BackgroundNext-generation sequencing is making it critical to robustly and rapidly handle genomic ranges within standard pipelines. Standard use-cases include annotating sequence ranges with gene or other genomic annotation, merging multiple experiments together and subsequently quantifying and visualizing the overlap. The most widely-used tools for these tasks work at the command-line (e.g. BEDTools) and the small number of available R packages are either slow or have distinct semantics and features from command-line interfaces.ResultsTo provide a robust R-based interface to standard command-line tools for genomic coordinate manipulation, we created bedr. This open-source R package can use either BEDTools or BEDOPS as a back-end and perfor...
The statistical programming language R has become a de facto standard for the analysis of many types...
Abstract Efficient large-scale annotation of genomic intervals is essential for personal genome inte...
Abstract Background High-throughput sequencing often provides a foundation for experimental analyses...
Abstract Background Next-generation sequencing is mak...
We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges a...
Summary: Biological insights can be obtained through computational integration of genomics data sets...
Bedtools allows researchers to quickly compare, contrast, and summarize large genomic dataset and an...
Population genetics and genomics have developed and been treated as independent fields of study desp...
We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges a...
Population genetics and genomics have developed and been treated as independent fields of study desp...
We created a suite of packages to enable analysis of extremely large genomic data sets (potentially ...
Complex genomic analyses often use sequences of simple set operations like intersection, overlap and...
BACKGROUND: The recent advancements in high-throughput sequencing have resulted in the availability ...
Although many computer programs can perform population genetics calculations, they are typically lim...
In an effort to better understand the relationships between organisms, we are trying to map the simi...
The statistical programming language R has become a de facto standard for the analysis of many types...
Abstract Efficient large-scale annotation of genomic intervals is essential for personal genome inte...
Abstract Background High-throughput sequencing often provides a foundation for experimental analyses...
Abstract Background Next-generation sequencing is mak...
We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges a...
Summary: Biological insights can be obtained through computational integration of genomics data sets...
Bedtools allows researchers to quickly compare, contrast, and summarize large genomic dataset and an...
Population genetics and genomics have developed and been treated as independent fields of study desp...
We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges a...
Population genetics and genomics have developed and been treated as independent fields of study desp...
We created a suite of packages to enable analysis of extremely large genomic data sets (potentially ...
Complex genomic analyses often use sequences of simple set operations like intersection, overlap and...
BACKGROUND: The recent advancements in high-throughput sequencing have resulted in the availability ...
Although many computer programs can perform population genetics calculations, they are typically lim...
In an effort to better understand the relationships between organisms, we are trying to map the simi...
The statistical programming language R has become a de facto standard for the analysis of many types...
Abstract Efficient large-scale annotation of genomic intervals is essential for personal genome inte...
Abstract Background High-throughput sequencing often provides a foundation for experimental analyses...