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This package defines coerce methods for microarray data objects.
This package provides an integrated web interface for doing microarray analysis using several of the Bioconductor packages. It is intended to be deployed as a centralized bioinformatics resource for use by many users. Currently only Affymetrix oligonucleotide analysis is supported.
This package represents an integrative method of analyzing multi omics data that conducts enrichment analysis of annotated gene sets. ActivePathways uses a statistical data fusion approach, rationalizes contributing evidence and highlights associated genes, improving systems-level understanding of cellular organization in health and disease.
This package provides a database of SIFT predictions for Homo sapiens dbSNP build 132.
This package provides mappings from Entrez gene identifiers to various annotations for the genome of the model fruit fly Drosophila melanogaster.
The rpx package implements an interface to proteomics data submitted to the ProteomeXchange consortium.
This package provides tools to efficiently represent and manipulate genomic annotations and alignments is playing a central role when it comes to analyzing high-throughput sequencing data (a.k.a. NGS data). The GenomicRanges package defines general purpose containers for storing and manipulating genomic intervals and variables defined along a genome.
This package provides a method to purify a cell type or cell population of interest from heterogeneous datasets. scGate package automatizes marker-based purification of specific cell populations, without requiring training data or reference gene expression profiles. scGate takes as input a gene expression matrix stored in a Seurat object and a GM, consisting of a set of marker genes that define the cell population of interest. It evaluates the strength of signature marker expression in each cell using the rank-based method UCell, and then performs kNN smoothing by calculating the mean UCell score across neighboring cells. kNN-smoothing aims at compensating for the large degree of sparsity in scRNAseq data. Finally, a universal threshold over kNN-smoothed signature scores is applied in binary decision trees generated from the user-provided gating model, to annotate cells as either “pure” or “impure”, with respect to the cell population of interest.
This package provides a dplyr-like interface for interacting with the common Bioconductor classes Ranges and GenomicRanges. By providing a grammatical and consistent way of manipulating these classes their accessibility for new Bioconductor users is hopefully increased.
This package provides a toolset for deciphering and managing biological sequences.
This package provides tools to produce a graphical display, as a heat map, of measures of pairwise linkage disequilibria between SNPs. Users may optionally include the physical locations or genetic map distances of each SNP on the plot.
This is a package for segmentation of allele-specific DNA copy number data and detection of regions with abnormal copy number within each parental chromosome. Both tumor-normal paired and tumor-only analyses are supported.
This package provides genome wide annotation for E coli strain K12, primarily based on mapping using Entrez Gene identifiers. Entrez Gene is National Center for Biotechnology Information (NCBI)’s database for gene-specific information. Entrez Gene maintains records from genomes which have been completely sequenced, which have an active research community to submit gene-specific information, or which are scheduled for intense sequence analysis.
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 AffyRNADegradation package helps with the assessment and correction of RNA degradation effects in Affymetrix 3 expression arrays. The parameter d gives a robust and accurate measure of RNA integrity. The correction removes the probe positional bias, and thus improves comparability of samples that are affected by RNA degradation.
This package provides a one-to-one mapping from gene to "best" probe set for four Affymetrix human gene expression microarrays: hgu95av2, hgu133a, hgu133plus2, and u133x3p. On Affymetrix gene expression microarrays, a single gene may be measured by multiple probe sets. This can present a mild conundrum when attempting to evaluate a gene "signature" that is defined by gene names rather than by specific probe sets. This package also includes the pre-calculated probe set quality scores that were used to define the mapping.
Data package for JASPAR2020. To explore these databases, utilize the TFBSTools package (version 1.23.1 or higher).
This package expands the usethis package with the goal of helping automate the process of creating R packages for Bioconductor or making them Bioconductor-friendly.
The package provides a set of functions to interact with the Google Cloud Platform (GCP) services on the AnVIL platform. The package is designed to work with the AnVIL package. User-level interaction with this package should be minimal.
This is a package for saving SummarizedExperiments 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 sparse nature of single cell epigenomics data can be overruled using probabilistic modelling methods such as Latent Dirichlet Allocation (LDA). This package allows the probabilistic modelling of cis-regulatory topics (cisTopics) from single cell epigenomics data, and includes functionalities to identify cell states based on the contribution of cisTopics and explore the nature and regulatory proteins driving them.
This package provides many functions for computing the nonparametric maximum likelihood estimator (NPMLE) for censored and truncated data.
Monocle performs differential expression and time-series analysis for single-cell expression experiments. It orders individual cells according to progress through a biological process, without knowing ahead of time which genes define progress through that process. Monocle also performs differential expression analysis, clustering, visualization, and other useful tasks on single cell expression data. It is designed to work with RNA-Seq and qPCR data, but could be used with other types as well.
This package provides a quality control pipeline for ChIP-exo/nexus sequencing data.