This package is used to detect combination of genomic coordinates falling within a user defined window size along with user defined overlap between identified neighboring clusters. It can be used for genomic data where the clusters are built on a specific chromosome or specific strand. Clustering can be performed with a "greedy" option allowing thus the presence of additional sites within the allowed window size.

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.

The biobtreeR package provides an interface to biobtree, a tool which covers large sets of bioinformatics datasets and allows search and chain mappings functionalities.

This package provides a new clustering algorithm, binary cut, for clustering similarity matrices of functional terms is implemented in this package. It also provides functionalities for visualizing, summarizing and comparing the clusterings.

The package r-alevinqc generates quality control reports summarizing the output from an alevin run. The reports can be generated as HTML or PDF files, or as Shiny applications.

This is the core package for the automated analysis of Affymetrix arrays.

MultiAssayExperiment harmonizes data management of multiple assays performed on an overlapping set of specimens. It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of standard data classes for individual assays, and allowing subsetting by genomic ranges or rownames.

This package provides a collection of tools for doing various analyses of single-cell RNA-seq gene expression data, with a focus on quality control.

This package provides an array-like container for convenient access and manipulation of HDF5 datasets. It supports delayed operations and block processing.

RnBeads facilitates comprehensive analysis of various types of DNA methylation data at the genome scale.

This package provides a package that provides a client interface to the Kyoto Encyclopedia of Genes and Genomes (KEGG) REST server.

This package is devoted to analyzing high-throughput data (e.g. gene expression microarray, DNA methylation microarray, RNA-seq) from complex tissues. Current functionalities include

1. detect cell-type specific or cross-cell type differential signals

2. tree-based differential analysis

3. improve variable selection in reference-free deconvolution

4. partial reference-free deconvolution with prior knowledge.

This package provides a method for combining single-cell cytometry datasets, which increases the analytical flexibility and the statistical power of the analyses while minimizing technical noise.

This package contains reads from an RNA-seq experiment between two lung cancer cell lines: H1993 (met) and H2073 (primary). The reads are stored as Fastq files and are meant for use with the TP53Genome object in the gmapR package.

R-escape streamlines gene set enrichment analysis for single-cell RNA sequencing. Using raw count information, Seurat objects, or SingleCellExperiment format, users can perform and visualize GSEA across individual cells.

Data package for JASPAR2020. To explore these databases, utilize the TFBSTools package (version 1.23.1 or higher).

This package provides a function that performs gene-permuting of a gene-set enrichment analysis (GSEA) calculation with or without the absolute filtering. Without filtering, users can perform (original) two-tailed or one-tailed absolute GSEA.

Fit linear models to overdispersed count data. The package can estimate the overdispersion and fit repeated models for matrix input. It is designed to handle large input datasets as they typically occur in single cell RNA-seq experiments.

This package contains data from untargeted mass spectrometry (MS) of modifications to oxidized cysteine (Cys) 34 in human serum albumin (HSA).

This package provides a framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. It imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. It preprocesses data for high-throughput, untargeted analyte profiling.

This package provides the complete genome sequences for Homo sapiens as provided by UCSC (genome hg38, based on assembly GRCh38.p14 since 2023/01/31). The sequences are the same as in BSgenome.Hsapiens.UCSC.hg38, except that each of them has the 4 following masks on top:

1. the mask of assembly gaps (AGAPS mask);

2. the mask of intra-contig ambiguities (AMB mask);

3. the mask of repeats from RepeatMasker (RM mask);

4. the mask of repeats from Tandem Repeats Finder (TRF mask).

Only the AGAPS and AMB masks are "active" by default. The sequences are stored in MaskedDNAString objects.

The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. GOSemSim is an R package for semantic similarity computation among GO terms, sets of GO terms, gene products and gene clusters.

This R package is for multi-sample transcript discovery and quantification using long read RNA-Seq data. You can use bambu after read alignment to obtain expression estimates for known and novel transcripts and genes. The output from bambu can directly be used for visualisation and downstream analysis, such as differential gene expression or transcript usage.

This package exposes an annotation databases generated from UCSC by exposing these as TxDb objects.