (GO) analysis on RNA-seq data. GO analysis is widely used to reduce complexity and highlight…”
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  11. 11

    Moderated statistical tests for assessing differences in tag abundance by Robinson, Mark D., Smyth, Gordon K.

    Published in Bioinformatics (01-11-2007)
    “…Motivation: Digital gene expression (DGE) technologies measure gene expression by counting sequence tags. They are sensitive technologies for measuring gene…”
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  12. 12

    Count-based differential expression analysis of RNA sequencing data using R and Bioconductor by Anders, Simon, McCarthy, Davis J, Chen, Yunshun, Okoniewski, Michal, Smyth, Gordon K, Huber, Wolfgang, Robinson, Mark D

    Published in Nature protocols (01-09-2013)
    “…RNA sequencing (RNA-seq) has been rapidly adopted for the profiling of transcriptomes in many areas of biology, including studies into gene regulation,…”
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  13. 13
  14. 14

    Blimp-1 controls plasma cell function through the regulation of immunoglobulin secretion and the unfolded protein response by Tellier, Julie, Shi, Wei, Minnich, Martina, Liao, Yang, Crawford, Simon, Smyth, Gordon K, Kallies, Axel, Busslinger, Meinrad, Nutt, Stephen L

    Published in Nature immunology (01-03-2016)
    “…The transcription factor Blimp-1 is required for the differentiation of activated B cells into plasmablasts. Nutt and colleagues show that plasma cells need…”
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  15. 15

    From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline [version 2; peer review: 5 approved] by Chen, Yunshun, Lun, Aaron T. L, Smyth, Gordon K

    Published in F1000 research (2016)
    “…In recent years, RNA sequencing (RNA-seq) has become a very widely used technology for profiling gene expression. One of the most common aims of RNA-seq…”
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  16. 16

    Optimizing the noise versus bias trade-off for Illumina whole genome expression BeadChips by Shi, Wei, Oshlack, Alicia, Smyth, Gordon K

    Published in Nucleic acids research (01-12-2010)
    “…Five strategies for pre-processing intensities from Illumina expression BeadChips are assessed from the point of view of precision and bias. The strategies…”
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  17. 17

    diffHic: a Bioconductor package to detect differential genomic interactions in Hi-C data by Lun, Aaron T L, Smyth, Gordon K

    Published in BMC bioinformatics (19-08-2015)
    “…Chromatin conformation capture with high-throughput sequencing (Hi-C) is a technique that measures the in vivo intensity of interactions between all pairs of…”
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  18. 18

    Transcriptional profiling of mouse B cell terminal differentiation defines a signature for antibody-secreting plasma cells by Shi, Wei, Liao, Yang, Willis, Simon N, Taubenheim, Nadine, Inouye, Michael, Tarlinton, David M, Smyth, Gordon K, Hodgkin, Philip D, Nutt, Stephen L, Corcoran, Lynn M

    Published in Nature immunology (01-06-2015)
    “…The process of B cell differentiation into plasma cells involves dramatic cellular reprogramming. Corcoran and colleagues profile the transcriptome of all…”
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  19. 19

    Use of within-array replicate spots for assessing differential expression in microarray experiments by Smyth, Gordon K., Michaud, Joëlle, Scott, Hamish S.

    Published in Bioinformatics (01-05-2005)
    “…Motivation: Spotted arrays are often printed with probes in duplicate or triplicate, but current methods for assessing differential expression are not able to…”
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  20. 20

    Differential co-expression-based detection of conditional relationships in transcriptional data: comparative analysis and application to breast cancer by Bhuva, Dharmesh D, Cursons, Joseph, Smyth, Gordon K, Davis, Melissa J

    Published in Genome Biology (14-11-2019)
    “…Elucidation of regulatory networks, including identification of regulatory mechanisms specific to a given biological context, is a key aim in systems biology…”
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