Feature rankings can be distorted by a single case in the context of high-dimensional data. The cases exerts abnormal influence on feature rankings are called influential points (IPs). The package aims at detecting IPs based on case deletion and quantifies their effects by measuring the rank changes (DOI:10.48550/arXiv.2303.10516). The package applies a novel rank comparing measure using the adaptive weights that stress the top-ranked important features and adjust the weights to ranking properties.

The package Fletcher2013a contains time-course gene expression data from MCF-7 cells treated under different experimental systems in order to perturb FGFR2 signalling. The data comes from Fletcher et al. (Nature Comms 4:2464, 2013) where further details about the background and the experimental design of the study can be found.

Compiled HumanMethylation27 and HumanMethylation450 annotations.

Per-channel variance stabilization from a collection of flow cytometry samples by Bertlett test for homogeneity of variances. The approach is applicable to microarrays data as well.

High-throughput extensible toolkit for processing FASTQ data. The goal of this package is to empower users to quickly build out small programmatic kernels to define any FASTQ processing task they may need. Builds on Intel TBB’s flow graph to orchestrate concurrent I/O and data processing; throughput can be as fast as compression and disk speed allows. The package also ships with a suite of predefined kernels for common FASTQ tasks.

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).

Package that implements the FGGA algorithm. This package provides a hierarchical ensemble method based ob factor graphs for the consistent cross-ontology annotation of protein coding genes. FGGA embodies elements of predicate logic, communication theory, supervised learning and inference in graphical models.

flowcatchR is a set of tools to analyze in vivo microscopy imaging data, focused on tracking flowing blood cells. It guides the steps from segmentation to calculation of features, filtering out particles not of interest, providing also a set of utilities to help checking the quality of the performed operations (e.g. how good the segmentation was). It allows investigating the issue of tracking flowing cells such as in blood vessels, to categorize the particles in flowing, rolling and adherent. This classification is applied in the study of phenomena such as hemostasis and study of thrombosis development. Moreover, flowcatchR presents an integrated workflow solution, based on the integration with a Shiny App and Jupyter notebooks, which is delivered alongside the package, and can enable fully reproducible bioimage analysis in the R environment.

FANTOM4 promoters, liftOver'ed from hg18 to hg19, CpGs quantified.

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 funOmics package ggregates or summarizes omics data into higher level functional representations such as GO terms gene sets or KEGG metabolic pathways. The aggregated data matrix represents functional activity scores that facilitate the analysis of functional molecular sets while allowing to reduce dimensionality and provide easier and faster biological interpretations. Coordinated functional activity scores can be as informative as single molecules!

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

An R package that tests for enrichment and depletion of user-defined pathways using a Fisher's exact test. The method is designed for versatile pathway annotation formats (eg. gmt, txt, xlsx) to allow the user to run pathway analysis on custom annotations. This package is also integrated with Cytoscape to provide network-based pathway visualization that enhances the interpretability of the results.

This package contains two main functions. The first is fdr.ma which takes normalized expression data array, experimental design and computes adjusted p-values It returns the fdr adjusted p-values and plots, according to the methods described in (Reiner, Yekutieli and Benjamini 2002). The second, is fdr.gui() which creates a simple graphic user interface to access fdr.ma.

(f-divergence Cutoff Index), is to find DEGs in the transcriptomic & proteomic data, and identify DEGs by computing the difference between the distribution of fold-changes for the control-control and remaining (non-differential) case-control gene expression ratio data. fCI provides several advantages compared to existing methods.

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.

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

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.

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.

This package provides a package to analyze flow cytometric data of complex microbial communities based on histogram images.

Identifies maximal differential cell populations in flow cytometry data taking into account dependencies between cell populations; flowGraph calculates and plots SpecEnr abundance scores given cell population cell counts.

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.

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.

flowGate adds an interactive Shiny app to allow manual GUI-based gating of flow cytometry data in R. Using flowGate, you can draw 1D and 2D span/rectangle gates, quadrant gates, and polygon gates on flow cytometry data by interactively drawing the gates on a plot of your data, rather than by specifying gate coordinates. This package is especially geared toward wet-lab cytometerists looking to take advantage of R for cytometry analysis, without necessarily having a lot of R experience.