This package provides a package containing an environment representing the Porcine.cdf file.

FHCRC Nelson Lab pedbarrayv9 Annotation Data (pedbarrayv9) assembled using data from public repositories.

PhantasusLite – a lightweight package with helper functions of general interest extracted from phantasus package. In parituclar it simplifies working with public RNA-seq datasets from GEO by providing access to the remote HSDS repository with the precomputed gene counts from ARCHS4 and DEE2 projects.

PIPETS provides statistically robust analysis for 3'-seq/term-seq data. It utilizes a sliding window approach to apply a Poisson Distribution test to identify genomic positions with termination read coverage that is significantly higher than the surrounding signal. PIPETS then condenses proximal signal and produces strand specific results that contain all significant termination peaks.

This package estimates tumor purity, copy number, and loss of heterozygosity (LOH), and classifies single nucleotide variants (SNVs) by somatic status and clonality. PureCN is designed for targeted short read sequencing data, integrates well with standard somatic variant detection and copy number pipelines, and has support for tumor samples without matching normal samples.

Relative transcript abundance has proven to be a valuable tool for understanding the function of genes in biological systems. For the differential analysis of transcript abundance using RNA sequencing data, the negative binomial model is by far the most frequently adopted. However, common methods that are based on a negative binomial model are not robust to extreme outliers, which we found to be abundant in public datasets. So far, no rigorous and probabilistic methods for detection of outliers have been developed for RNA sequencing data, leaving the identification mostly to visual inspection. Recent advances in Bayesian computation allow large-scale comparison of observed data against its theoretical distribution given in a statistical model. Here we propose ppcseq, a key quality-control tool for identifying transcripts that include outlier data points in differential expression analysis, which do not follow a negative binomial distribution. Applying ppcseq to analyse several publicly available datasets using popular tools, we show that from 3 to 10 percent of differentially abundant transcripts across algorithms and datasets had statistics inflated by the presence of outliers.

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

Platform Design Info for Affymetrix MoGene-2_1-st.

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

This package provides sample files and data for the vignettes of pepStat and Pviz as well as peptide collections for HIV and SIV.

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

Phenotypes comparison based on a pathway consensus approach. Assess the relationship between candidate genes and a set of phenotypes based on additional genes related to the candidate (e.g. Pathways or network neighbors).

This package provides functions for the projection of data into the spaces defined by PCA, CoGAPS, NMF, correlation, and clustering.

The purpose of this package is to perform Statistical Microbiome Analysis on metagenomics results from sequencing data samples. In particular, it supports analyses on the PathoScope generated report files. PathoStat provides various functionalities including Relative Abundance charts, Diversity estimates and plots, tests of Differential Abundance, Time Series visualization, and Core OTU analysis.

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

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

Platform Design Info for Affymetrix RaGene-2_1-st.

This package provides a Bioconductor data package for the Grasso (2012) Prostate Cancer dataset.

Platform Design Info for Affymetrix MoGene-1_1-st-v1.

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

Platform Design Info for Affymetrix Clariom_S_Human.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was Plasmodium\_Anopheles\_probe\_tab.

This package provides a package containing an environment representing the Poplar.cdf file.

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.