Single-cell RNA-seq (scRNA-seq) is widely used to investigate the composition of complex tissues since the technology allows researchers to define cell-types using unsupervised clustering of the transcriptome. However, due to differences in experimental methods and computational analyses, it is often challenging to directly compare the cells identified in two different experiments. scmap is a method for projecting cells from a scRNA-seq experiment onto the cell-types or individual cells identified in a different experiment.

The aim of TCGAbiolinks is:

1. facilitate GDC open-access data retrieval;

2. prepare the data using the appropriate pre-processing strategies;

3. provide the means to carry out different standard analyses, and;

4. to easily reproduce earlier research results.

In more detail, the package provides multiple methods for analysis (e.g., differential expression analysis, identifying differentially methylated regions) and methods for visualization (e.g., survival plots, volcano plots, starburst plots) in order to easily develop complete analysis pipelines.

This package provides HDF5 storage based methods and functions for manipulation of flow cytometry data.

This package provides functions for bipartite network rewiring through N consecutive switching steps and for the computation of the minimal number of switching steps to be performed in order to maximise the dissimilarity with respect to the original network. It includes functions for the analysis of the introduced randomness across the switching steps and several other routines to analyse the resulting networks and their natural projections.

The package ANF(Affinity Network Fusion) provides methods for affinity matrix construction and fusion as well as spectral clustering. This package is used for complex patient clustering by integrating multi-omic data through affinity network fusion.

This package defines coerce methods for microarray data objects.

This package provides functionality for the compression and decompression of raw bead-level data from the Illumina BeadArray platform.

The dada2 package infers exact amplicon sequence variants (ASVs) from high-throughput amplicon sequencing data, replacing the coarser and less accurate OTU clustering approach. The dada2 pipeline takes as input demultiplexed fastq files, and outputs the sequence variants and their sample-wise abundances after removing substitution and chimera errors. Taxonomic classification is available via a native implementation of the RDP naive Bayesian classifier, and species-level assignment to 16S rRNA gene fragments by exact matching.

This package provides functions for inferring continuous, branching lineage structures in low-dimensional data. Slingshot was designed to model developmental trajectories in single-cell RNA sequencing data and serve as a component in an analysis pipeline after dimensionality reduction and clustering. It is flexible enough to handle arbitrarily many branching events and allows for the incorporation of prior knowledge through supervised graph construction.

Oscope is a oscillatory genes identifier in unsynchronized single cell RNA-seq. This statistical pipeline has been developed to identify and recover the base cycle profiles of oscillating genes in an unsynchronized single cell RNA-seq experiment. The Oscope pipeline includes three modules: a sine model module to search for candidate oscillator pairs; a K-medoids clustering module to cluster candidate oscillators into groups; and an extended nearest insertion module to recover the base cycle order for each oscillator group.

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.

This package provides Affymetrix HG_U95Av2 Array annotation data (chip hgu95av2) assembled using data from public repositories.

This package provides tools for the identification of differentially expressed genes and estimation of the False Discovery Rate (FDR) using both the Significance Analysis of Microarrays (SAM) and the Empirical Bayes Analyses of Microarrays (EBAM).

This package provides an implementation of an algorithm for recalibrating the base quality scores for aligned sequencing data in BAM format.

This package provides efficient containers for storing and manipulating short genomic alignments (typically obtained by aligning short reads to a reference genome). This includes read counting, computing the coverage, junction detection, and working with the nucleotide content of the alignments.

This is a package for saving GenomicRanges, IRanges and related data structures into file artifacts, and loading them back into memory. This is a more portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.

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 implements transcript quantification import from Salmon and alevin with automatic attachment of transcript ranges and release information, and other associated metadata. De novo transcriptomes can be linked to the appropriate sources with linkedTxomes and shared for computational reproducibility.

The polyester package simulates RNA-seq reads from differential expression experiments with replicates. The reads can then be aligned and used to perform comparisons of methods for differential expression.

EBImage provides general purpose functionality for image processing and analysis. In the context of (high-throughput) microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. This allows the automation of such tasks using the R programming language and facilitates the use of other tools in the R environment for signal processing, statistical modeling, machine learning and visualization with image data.

The MBECS provides a set of functions to evaluate and mitigate unwated noise due to processing in batches. To that end it incorporates a host of batch correcting algorithms (BECA) from various packages. In addition it offers a correction and reporting pipeline that provides a preliminary look at the characteristics of a data-set before and after correcting for batch effects.

This package provides a consistent C++ class interface for a variety of commonly used matrix types, including sparse and HDF5-backed matrices.

This is an annotation package for Illumina's EPIC v2.0 methylation arrays. The version 2 covers more than 935K CpG sites in the human genome hg38. It is an update of the original EPIC v1.0 array (i.e., the 850K methylation array).

This package provides a manifest package for Illumina's EPIC v2.0 methylation arrays. The version 2 covers more than 935K CpG sites in the human genome hg38. It is an update of the original EPIC v1.0 array (i.e., the 850K methylation array).