Optimal-transport techniques applied to supervised flow cytometry gating.

Platform Design Info for The Manufacturer's Name MG_U74Cv2.

Platform Design Info for The Manufacturer's Name HC_G110.

PhyloProfile is a tool for exploring complex phylogenetic profiles. Phylogenetic profiles, presence/absence patterns of genes over a set of species, are commonly used to trace the functional and evolutionary history of genes across species and time. With PhyloProfile we can enrich regular phylogenetic profiles with further data like sequence/structure similarity, to make phylogenetic profiling more meaningful. Besides the interactive visualisation powered by R-Shiny, the package offers a set of further analysis features to gain insights like the gene age estimation or core gene identification.

Platform Design Info for The Manufacturer's Name HG_U95C.

Platform Design Info for The Manufacturer's Name RAE230A.

Platform Design Info for Affymetrix Clariom_S_Human_HT.

Platform Design Info for The Manufacturer's Name X_tropicalis.

PrInCE (Predicting Interactomes from Co-Elution) uses a naive Bayes classifier trained on dataset-derived features to recover protein-protein interactions from co-elution chromatogram profiles. This package contains the R implementation of PrInCE.

Platform Design Info for The Manufacturer's Name E_coli_2.

Platform Design Info for Affymetrix HTA-2_0.

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

The package provides `rlang` data masks for the SummarizedExperiment class. The enables the evaluation of unquoted expression in different contexts of the SummarizedExperiment object with optional access to other contexts. The goal for `plyxp` is for evaluation to feel like a data.frame object without ever needing to unwind to a rectangular data.frame.

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

Mapping PSMs back to genome. The package builds SAM file from shotgun proteomics data The package also provides function to prepare annotation from GTF file.

It uses the overlap between enriched and non-enriched datasets to compensate for the bias introduced in global phosphorylation after applying median normalization.

preciseTAD provides functions to predict the location of boundaries of topologically associated domains (TADs) and chromatin loops at base-level resolution. As an input, it takes BED-formatted genomic coordinates of domain boundaries detected from low-resolution Hi-C data, and coordinates of high-resolution genomic annotations from ENCODE or other consortia. preciseTAD employs several feature engineering strategies and resampling techniques to address class imbalance, and trains an optimized random forest model for predicting low-resolution domain boundaries. Translated on a base-level, preciseTAD predicts the probability for each base to be a boundary. Density-based clustering and scalable partitioning techniques are used to detect precise boundary regions and summit points. Compared with low-resolution boundaries, preciseTAD boundaries are highly enriched for CTCF, RAD21, SMC3, and ZNF143 signal and more conserved across cell lines. The pre-trained model can accurately predict boundaries in another cell line using CTCF, RAD21, SMC3, and ZNF143 annotation data for this cell line.

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.

This package provides a Bioconductor data package for the Taylor et al (2010) dataset.

Package to predict protein-protein interaction (PPI) networks in target organisms for which only a view information about PPIs is available. Path2PPI predicts PPI networks based on sets of proteins which can belong to a certain pathway from well-established model organisms. It helps to combine and transfer information of a certain pathway or biological process from several reference organisms to one target organism. Path2PPI only depends on the sequence similarity of the involved proteins.

Platform Design Info for NimbleGen 2006-10-31_rn34_refseq_promoter.

pipeFrame is an R package for building a componentized bioinformatics pipeline. Each step in this pipeline is wrapped in the framework, so the connection among steps is created seamlessly and automatically. Users could focus more on fine-tuning arguments rather than spending a lot of time on transforming file format, passing task outputs to task inputs or installing the dependencies. Componentized step elements can be customized into other new pipelines flexibly as well. This pipeline can be split into several important functional steps, so it is much easier for users to understand the complex arguments from each step rather than parameter combination from the whole pipeline. At the same time, componentized pipeline can restart at the breakpoint and avoid rerunning the whole pipeline, which may save a lot of time for users on pipeline tuning or such issues as power off or process other interrupts.

This package provide simulation based methods for evaluating the statistical power in differential expression analysis from RNA-seq data.

Calculates Probe-level Expression Change Averages (PECA) to identify differential expression in Affymetrix gene expression microarray studies or in proteomic studies using peptide-level mesurements respectively.