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This package provides an array-like container for convenient access and manipulation of HDF5 datasets. It supports delayed operations and block processing.
The necessary external data to run the flowWorkspace and openCyto vignette is found in this package. This data package contains two flowJo, one diva xml workspace and the associated fcs files as well as three GatingSets for testing the flowWorkspace, openCyto and CytoML packages.
This R package is providing functions to perform geneset significance analysis over simple cross-sectional data between 2 and 5 phenotypes of interest.
This package provides a client for the gypsum REST API (https://gypsum.artifactdb.com), a cloud-based file store in the ArtifactDB ecosystem. This package provides functions for uploads, downloads, and various administrative and management tasks. Check out the documentation at https://github.com/ArtifactDB/gypsum-worker for more details.
This package provides many functions for computing the nonparametric maximum likelihood estimator (NPMLE) for censored and truncated data.
This package provides a subset of BAM files untreated1.bam (single-end reads) and untreated3.bam (paired-end reads) from "Pasilla" experiment (Pasilla knock-down by Brooks et al., Genome Research 2011). See the vignette in the pasilla data package for how BAM files untreated1.bam and untreated3.bam were obtained from the RNA-Seq read sequence data that is provided by NCBI Gene Expression Omnibus under accession numbers GSM461176 to GSM461181. It also contains the DNA sequence for fly chromosome 4 to which the reads can be mapped.
This package contains default datasets used by the Bioconductor package biscuiteer.
This package implements `import()` and `export()` standard generics for importing and exporting biological data formats. `import()` supports whole-file as well as chunk-wise iterative import. The `import()` interface optionally provides a standard mechanism for 'lazy' access via `filter()` (on row or element-like components of the file resource), `select()` (on column-like components of the file resource) and `collect()`. The `import()` interface optionally provides transparent access to remote (e.g. via https) as well as local access. Developers can register a file extension, e.g., `.loom` for dispatch from character-based URIs to specific `import()` / `export()` methods based on classes representing file types, e.g., `LoomFile()`.
This package implements two functions. One of them reads an Affymetrix CDF and creates a hash table environment containing the location/probe set membership mapping. The other one creates a package that automatically loads that environment.
This package provides a fairly extensive and comprehensive interface to the graph algorithms contained in the Boost library.
This package provides a visual and interactive web application using RStudio's shiny package. Bad quality samples are detected using sample-dependent and sample-independent controls present on the array and user adjustable thresholds. In depth exploration of bad quality samples can be performed using several interactive diagnostic plots of the quality control probes present on the array. Furthermore, the impact of any batch effect provided by the user can be explored.
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.
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 the lengths of mRNA transcripts for a number of genomes and gene ID formats, largely based on the UCSC table browser.
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.
EBarrays provides tools for the analysis of replicated/unreplicated microarray data.
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.
This package provides fully Bayesian mixture models for differential gene expression.
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>).
The airpart package identifies sets of genes displaying differential cell-type-specific allelic imbalance across cell types or states, utilizing single-cell allelic counts. It makes use of a generalized fused lasso with binomial observations of allelic counts to partition cell types by their allelic imbalance. Alternatively, a nonparametric method for partitioning cell types is offered. The package includes a number of visualizations and quality control functions for examining single cell allelic imbalance datasets.
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 extracts tandem mass spectrometry (MS/MS) ID data from mzIdentML (leveraging the mzID package) or text files. After collating the search results from multiple datasets it assesses their identification quality and optimize filtering criteria to achieve the maximum number of identifications while not exceeding a specified false discovery rate. It also contains a number of utilities to explore the MS/MS results and assess missed and irregular enzymatic cleavages, mass measurement accuracy, etc.
This package provides mappings from Entrez gene identifiers to various annotations for the genome of the model mouse Mus musculus.
TrackViewer offers multi-omics analysis with web based tracks and lollipops. Visualize mapped reads along with annotation as track layers for NGS datasets such as ChIP-seq, RNA-seq, miRNA-seq, DNA-seq, SNPs and methylation data.