The package contains 8 BAM files, 1 per sequencing run. Each BAM file was obtained by aligning the reads (paired-end) to the full hg19 genome with TopHat2, and then subsetting to keep only alignments on chr14. See accession number E-MTAB-1147 in the ArrayExpress database for details about the experiment, including links to the published study (by Zarnack et al., 2012) and to the FASTQ files.

Cicero computes putative cis-regulatory maps from single-cell chromatin accessibility data. It also extends the monocle package for use in chromatin accessibility data.

This package provides data from 3 technical replicates of the cell line GM12878 from the EPIC methylation array.

This package provides an annotation database of Mouse genome data. It is derived from the UCSC mm9 genome and based on the "knownGene" track. The database is exposed as a TxDb object.

This package provides a package for RNA basepair analysis, including the visualization of basepairs as arc diagrams for easy comparison and annotation of sequence and structure. Arc diagrams can additionally be projected onto multiple sequence alignments to assess basepair conservation and covariation, with numerical methods for computing statistics for each.

This package provides the full genome sequences for Bos taurus (UCSC version bosTau8).

This package provides an R wrapper around the popular bowtie short read aligner and around SpliceMap, a de novo splice junction discovery and alignment tool.

This package provides tools to visualize read coverage from sequencing experiments together with genomic annotations (genes, transcripts, peaks). Introns of long transcripts can be rescaled to a fixed length for better visualization of exonic read coverage.

This package provides a collection of functions designed for analyzing deconvolution of the bulk sample(s) using an atlas of reference omic signature profiles and a user-selected model. Users are given the option to create or extend a reference atlas and,also simulate the desired size of the bulk signature profile of the reference cell types. The package includes the cell-type-specific methylation atlas and, Illumina Epic B5 probe ids that can be used in deconvolution. Additionally, we included BSmeth2Probe, to make mapping WGBS data to their probe IDs easier.

This package supports the computation of an F-test for the association between expression values and clinical entities. In many cases a two way layout with gene and a dichotomous group as factors will be considered. However, adjustment for other covariates and the analysis of arbitrary clinical variables, interactions, gene co-expression, time series data and so on is also possible. The test is carried out by comparison of corresponding linear models via the extra sum of squares principle.

This package provides a differential abundance analysis for the comparison of two or more conditions. Useful for analyzing data from standard RNA-seq or meta-RNA-seq assays as well as selected and unselected values from in-vitro sequence selections. Uses a Dirichlet-multinomial model to infer abundance from counts, optimized for three or more experimental replicates. The method infers biological and sampling variation to calculate the expected false discovery rate, given the variation, based on a Wilcoxon Rank Sum test and Welch's t-test, a Kruskal-Wallis test, a generalized linear model, or a correlation test. All tests report p-values and Benjamini-Hochberg corrected p-values. ALDEx2 also calculates expected standardized effect sizes for paired or unpaired study designs.

The ggbio package extends and specializes the grammar of graphics for biological data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries.

This package wraps common clustering algorithms in an easily extended S4 framework. Backends are implemented for hierarchical, k-means and graph-based clustering. Several utilities are also provided to compare and evaluate clustering results.

AS (alternative splicing) is a common mechanism of post-transcriptional gene regulation in eukaryotic organisms that expands the functional and regulatory diversity of a single gene by generating multiple mRNA isoforms that encode structurally and functionally distinct proteins. ASpli is an integrative pipeline and user-friendly R package that facilitates the analysis of changes in both annotated and novel AS events. ASpli integrates several independent signals in order to deal with the complexity that might arise in splicing patterns.

This package is able to perform an automatic or interactive quality control on FCS data acquired using flow cytometry instruments. By evaluating three different properties:

1. flow rate

2. signal acquisition, and

3. dynamic range,

the quality control enables the detection and removal of anomalies.

This package is designed to facilitate comparison of automated gating methods against manual gating done in flowJo. This package allows you to import basic flowJo workspaces into BioConductor and replicate the gating from flowJo using the flowCore functionality. Gating hierarchies, groups of samples, compensation, and transformation are performed so that the output matches the flowJo analysis.

This package provides tools for calculating the Reproducibility-Optimized Test Statistic (ROTS) for differential testing in omics data.

The scDblFinder package gathers various methods for the detection and handling of doublets/multiplets in single-cell RNA sequencing data (i.e. multiple cells captured within the same droplet or reaction volume). It includes methods formerly found in the scran package, and the new fast and comprehensive scDblFinder method.

IONiseR provides tools for the quality assessment of Oxford Nanopore MinION data. It extracts summary statistics from a set of fast5 files and can be used either before or after base calling. In addition to standard summaries of the read-types produced, it provides a number of plots for visualising metrics relative to experiment run time or spatially over the surface of a flowcell.

This package contains functions and classes that are needed by the arrayCGH packages.

The affyPLM provides a package that extends and improves the functionality of the base affy package. For speeding up the runs, it includes routines that make heavy use of compiled code. The central focus is on implementation of methods for fitting probe-level models and tools using these models. PLM based quality assessment tools are also provided.

This package provides an extensive toolset for the characterization and visualization of a wide range of mutational patterns in SNV base substitution data.

This is a representation of public golub data with some covariate data of provenance unknown to the maintainer at present; it now employs ExpressionSet format.

This package provides methods to infer clonal tree configuration for a population of cells using single-cell RNA-seq data (scRNA-seq), and possibly other data modalities. Methods are also provided to assign cells to inferred clones and explore differences in gene expression between clones. These methods can flexibly integrate information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. A flexible beta-binomial error model that accounts for stochastic dropout events as well as systematic allelic imbalance is used.