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This package provides examples and code that make use of the different graph related packages produced by Bioconductor.
This package provides R environments for the annotation of microarrays.
The mzR package provides a unified API to the common file formats and parsers available for mass spectrometry data. It comes with a wrapper for the ISB random access parser for mass spectrometry mzXML, mzData and mzML files. The package contains the original code written by the ISB, and a subset of the proteowizard library for mzML and mzIdentML. The netCDF reading code has previously been used in XCMS.
This package provides tools to parse Illumina Sequence Analysis Viewer (SAV) files, access data, and generate QC plots.
This package provides infrastructure for parallel computations distributed by file or by range. User defined mapper and reducer functions provide added flexibility for data combination and manipulation.
This package contains gene-level counts for a collection of public scRNA-seq datasets, provided as SingleCellExperiment objects with cell- and gene-level metadata.
This package offers a statistical framework based on customizable permutation tests to assess the association between genomic region sets and other genomic features.
This package provides a fairly extensive and comprehensive interface to the graph algorithms contained in the Boost library.
This is a package that can be used for quality control of Affymetrix GeneChip expression data and reproducibility analysis of human whole genome chips with the MAQC reference datasets.
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 an R wrapper of the popular bowtie2 sequencing reads aligner and AdapterRemoval, a convenient tool for rapid adapter trimming, identification, and read merging.
This package contains genome-wide annotations for Human, primarily based on mapping using Entrez Gene identifiers.
This package helps with the analysis of array CGH data by detecting of the breakpoints in the genomic profiles and assignment of a status (gain, normal or loss) to each chromosomal regions identified.
This package provides routines for parsing Affymetrix data files based upon file format information. The primary focus is on accessing the CEL and CDF file formats.
AUCell identifies cells with active gene sets (e.g. signatures, gene modules, etc) in single-cell RNA-seq data. AUCell uses the Area Under the Curve (AUC) to calculate whether a critical subset of the input gene set is enriched within the expressed genes for each cell. The distribution of AUC scores across all the cells allows exploring the relative expression of the signature. Since the scoring method is ranking-based, AUCell is independent of the gene expression units and the normalization procedure. In addition, since the cells are evaluated individually, it can easily be applied to bigger datasets, subsetting the expression matrix if needed.
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.
This package provides a quality control pipeline for ChIP-exo/nexus sequencing data.
The tRNA package allows tRNA sequences and structures to be accessed and used for subsetting. In addition, it provides visualization tools to compare feature parameters of multiple tRNA sets and correlate them to additional data. The tRNA package uses GRanges objects as inputs requiring only few additional column data sets.
This package provides a collection of functions for left-censored missing data imputation. Left-censoring is a special case of missing not at random (MNAR) mechanism that generates non-responses in proteomics experiments. The package also contains functions to artificially generate peptide/protein expression data (log-transformed) as random draws from a multivariate Gaussian distribution as well as a function to generate missing data (both randomly and non-randomly). For comparison reasons, the package also contains several wrapper functions for the imputation of non-responses that are missing at random.
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 functionalities for downstream analysis, annotation and visualizaton of alternative splicing events generated by rMATS.
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 provides S4 data structures and basic functions to deal with flow cytometry data.
The project is intended to support the use of sequins(synthetic sequencing spike-in controls) owned and made available by the Garvan Institute of Medical Research. The goal is to provide a standard library for quantitative analysis, modelling, and visualization of spike-in controls.