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Bioconductor Newsletter

posted by Valerie Obenchain, October 2014

Contents

Software Infrastructure

GRCh38 assembly

The GRCh38 human genome assembly is available in Bioconductor as BSgenome TranscriptDb and SNPloc packages.

The GRCh38 assembly includes both a primary assembly (non-redundant haploid assembly) and alternate sequences (alt loci). Alt loci are provided for regions of the genome where variation prevents representation by a single sequence. These regions are not new but have become more prominent as tools for variant detection have matured.

The previous GRCh37 assembly included patch releases tagged as ‘fix’ or ‘novel’. The ‘fix’ patches were incorporated in the primary assembly of GRCh38 while the ‘novel’ patches were moved into the alt loci units. The ‘multi-sequence’ nature of GRCh38 raises questions about how to best work with these alternate sequences with respect to alignment and downstream analysis.

htslib

The samtools library and associated sub-tools play an integral role in the analysis of HTS data. The htslib is the successor of libbam which is currently provided by samtools. Specifically, htslib is a C library for handling high-throughput sequencing data, providing APIs for manipulating SAM, BAM, and CRAM sequence files (similar to but more flexible than the old Samtools API) and for manipulating VCF or BCF variant files.

An implementation of htslib is in the works for Bioconductor and will likely be implemented as stand-alone package. Follow the development on Martin’s GitHub site.

S4Vectors and IRanges split completed

In September Hervé completed the move of non-range based code from IRanges to S4Vectors. The virtual Vector and List classes moved as well as DataFrame, Rle and Hits. Developers using or building on these classes should now import from S4Vectors.

Bioconductor support site

In September the Bioconductor mailing list was replaced with a fork of Biostars and renamed the Bioconductor Support Site. This affects the bioconductor list only; bioc-devel remains unchanged (bioc-devel@r-project.org).

The move was motivated by the volume of list traffic which highlighted the need for advanced searching, tagging and real-time editing of posts. Ideally the new interface will encourage participation from first-time users and simplify topic management.

Marc has imported the last 11+ years of posts to create continuity in the new environment. A FAQ is available to help with site navigation and common tasks such as posting, merging, or tracking topics.

Thanks to Marc and Dan for their work on this.

Developer’s corner

Style markdown documents with BiocStyle

The BiocStyle package provides a fast and easy approach to styling markdown documents in Bioconductor fashion. It includes all standard formatting styles for creating PDF and HTML documents of vignettes, workflows or other project documents. The html version of the package vignette is a demo of the styling and color theme.

The package offers formatting advantages over standard markdown such as automatic centering of figures, improved table display and Latex-compatible math symbols. Custom style sheets can be included by wrapping them in ` BiocStyle:::markdown`:

BiocStyle::markdown(css.files = c(‘my.css’))

Reuse and recycle: The power of import

The Bioconductor infrastructure contains a wealth of tools for HTS analysis. Because these methods and containers exist across a number of packages they can be difficult for new users to discover and for developers to remember when adding new functionality.

The import generic in rtracklayer is one such tool. import reads and parses large file formats such as BED, BAM, BigWig, GFF, Fasta, and Chain files. The methods operate on *File objects (e.g., BamFile) and param (e.g., ScanBamParam) objects, which allow flexible control over the parsing and subsetting of data. Data returned from import are parsed into useful downstream containers such as GRanges or Rle.

import should be the tool of choice when interacting with large files, such as those available in AnnotationHub, or when developing new reading/parsing functions.

biocMultiAssay

During Developer Day at BioC 2014, Levi Waldron’s discussion of his biocMultiAssay project generated a good deal of interest in the community. This effort, led by Levi, Vince, Kasper and Martin, aims to create Bioconductor tools for the efficient manipulation and analysis of multi-assay omics experiments.

The primary motivation is to combine data across multiple experiments for a common group of samples or patients. Goals are to develop classes and methods for the extraction of data subsets defined by indices such as genomic position or gene ID, and to streamline analyses that span multiple genomic data types. The data are high-dimensional assays such as gene and protein expression, copy number, methylation, somatic mutation, or microRNA.

The project has a both a GitHub site with code prototypes and a Google Group for conference call announcements and tracking progress.

Interview with Dr. Janet Young, FHCRC

This section of the newsletter highlights the work of an individual or group in the Bioconductor community. This month we spoke to Janet Young from the Fred Hutchinson Cancer Research Center. Janet is originally from the UK with an undergraduate degree in Natural Sciences from the University of Cambridge, and a PhD in Genetics from University College London. She is currently a Staff Scientist in the Malik lab in the Basic Sciences Division.

