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Aaron T L Lun

Showing results (1-10 of 38) with videos related to

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BMC Bioinformatics|August 19, 2015
diffHic: a Bioconductor package to detect differential genomic interactions in Hi-C dataAaron T L Lun, Gordon K Smyth
F1000Research|February 27, 2016
From reads to regions: a Bioconductor workflow to detect differential binding in ChIP-seq dataAaron T L Lun, Gordon K Smyth
Nucleic Acids Research|November 19, 2015
csaw: a Bioconductor package for differential binding analysis of ChIP-seq data using sliding windowsAaron T L Lun, Gordon K Smyth
Statistical Applications in Genetics and Molecular Biology|June 11, 2017
No counts, no variance: allowing for loss of degrees of freedom when assessing biological variability from RNA-seq dataAaron T L Lun, Gordon K Smyth
Biostatistics (Oxford, England)|March 24, 2017
Overcoming confounding plate effects in differential expression analyses of single-cell RNA-seq dataAaron T L Lun, John C Marioni
Nucleic Acids Research|May 24, 2014
De novo detection of differentially bound regions for ChIP-seq data using peaks and windows: controlling error rates correctlyAaron T L Lun, Gordon K Smyth
Plos Computational Biology|May 4, 2018
beachmat: A Bioconductor C++ API for accessing high-throughput biological data from a variety of R matrix typesAaron T L Lun, Hervé Pagès, Mike L Smith
Methods in Molecular Biology (Clifton, N.J.)|March 24, 2016
It's DE-licious: A Recipe for Differential Expression Analyses of RNA-seq Experiments Using Quasi-Likelihood Methods in edgeRAaron T L Lun, Yunshun Chen, Gordon K Smyth
F1000Research|September 1, 2016
From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipelineYunshun Chen, Aaron T L Lun, Gordon K Smyth
F1000Research|July 13, 2016
Infrastructure for genomic interactions: Bioconductor classes for Hi-C, ChIA-PET and related experimentsAaron T L Lun, Malcolm Perry, Elizabeth Ing-Simmons
Pageof 4

Showing results (1-10 of 38) with videos related to

Sort By:
Pageof 4
BMC Bioinformatics|August 19, 2015
diffHic: a Bioconductor package to detect differential genomic interactions in Hi-C dataAaron T L Lun, Gordon K Smyth
F1000Research|February 27, 2016
From reads to regions: a Bioconductor workflow to detect differential binding in ChIP-seq dataAaron T L Lun, Gordon K Smyth
Nucleic Acids Research|November 19, 2015
csaw: a Bioconductor package for differential binding analysis of ChIP-seq data using sliding windowsAaron T L Lun, Gordon K Smyth
Statistical Applications in Genetics and Molecular Biology|June 11, 2017
No counts, no variance: allowing for loss of degrees of freedom when assessing biological variability from RNA-seq dataAaron T L Lun, Gordon K Smyth
Biostatistics (Oxford, England)|March 24, 2017
Overcoming confounding plate effects in differential expression analyses of single-cell RNA-seq dataAaron T L Lun, John C Marioni
Nucleic Acids Research|May 24, 2014
De novo detection of differentially bound regions for ChIP-seq data using peaks and windows: controlling error rates correctlyAaron T L Lun, Gordon K Smyth
Plos Computational Biology|May 4, 2018
beachmat: A Bioconductor C++ API for accessing high-throughput biological data from a variety of R matrix typesAaron T L Lun, Hervé Pagès, Mike L Smith
Methods in Molecular Biology (Clifton, N.J.)|March 24, 2016
It's DE-licious: A Recipe for Differential Expression Analyses of RNA-seq Experiments Using Quasi-Likelihood Methods in edgeRAaron T L Lun, Yunshun Chen, Gordon K Smyth
F1000Research|September 1, 2016
From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipelineYunshun Chen, Aaron T L Lun, Gordon K Smyth
F1000Research|July 13, 2016
Infrastructure for genomic interactions: Bioconductor classes for Hi-C, ChIA-PET and related experimentsAaron T L Lun, Malcolm Perry, Elizabeth Ing-Simmons
Pageof 4