Registration and Call for Abstracts Open for Bioc2024

April 14, 2011

Bioconductors:

We are pleased to announce Bioconductor 2.8, consisting of 466 software packages and more than 500 up-to-date annotation packages. There are 48 new software packages, and many updates and improvements to existing packages. Two software packages that were in the previous version have been removed. Bioconductor 2.8 is compatible with R 2.13.0, and is supported on Linux, 32- and 64-bit Windows, and Mac OS. Visit

http://bioconductor.org

for details and downloads.

Contents

  • Getting Started with Bioconductor 2.8
  • New Software Packages
  • Using Bioconductor in the cloud

Getting Started with Bioconductor 2.8

To install Bioconductor 2.8:

  1. Install R 2.13.0. Bioconductor 2.8 has been designed expressly for this version of R.

  2. Follow the instructions here:

http://bioconductor.org/install/

Please visit http://bioconductor.org for details and downloads.

New Software Packages

There are 48 new packages in this release of Bioconductor.

a4

Automated Affymetrix Array Analysis Umbrella Package

a4Base

Automated Affymetrix Array Analysis Base Package

a4Classif

Automated Affymetrix Array Analysis Classification Package

a4Core

Automated Affymetrix Array Analysis Core Package

a4Preproc

Automated Affymetrix Array Analysis Preprocessing Package

a4Reporting

Automated Affymetrix Array Analysis Reporting Package

AnnotationFuncs

Annotation translation functions

anota

ANalysis Of Translational Activity

chopsticks

The snp.matrix and X.snp.matrix classes

Clonality

Clonality testing

clst

Classification by local similarity threshold

clstutils

Tools for performing taxonomic assignment

clusterProfiler

statistical analysis and visulization of functional profiles for genes and gene clusters

cn.farms

Factor Analysis for copy number estimation

ENVISIONQuery

Retrieval from the ENVISION bioinformatics data portal into R

ExiMiR

R functions for the normalization of Exiqon miRNA array data

flowPhyto

Methods for Continuous Flow Cytometry

flowPlots

analysis plots and data class for gated flow cytometry data

gaia

An R package for genomic analysis of significant chromosomal aberrations

genefu

Relevant Functions for Gene Expression Analysis, Especially in Breast Cancer

genoset

Provides classes similar to ExpressionSet for copy number analysis

GSVA

Gene Set Variation Analysis

ibh

Interaction Based Homogeneity for Evaluating Gene Lists

inveRsion

Inversions in genotype data

IPPD

Isotopic peak pattern deconvolution for Protein Mass Spectrometry by template matching

joda

JODA algorithm for quantifying gene deregulation using knowledge

lol

Lots Of Lasso

mcaGUI

Microbial Community Analysis GUI

mgsa

Model-based gene set analysis

MLP

Mean Log P Analysis

mosaics

MOdel-based one and two Sample Analysis and Inference for ChIP-Seq

MSnbase

Base Functions and Classes for MS-based Proteomics

NCIgraph

Pathways from the NCI Pathways Database

phenoDist

Phenotypic distance measures

phenoTest

Tools to test correlation between gene expression and phenotype

procoil

Prediction of Oligomerization of Coiled Coil Proteins

pvac

PCA-based gene filtering for Affymetrix arrays

qrqc

Quick Read Quality Control

RNAinteract

Estimate Pairwise Interactions from multidimensional features

Rsubread

a super fast, sensitive and accurate read aligner for mapping next-generation sequencing reads

seqbias

Estimation of per-position bias in high-throughput sequencing data

snm

Supervised Normalization of Microarrays

snpStats

SnpMatrix and XSnpMatrix classes and methods

survcomp

Performance Assessment and Comparison for Survival Analysis

TDARACNE

Network reverse engineering from time course data

TEQC

Quality control for target capture experiments

TurboNorm

A fast scatterplot smoother suitable for microarray normalization

Vega

An R package for copy number data segmentation

Using Bioconductor in the cloud

This release features the Bioconductor Amazon Machine Image (AMI), which allows easy access to R and Bioconductor within the Elastic Compute Cloud (EC2). It’s easy to run parallelizable tasks on MPI clusters, run R from within your web browser using RStudio Server, and more. No installation required. Information available at:

http://bioconductor.org/help/bioconductor-cloud-ami/