This is a package for creating na HTML report of differential expression analyses of count data. It integrates some of the code mentioned in DESeq2 and edgeR vignettes, and report a ranked list of genes according to the fold changes mean and variability for each selected gene.

The package is able to read bead-level data (raw TIFFs and text files) output by BeadScan as well as bead-summary data from BeadStudio. Methods for quality assessment and low-level analysis are provided.

This package implements a new RNA-Seq analysis method and integrates two modules: a basic model for pairwise comparison and a linear model for complex design. RNA-Seq quantifies gene expression with reads count, which usually consists of conditions (or treatments) and several replicates for each condition. This software infers differential expression directly by the counts difference between conditions. It assumes that the sum counts difference between conditions follow a negative binomial distribution. In addition, ABSSeq moderates the fold-changes by two steps: the expression level and gene-specific dispersion, that might facilitate the gene ranking by fold-change and visualization.

This package provides a one-to-one mapping from gene to "best" probe set for four Affymetrix human gene expression microarrays: hgu95av2, hgu133a, hgu133plus2, and u133x3p. On Affymetrix gene expression microarrays, a single gene may be measured by multiple probe sets. This can present a mild conundrum when attempting to evaluate a gene "signature" that is defined by gene names rather than by specific probe sets. This package also includes the pre-calculated probe set quality scores that were used to define the mapping.

This package ADAMgui is a graphical user interface (GUI) for the ADAM package. The ADAMgui package provides two shiny-based applications that allows the user to study the output of the ADAM package files through different plots. It's possible, for example, to choose a specific group of functionally associated genes (GFAG) and observe the gene expression behavior with the plots created with the GFAGtargetUi function. Features such as differential expression and fold change can be easily seen with aid of the plots made with the GFAGpathUi function.

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.

This package provides tools to calculate functional similarities based on the pathways described on KEGG and REACTOME or in gene sets. These similarities can be calculated for pathways or gene sets, genes, or clusters and combined with other similarities. They can be used to improve networks, gene selection, testing relationships, and so on.

This package provides raw beta values from 36 samples across 3 groups from Illumina 450k methylation arrays.

This package offers functionality for taking methtuple or Bismark outputs to calculate ASM scores and compute DAMEs regions. It also offers nice visualization of methyl-circle plots.

This is a package for de novo identification and extraction of differentially methylated regions (DMRs) from the human genome using Whole Genome Bisulfite Sequencing (WGBS) and Illumina Infinium Array (450K and EPIC) data. It provides functionality for filtering probes possibly confounded by SNPs and cross-hybridisation. It includes GRanges generation and plotting functions.

This is a package for noise-robust soft clustering of gene expression time-series data (including a graphical user interface).

This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g. VCF, bed, wig) and other resources from standard locations (e.g. UCSC, Ensembl) can be discovered. The resource includes metadata about each resource, e.g., a textual description, tags, and date of modification. The client creates and manages a local cache of files retrieved by the user, helping with quick and reproducible access.

This package provides Ion Trap positive ionization mode data in mzML file format. It includes a subset from 500-850 m/z and 1190-1310 seconds, including MS2 and MS3, intensity threshold 100.000; extracts from FTICR Apex III, m/z 400-450; a subset of UPLC - Bruker micrOTOFq data, both mzML and mz5; LC-MSMS and MRM files from proteomics experiments; and PSI mzIdentML example files for various search engines.

This package implements tools for delayed computation of a matrix of residuals after fitting a linear model to each column of an input matrix. It also supports partial computation of residuals where selected factors are to be preserved in the output matrix. It implements a number of efficient methods for operating on the delayed matrix of residuals, most notably matrix multiplication and calculation of row/column sums or means.

The package provides functionality that can be useful for the analysis of the high-density tiling microarray data (such as from Affymetrix genechips) or for measuring the transcript abundance and the architecture. The main functionalities of the package are:

1. the class segmentation for representing partitionings of a linear series of data;

2. the function segment for fitting piecewise constant models using a dynamic programming algorithm that is both fast and exact;

3. the function confint for calculating confidence intervals using the strucchange package;

4. the function plotAlongChrom for generating pretty plots;

5. the function normalizeByReference for probe-sequence dependent response adjustment from a (set of) reference hybridizations.

R-dsb improves protein expression analysis in droplet-based single-cell studies. The package specifically addresses noise in raw protein UMI counts from methods like CITE-seq. It identifies and removes two main sources of noise—protein-specific noise from unbound antibodies and droplet/cell-specific noise. The package is applicable to various methods, including CITE-seq, REAP-seq, ASAP-seq, TEA-seq, and Mission Bioplatform data. Check the vignette for tutorials on integrating dsb with Seurat and Bioconductor, and using dsb in Python.

The S4Arrays package defines the Array virtual class to be extended by other S4 classes that wish to implement a container with an array-like semantic. It also provides:

1. low-level functionality meant to help the developer of such container to implement basic operations like display, subsetting, or coercion of their array-like objects to an ordinary matrix or array, and

2. a framework that facilitates block processing of array-like objects (typically on-disk objects).

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.

This package r-chromvar determines variation in chromatin accessibility across sets of annotations or peaks. r-chromvar is designed primarily for single-cell or sparse chromatin accessibility data like single cell assay for transposase-accessible chromatin using sequencing (scATAC-seq or sparse bulk ATAC or deoxyribonuclease sequence (DNAse-seq) experiments.

Independent Surrogate Variable Analysis is an algorithm for feature selection in the presence of potential confounding factors (see Teschendorff AE et al 2011, <doi: 10.1093/bioinformatics/btr171>).

This package provides a universal, user friendly, single-cell and bulk RNA sequencing visualization toolkit that allows highly customizable creation of color blindness friendly, publication-quality figures. dittoSeq accepts both SingleCellExperiment (SCE) and Seurat objects, as well as the import and usage, via conversion to an SCE, of SummarizedExperiment or DGEList bulk data. Visualizations include dimensionality reduction plots, heatmaps, scatterplots, percent composition or expression across groups, and more. Customizations range from size and title adjustments to automatic generation of annotations for heatmaps, overlay of trajectory analysis onto any dimensionality reduciton plot, hidden data overlay upon cursor hovering via ggplotly conversion, and many more. All with simple, discrete inputs. Color blindness friendliness is powered by legend adjustments (enlarged keys), and by allowing the use of shapes or letter-overlay in addition to the carefully selected codedittoColors().

This package provides the output of running various transcript abundance quantifiers on a set of 6 RNA-seq samples from the GEUVADIS project. The quantifiers were Cufflinks, RSEM, kallisto, Salmon and Sailfish. Alevin example output is also included.

MDQC is a multivariate quality assessment method for microarrays based on quality control (QC) reports. The Mahalanobis distance of an array's quality attributes is used to measure the similarity of the quality of that array against the quality of the other arrays. Then, arrays with unusually high distances can be flagged as potentially low-quality.

This package provides full genome sequences for Homo sapiens as provided by UCSC (hg19, February 2009) and stored in Biostrings objects.