This package calculates probabilistic pathway scores using gene expression data. Gene expression values are aggregated into pathway-based scores using Bayesian network representations of biological pathways.

Platform Design Info for Affymetrix GuiGene-1_1-st.

This package contains R functions to predict biological variables to from placnetal DNA methylation data generated from infinium arrays. This includes inferring ethnicity/ancestry, gestational age, and cell composition from placental DNA methylation array (450k/850k) data.

Platform Design Info for Affymetrix RaGene-1_0-st-v1.

Platform Design Info for Affymetrix EquGene-1_0-st.

Probabilistic inference of ChIP-Seq using an empirical Bayes mixture model approach.

Platform Design Info for Affymetrix OviGene-1_0-st.

The Parallel Mixed Model (PMM) approach is suitable for hit selection and cross-comparison of RNAi screens generated in experiments that are performed in parallel under several conditions. For example, we could think of the measurements or readouts from cells under RNAi knock-down, which are infected with several pathogens or which are grown from different cell lines.

Platform Design Info for The Manufacturer's Name HG_U95Av2.

Platform Design Info for The Manufacturer's Name Pae_G1a.

Platform Design Info for Affymetrix SoyGene-1_1-st.

pathlinkR is an R package designed to facilitate analysis of RNA-Seq results. Specifically, our aim with pathlinkR was to provide a number of tools which take a list of DE genes and perform different analyses on them, aiding with the interpretation of results. Functions are included to perform pathway enrichment, with muliplte databases supported, and tools for visualizing these results. Genes can also be used to create and plot protein-protein interaction networks, all from inside of R.

This package provides a Bioconductor data package for the Stockholm dataset.

Platform Design Info for Affymetrix DroGene-1_1-st.

Platform Design Info for The Manufacturer's Name Tomato.

Platform Design Info for Affymetrix ChiGene-1_1-st.

Platform Design Info for The Manufacturer's Name YG_S98.

Store UCSC phastCons conservation scores for the human genome (hg38) calculated from multiple alignments with other 99 vertebrate species.

The package allows for predicting whether a coiled coil sequence (amino acid sequence plus heptad register) is more likely to form a dimer or more likely to form a trimer. Additionally to the prediction itself, a prediction profile is computed which allows for determining the strengths to which the individual residues are indicative for either class. Prediction profiles can also be visualized as curves or heatmaps.

Platform Design Info for NimbleGen 081229_hg18_promoter_medip_hx1.

Platform Design Info for Affymetrix Mapping250K_Nsp.

Platform Design Info for The Manufacturer's Name HG-U133_Plus_2.

This package implements a suite of methods to preprocess data from PTR-TOF-MS instruments (HDF5 format) and generates the sample by features table of peak intensities in addition to the sample and feature metadata (as a singl<e ExpressionSet object for subsequent statistical analysis). This package also permit usefull tools for cohorts management as analyzing data progressively, visualization tools and quality control. The steps include calibration, expiration detection, peak detection and quantification, feature alignment, missing value imputation and feature annotation. Applications to exhaled air and cell culture in headspace are described in the vignettes and examples. This package was used for data analysis of Gassin Delyle study on adults undergoing invasive mechanical ventilation in the intensive care unit due to severe COVID-19 or non-COVID-19 acute respiratory distress syndrome (ARDS), and permit to identfy four potentiel biomarquers of the infection.

This package provides a fast, convenient tool to identify the TSSs of miRNAs by integrating the data of H3K4me3 and Pol II as well as combining the conservation level and sequence feature, provided within both command-line and graphical interfaces, which achieves a better performance than the previous non-cell-specific methods on miRNA TSSs.