Q: To begin would you tell us a bit about yourself?

I joined Fred Hutch in 2000 and worked in the Trask lab first as a post-doc then as a staff scientist. My own research focused on the evolution and transcriptional regulation of mammalian olfactory receptor gene families, but I also helped others with projects to measure genomic copy-number gain and loss in prostate cancer and measurement of methylation levels in healthy human tissues. When Barb (Trask) retired I spent time in the Tapscott lab where we studied how transposable elements might be involved in a form of muscular dystrophy. Currently I provide bioinformatics support to a variety of projects in the Malik lab. The group studies evolutionary biology and genetic conflict, primarily in drosophila, primates and yeast.

Q: How did you get started with Bioconductor?

I started working with Bioconductor when helping others in the Trask and Tapscott labs with various microarray projects. Initially I used R / Bioconductor simply for creating diagnostic plots of microarray data, but soon started using limma and lumi for the analysis steps.

Q: How does Bioconductor fit into your current workflows?

I’m largely using it for analysis of deep sequencing data these days. We use a variety of upstream software such as TopHat, BWA, and GATK. I use Bioconductor for things like differential expression analysis, comparing coverage to look for genomic copy number changes, filtering SNPs, or retrieving and analyzing gene/ annotations. Often I use rtracklayer to export the data for viewing in IGV or the UCSC genome browser. As well as being a great analysis tool itself, Bioconductor acts as the glue to help me integrate results from other tools.

Q: Are there any Bioconductor resources you find particularly useful?

The local classes offered at the Hutch were very helpful. I also like the responsive Q and A on the mailing list. All software has bugs; knowing that the bugs get fixed in a timely manner makes you keep using it. The package vignettes are a valuable ‘stand alone’ resource that help get you going with a specific package or task right away.

Thanks for talking with us and sharing your insights.

Quarterly Project Statistics

The Bioconductor project continues to expand globally. Over the next quarter there are course offerings in Japan, Germany the UK and US. In August 2014, the Latin American Bioconductor LAB foundation held its official inauguration in Ribeirao Preto, Brazil. LAB is a non-profit scientific initiative created to represent and expand Bioconductor to the research community in Latin America and is headed up by Benilton Carvalho and Houtan Noushmehr.

Website traffic

Google analytics reports the following new visitors to the website for the period of July 1 to September 28, 2014:

New vs Returning Users
Sessions
Returning Visitor179,242 (63.81%)
New Visitor101,668 (36.19%)

Overall website traffic by country:

Website Visits by Location
Sessions
Americas118,398 (42.15%)
Europe93,973 (33.45%)
Asia57,744 (20.56%)
Oceania8,015 (2.85%)
Africa2,403 (0.86%)
Other377 (0.13%)

Package downloads

The number of distinct IP downloads of Bioconductor software packages for July, August and September were 36900, 36749, and 36618 respectively for an average of 36756. A full summary of package download stats is available here.

Resources, Courses and Conferences

Search Bioconductor materials by topic

Materials from past courses and conferences have long been available on the Bioconductor web site categorized by conference name and date. At BioC 2014 this year we had several requests for a more refined search of these materials by topic area or key word.

In response, Sonali and Dan have categorized all 2014 materials and implemented a new key word(s) search table interface. The plan is to index all future materials while years prior to 2014 will be available in the old format (see ‘Courses by year’ below the search table).

Publications

If you are looking for resources to enhance your knowledge of working with genomic ranges and sequences in Bioconductor the following publications may be of interest:

Software for Computing and Annotating GenomicRanges
This manuscript describes data structures available in the Bioconductor infrastructure for representing and annotating ranges on the genome. Focus is on the IRanges, GenomicRanges and GeomicFeatures packages which provide support for transcript structures, read alignments and coverage vectors.

Scalable Genomics with R and Bioconductor Strategies for analyzing large genomic data are described and implemented in R and Bioconductor. Topics include scalable processing, summarization and visualization.

Bioconductor 3.0 release

The release of Bioconductor 3.0 is scheduled for October 14. This version will continue to use the current version of R (3.1.1). Visit the website for help updating packages and for a look at the release schedule.

Upcoming events

Practical Course on Analysis of High-Throughput Sequencing Data EBI, Hinxton, UK
October 20-25, 2014

Learning R / Bioconductor for Sequence Analysis FHCRC, Seattle WA, USA October 27-29, 2014

BioC Europe 2015 EMBL, Heidelberg, Germany January 12-15, 2015

Please send comments or questions to Valerie at vobencha@fhcrc.org.