Processed RNA-seq data for 1,139 human primary colorectal tissue samples across three phenotypes, including tumor, normal adjacent-to-tumor, and healthy, available as Synapse ID syn22237139 on synapse.org. Data have been parsed into SummarizedExperiment objects available via ExperimentHub to facilitate reproducibility and extension of results from Dampier et al. (PMCID: PMC7386360, PMID: 32764205).

Enrichment of metabolomics data using KEGG entries. Given a set of affected compounds, FELLA suggests affected reactions, enzymes, modules and pathways using label propagation in a knowledge model network. The resulting subnetwork can be visualised and exported.

This package provides a subset of GSE17565 (April et al. 2009) containing 32 FFPE samples of Burkitts Lymphoma and Breast Adenocarcinoma, with a dilution series in technical duplicate.

Raw data objects for the Illumina 450k DNA methylation microarrays.

Raw data objects to be used for cord blood cell proportion estimation in minfi.

This package provides tools for automated sequential gating analogous to the manual gating strategy based on the density of the data.

fourDNData is a data package giving programmatic access to Hi-C contact matrices uniformly processed by the [4DN consortium](https://www.4dnucleome.org/). The matrices are available in the multi-resolution `.mcool` format.

High-performance interval overlap and join operations for IRanges and GenomicRanges'. The package provides deterministic multithreaded overlap computation, reusable subject indexes for repeated queries, and join helpers that keep range metadata in a consistent output grammar.

Detection of rare aberrant splicing events in transcriptome profiles. Read count ratio expectations are modeled by an autoencoder to control for confounding factors in the data. Given these expectations, the ratios are assumed to follow a beta-binomial distribution with a junction specific dispersion. Outlier events are then identified as read-count ratios that deviate significantly from this distribution. FRASER is able to detect alternative splicing, but also intron retention. The package aims to support diagnostics in the field of rare diseases where RNA-seq is performed to identify aberrant splicing defects.

The package obtains parameter estimation, i.e., maximum likelihood estimators (MLE), via the Expectation-Maximization (EM) algorithm for the Finite Mixture of Regression (FMR) models with Normal distribution, and MLE for the Finite Mixture of Accelerated Failure Time Regression (FMAFTR) subject to right censoring with Log-Normal and Weibull distributions via the EM algorithm and the Newton-Raphson algorithm (for Weibull distribution). More importantly, the package obtains the maximum penalized likelihood (MPLE) for both FMR and FMAFTR models (collectively called FMRs). A component-wise tuning parameter selection based on a component-wise BIC is implemented in the package. Furthermore, this package provides Ridge Regression and Elastic Net.

Calculate distances, build phylogenetic trees or perform hierarchical clustering between the samples of a VCF or FASTA file. Functions are implemented in Java-11 and called via rJava. Parallel implementation that operates directly on the VCF or FASTA file for fast execution.

Profile maximum likelihood estimation of parameters for flow cytometry data transformations.

This package provides a package to analyze flow cytometric data using gate information to follow population/community dynamics.

This package provides a set of tools for interacting with the Food-Biomarker Ontology (FOBI). A collection of basic manipulation tools for biological significance analysis, graphs, and text mining strategies for annotating nutritional data.

Biclustering by "Factor Analysis for Bicluster Acquisition" (FABIA). FABIA is a model-based technique for biclustering, that is clustering rows and columns simultaneously. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. It captures realistic non-Gaussian data distributions with heavy tails as observed in gene expression measurements. FABIA utilizes well understood model selection techniques like the EM algorithm and variational approaches and is embedded into a Bayesian framework. FABIA ranks biclusters according to their information content and separates spurious biclusters from true biclusters. The code is written in C.

Base annotation databases for fly, intended ONLY to be used by AnnotationDbi to produce regular annotation packages.

Exposes an annotation databases generated from UCSC by exposing these as FeatureDb objects.

This package provides a fast and automatic clustering to classify the cells into subpopulations based on finding the peaks from the overall density function generated by K-means.

This package provides a collection of raw flow cytometry data for use in vignettes for the flowPloidy package.

Raw data objects to be used for umbilical cord blood cell proportion estimation in minfi and similar packages. The FlowSorted.CordBloodCombined.450k object is based in samples assayed by Bakulski et al, Gervin et al., de Goede et al., and Lin et al.

The FDA Adverse Event Reporting System (FAERS) is a database used for the spontaneous reporting of adverse events and medication errors related to human drugs and therapeutic biological products. faers pacakge serves as the interface between the FAERS database and R. Furthermore, faers pacakge offers a standardized approach for performing pharmacovigilance analysis.

This package provides a novel method for interpreting new transcriptomic datasets through near-instantaneous comparison to public archives without high-performance computing requirements. Through the pre-computed index, users can identify public resources associated with their dataset such as gene sets, MeSH term, and publication. Functions to identify interpretable annotations and intuitive visualization options are implemented in this package.

Offers a set of autoplot methods to visualize tree-like structures (e.g., hierarchical clustering and classification/regression trees) using ggtree'. You can adjust graphical parameters using grammar of graphic syntax and integrate external data to the tree.

Identification of the most likely gene or genes through which variation at a given genomic locus in the human genome acts. The most basic functionality assumes that the closer gene is to the input locus, the more likely the gene is to be causative. Additionally, any empirical data that links genomic regions to genes (e.g. eQTL or genome conformation data) can be used if it is supplied in the UCSC .BED file format.