July, Dana-Farber Cancer Institute, Boston, MA, USA
This conference highlights current developments within and beyond Bioconductor. Morning scientific talks and afternoon practicals provide conference participants with insights and tools required for the analysis and comprehension of high-throughput genomic data. This year's conference is at the Dana-Farber Cancer Institute Longwood Campus, in Boston, MA. Visit the Conference Registration Page for more information.
July, Boston, USA
The Bioconductor project is a leading development and analysis environment for bioinformatics, supported by a core of dedicated programmers and a broad contributing scientific community. The project is evolving rapidly along with sequencing technologies and the quantity of available genome annotation, and this workshop provides ISMB attendees with the inside track on the most recent and upcoming trends in Bioconductor. The workshop will begin with a high-level tour of leading Bioconductor packages and capabilities across a wide variety of disciplines, then will cover current advances for 1) accessing genomic annotation data such as ENCODE and the UCSC genome browser through the AnnotationHub architecture, 2) data and algorithm element designs for integrative analysis of large genomic data and annotation that permit scalable resource utilization at run-time, and 3) analysis of RNA-seq data. The workshop features the project leader Martin Morgan, co-founders and Core member Vince Carey, Advisory Board member Levi Waldron, and post-doctoral fellow Michael Love (Rafael Irizarry lab). This workshop is intended for a wide audience and will be valuable for beginner to experienced analysts of genomic data.
June, useR! 2014, UCLA, USA,
DNA sequence analysis generates large volumes of data presenting challenging bioinformatic and statistical problems. This tutorial introduces Bioconductor packages and work flows for the analysis of sequence data. We learn about approaches for efficiently manipulating sequences and alignments, and introduce common work flows and the unique statistical challenges associated with 'RNAseq', variant annotation, and other experiments. The emphasis is on exploratory analysis, and the analysis of designed experiments.The workshop emphasizes orientation within the Bioconductor milieu; we will touch on the Biostrings, ShortRead, GenomicRanges, GenomicAlignments, DESeq2, and VariantAnnotation, and other packages, with short exercises to illustrate the functionality of each package.
June, Brixen-Bressanone, Italy
This one-week intensive course teaches current approaches in the statistical and computational analysis of large-scale experiments in biology. The course focuses on the methods for downstream analyses of high-throughput sequencing experiments including RNA sequencing (differential expression), DNA sequencing (variant calling), ChIP-Seq. Lectures also cover essentials including statistical testing, linear models, machine learning, visualisation and bioinformatic annotation. Emphasis is given to practical problem solving skills using open-source software from the Bioconductor, CRAN and other projects. The course is intended for researchers who have basic familiarity with the experimental technologies and the biology of the genome, and who are interested in developing their own, advanced data analyses using a scripting environment. The four practical sessions of the course will require simple script understanding in the computer language R. A tutorial on the required more advanced features of R will be provided, students are advised to familiarize themselves with the very basics of R beforehand. (Consider one of the many online resources or books, e.g. R-Intro from the R Project, Germán Rodríguez, R-Studio.
February, Seattle, USA
Introduction to Bioconductor for Sequence Analysis introduces users with some R experience to Bioconductor, especially working with high-throughput sequence data. Day 1 develops core R and Bioconductor concepts for working with large and complicated data. Participants will become familiar with data classes, packages, and scripting and programming concepts that are important for common and integrated work flows in Bioconductor. Day 2 will put these skills to use for the analysis of RNAseq differential expression data, including initial quality assessment, pre-processing, differential representation, annotation, and visualization. The course involves a combination of presentations and hands-on exercises; participants should come prepared with a modern laptop with wireless internet access.
January, Ribeirao Preto, Sao Paulo, Brazil
R / Bioconductor material for portions of a course on the analysis and comprehension of high-throughput sequence data. Additional material available from the course web site and other course instructors.