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.

Data set containing two complete lists of identified functional interaction partners in Human. Data are derived from Reactome and BioGRID databases.

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.

Fingerprint generation of flow cytometry data, used to facilitate the application of machine learning and datamining tools for flow cytometry.

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 reproduces the systems biology analysis for the data in package Fletcher2013a using RTN.

Build and visualize functional gene and term networks from clustering of enrichment analyses in multiple annotation spaces. The package includes a graphical user interface (GUI) and functions to perform the functional enrichment analysis through DAVID, GeneTerm Linker, gage (GSEA) and topGO.

This package provides a RangedSummarizedExperiment object of read counts in genes for a time course RNA-Seq experiment of fission yeast (Schizosaccharomyces pombe) in response to oxidative stress (1M sorbitol treatment) at 0, 15, 30, 60, 120 and 180 mins. The samples are further divided between a wild-type group and a group with deletion of atf21. The read count matrix was prepared and provided by the author of the study: Leong HS, Dawson K, Wirth C, Li Y, Connolly Y, Smith DL, Wilkinson CR, Miller CJ. "A global non-coding RNA system modulates fission yeast protein levels in response to stress". Nat Commun 2014 May 23;5:3947. PMID: 24853205. GEO: GSE56761.

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.

This package implements functions to find influential TF and target based on different input type. It have five module: Multi-peak multi-gene annotaion(mmPeakAnno module), Calculate regulation potential(calcRP module), Find influential Target based on ChIP-Seq and RNA-Seq data(Find influential Target module), Find influential TF based on different input(Find influential TF module), Calculate peak-gene or peak-peak correlation(peakGeneCor module). And there are also some other useful function like integrate different source information, calculate jaccard similarity for your TF.

Supplying gene expression data sets for the demos of the biclustering method "Factor Analysis for Bicluster Acquisition" (FABIA). The following three data sets are provided: A) breast cancer (van't Veer, Nature, 2002), B) multiple tissues (Su, PNAS, 2002), and C) diffuse large-B-cell lymphoma (Rosenwald, N Engl J Med, 2002).

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).

F-informed MDS is a new multidimensional scaling-based ordination method that configures data distribution based on the F-statistic (i.e., the ratio of dispersion between groups with shared or differing labels).

makeFeatureDbFromUCSC cannot cope with this track, hence a package.

This package provides a function to normalize Illumina Infinium Human Methylation 450 BeadChip (Illumina 450K), correcting for tissue and/or cell type.

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

This package facilitates analysis of both timecourse and steady state flow cytometry experiments. This package was originially developed for quantifying the function of gene regulatory networks in yeast (strain W303) expressing fluorescent reporter proteins using BD Accuri C6 and SORP cytometers. However, the functions are for the most part general and may be adapted for analysis of other organisms using other flow cytometers. Functions in this package facilitate the annotation of flow cytometry data with experimental metadata, as often required for publication and general ease-of-reuse. Functions for creating, saving and loading gate sets are also included. In the past, we have typically generated summary statistics for each flowset for each timepoint and then annotated and analyzed these summary statistics. This method loses a great deal of the power that comes from the large amounts of individual cell data generated in flow cytometry, by essentially collapsing this data into a bulk measurement after subsetting. In addition to these summary functions, this package also contains functions to facilitate annotation and analysis of steady-state or time-lapse data utilizing all of the data collected from the thousands of individual cells in each sample.

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.

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

(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.

Framework providing basic pedigree analysis and plotting utilities as well as a variety of methods to evaluate familial aggregation of traits in large pedigrees.

Image feature data and analysis codes for the Guglielmi, Barry et al. paper describing the application of an optogenetics tools to disrupt Drosophila embryo furrowing.

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.