• Publications
  • Influence
Bioconductor: open software development for computational biology and bioinformatics
TLDR
Details of the aims and methods of Bioconductor, the collaborative creation of extensible software for computational biology and bioinformatics, and current challenges are described.
ggplot2
  • R. Irizarry
  • Introduction to Data Science
  • 12 November 2019
Exploration, normalization, and summaries of high density oligonucleotide array probe level data.
TLDR
There is no obvious downside to using RMA and attaching a standard error (SE) to this quantity using a linear model which removes probe-specific affinities, and the exploratory data analyses of the probe level data motivate a new summary measure that is a robust multi-array average (RMA) of background-adjusted, normalized, and log-transformed PM values.
Salmon provides fast and bias-aware quantification of transcript expression
TLDR
Salmon is the first transcriptome-wide quantifier to correct for fragment GC-content bias, which substantially improves the accuracy of abundance estimates and the sensitivity of subsequent differential expression analysis.
A comparison of normalization methods for high density oligonucleotide array data based on variance and bias
TLDR
Three methods of performing normalization at the probe intensity level are presented: a one number scaling based algorithm and a method that uses a non-linear normalizing relation by comparing the variability and bias of an expression measure and the simplest and quickest complete data method is found to perform favorably.
Summaries of Affymetrix GeneChip probe level data.
TLDR
It is found that the performance of the current version of the default expression measure provided by Affymetrix Microarray Suite can be significantly improved by the use of probe level summaries derived from empirically motivated statistical models.
Orchestrating high-throughput genomic analysis with Bioconductor
TLDR
An overview of Bioconductor, an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology, which comprises 934 interoperable packages contributed by a large, diverse community of scientists.
affy - analysis of Affymetrix GeneChip data at the probe level
TLDR
The affy package is an R package of functions and classes for the analysis of oligonucleotide arrays manufactured by Affymetrix that provides the user with extreme flexibility when carrying out an analysis and make it possible to access and manipulate probe intensity data.
A Model-Based Background Adjustment for Oligonucleotide Expression Arrays
TLDR
The default ad hoc adjustment, provided as part of the Affymetrix system, can be improved through the use of estimators derived from a statistical model that uses probe sequence information, which greatly improves the performance of the technology in various practical applications.
The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores
TLDR
Methylation changes in cancer are at sites that vary normally in tissue differentiation, consistent with the epigenetic progenitor model of cancer, which proposes that epigenetic alterations affecting tissue-specific differentiation are the predominant mechanism by which epigenetic changes cause cancer.
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