This is a package to perform the zFPKM transform on RNA-seq FPKM data. This algorithm is based on the publication by Hart et al., 2013 (Pubmed ID 24215113).

This package includes details on variants for each probe on the 450k bead chip for each of the four populations (Asian, American, African and European).

Human Phenotype Ontology (HPO) was developed to create a consistent description of gene products with disease perspectives, and is essential for supporting functional genomics in disease context. Accurate disease descriptions can discover new relationships between genes and disease, and new functions for previous uncharacteried genes and alleles.

This package uses a Bayesian hierarchical model to detect enriched regions from ChIP-chip experiments. The common goal in analyzing this ChIP-chip data is to detect DNA-protein interactions from ChIP-chip experiments. The BAC package has mainly been tested with Affymetrix tiling array data. However, we expect it to work with other platforms (e.g. Agilent, Nimblegen, cDNA, etc.). Note that BAC does not deal with normalization, so you will have to normalize your data beforehand.

The fishpond package contains methods for differential transcript and gene expression analysis of RNA-seq data using inferential replicates for uncertainty of abundance quantification, as generated by Gibbs sampling or bootstrap sampling. Also the package contains a number of utilities for working with Salmon and Alevin quantification files.

This package provides functions and routines useful in the analysis of somatic signatures (cf. L. Alexandrov et al., Nature 2013). In particular, functions to perform a signature analysis with known signatures and a signature analysis on stratified mutational catalogue (SMC) are provided.

This package provides an R interface to Illumina's BaseSpace cloud computing environment, enabling the fast development of data analysis and visualization tools. Besides providing an easy to use set of tools for manipulating the data from BaseSpace, it also facilitates the access to R's rich environment of statistical and data analysis tools.

This is an R package for interfacing with the BIOM format. This package includes basic tools for reading biom-format files, accessing and subsetting data tables from a biom object (which is more complex than a single table), as well as limited support for writing a biom-object back to a biom-format file. The design of this API is intended to match the Python API and other tools included with the biom-format project, but with a decidedly "R flavor" that should be familiar to R users. This includes S4 classes and methods, as well as extensions of common core functions/methods.

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.

The BADER package is intended for the analysis of RNA sequencing data. The algorithm fits a Bayesian hierarchical model for RNA sequencing count data. BADER returns the posterior probability of differential expression for each gene between two groups A and B. The joint posterior distribution of the variables in the model can be returned in the form of posterior samples, which can be used for further down-stream analyses such as gene set enrichment.

This package performs unbiased cell type recognition from single-cell RNA sequencing data, by leveraging reference transcriptomic datasets of pure cell types to infer the cell of origin of each single cell independently.

This package provides full genome sequences for Danio rerio (Zebrafish) as provided by UCSC (danRer10, Sep. 2014) and stored in Biostrings objects.

This package implements the circular binary segmentation (CBS) algorithm to segment DNA copy number data and identify genomic regions with abnormal copy number.

This package provides tools to visualize oligonucleotide patterns and sequence motif occurrences across a large set of sequences centred at a common reference point and sorted by a user defined feature.

CIGAR stands for Concise Idiosyncratic Gapped Alignment Report. CIGAR strings are found in the BAM files produced by most aligners and in the AIRR-formatted output produced by IgBLAST. The cigarillo package provides functions to parse and inspect CIGAR strings, trim them, turn them into ranges of positions relative to the "query space" or "reference space", and project positions or sequences from one space to the other. Note that these operations are low-level operations that the user rarely needs to perform directly. More typically, they are performed behind the scene by higher-level functionality implemented in other packages like Bioconductor packages GenomicAlignments and igblastr.

systemPipeRdata complements the systemPipeR workflow management system (WMS) by offering a collection of pre-designed data analysis workflow templates. These templates are easily accessible and can be readily loaded onto a user's system with a single command. Once loaded, the WMS can immediately utilize these templates for efficient end-to-end analysis, serving a wide range of data analysis needs.

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

The purpose of this package is to identify traits in a dataset that can separate groups. This is done on two levels. First, clustering is performed, using an implementation of sparse K-means. Secondly, the generated clusters are used to predict outcomes of groups of individuals based on their distribution of observations in the different clusters. As certain clusters with separating information will be identified, and these clusters are defined by a sparse number of variables, this method can reduce the complexity of data, to only emphasize the data that actually matters.

This package provides negative binomial models for two-group comparisons and regression inferences from RNA-sequencing data.

The package performs alignment of the amplicon reads, normalizes gathered data, calculates multiple statistics (e.g. cut rates, frameshifts) and presents the results in the form of aggregated reports. Data and statistics can be broken down by experiments, barcodes, user defined groups, guides and amplicons allowing for quick identification of potential problems.

This package provides tools for quality control, analysis and visualization of Illumina DNA methylation array data.

This package aggregateBioVar contains tools to summarize single cell gene expression profiles at the level of subject for single cell RNA-seq data collected from more than one subject (e.g. biological sample or technical replicates). A SingleCellExperiment object is taken as input and converted to a list of SummarizedExperiment objects, where each list element corresponds to an assigned cell type. The SummarizedExperiment objects contain aggregate gene-by-subject count matrices and inter-subject column metadata for individual subjects that can be processed using downstream bulk RNA-seq tools.

This package provides a client for the OmniPath web service and many other resources. It also includes functions to transform and pretty print some of the downloaded data, functions to access a number of other resources. Furthermore, OmnipathR features a close integration with the NicheNet method for ligand activity prediction from transcriptomics data.

The mia package implements tools for microbiome analysis based on the SummarizedExperiment, SingleCellExperiment and TreeSummarizedExperiment infrastructure. Data wrangling and analysis in the context of taxonomic data is the main scope. Additional functions for common task are implemented such as community indices calculation and summarization.