Rapid Development and Distribution of Statistical Tools for High-Throughput Sequencing Data

Software

• BiocStyle
  An R package providing standard formatting styles for vignettes and other Bioconductor documents.
  Authors: Martin Morgan, Andrzej Oleś, Wolfgang Huber
  
  This package was principally developed using RADIANT funding.

• BitSeq
  An R package targeted for transcript expression analysis and differential expression analysis of RNA-seq data in a two stage process. In the first stage it uses Bayesian inference methodology to infer expression levels of individual transcripts from individual RNA-seq libraries. The second stage of BitSeq performs differential expression analysis at the transcript level. Based on stage-1 expression estimates from replicates of multiple conditions, a Log-Normal model is used to infer the condition mean transcript expression level and rank the transcripts with regard to differential expression.
  Authors:Peter Glaus, Antti Honkela, Panagiotis Papastamoulis, Magnus Rattray
  
  This package was partially supported by RADIANT.

• compEpiTools
  R tools for computational epigenomics developed for the analysis, integration and simultaneous visualization of various (epi)genomics data types across multiple genomic regions in multiple samples.
  Authors:Kamal Kishore and Mattia Pelizzola
  
  This package was principally developed using RADIANT funding.

• DESeq2
  An R package for inference of differential expression from count data from high-throughput sequencing assays. Based on generalised linear models of the Negative Binomial family, it provides shrinkage (empirical Bayes) estimates of dispersion and effect estimates (fold changes). Functionalities include outlier robustness, variance stabilising transformations, automated independent filtering, and extensive documentation.
  Authors:Michael Love, Simon Anders, Wolfgang Huber
  
  This package was principally developed using RADIANT funding.

• edgeR
  A general purpose R package for detection of differential features starting from a count table (e.g., RNA-seq, ChIP-seq, SAGE and CAGE, metagenome counts, transcript-level estimated counts). Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models and quasi-likelihood tests.
  Authors: Yunshun Chen, Aaron Lun, Davis McCarthy, Xiaobei Zhou, Mark Robinson, Gordon Smyth
  
  The development of this package was partially supported by RADIANT. Added features include: observation-level weights for robustness.

• flipflop
  An R package aimed to discover which isoforms of a gene are expressed in a given sample together with their abundances, based on RNA-Seq read data. It takes an alignment file in SAM format as input. It can be also used to discover transcripts from several samples simultaneously, increasing statistical power.
  Authors: Elsa Bernard, Laurent Jacob, Julien Mairal and Jean-Philippe Vert
  
  This package was partially developed using RADIANT funding.

• GPy
  Gaussian processes framework for Python.
  Contributors: see https://github.com/SheffieldML/GPy/graphs/contributors
  
  This package was partially supported by RADIANT.

• Hiiragi2013
  This R package contains the experimental data and a complete executable transcript (vignette) of the statistical analysis presented in the paper "Cell-to-cell expression variability followed by signal reinforcement progressively segregates early mouse lineages" by Y. Ohnishi, W. Huber, A. Tsumura, M. Kang, P. Xenopoulos, K. Kurimoto, A. K. Oles, M. J. Arauzo-Bravo, M. Saitou, A.-K. Hadjantonakis and T. Hiiragi; Nature Cell Biology (2014) 16(1): 27-37. doi: 10.1038/ncb2881."
  Authors: Andrzej Oleś, Wolfgang Huber
  
  This package was principally developed using RADIANT funding.

• INSPEcT
  An R package for the integrative analysis of RNA- and 4sU-seq data to study the dynamics of transcriptional regulation. INSPEcT provides gene-level quantification of these rates, and a modeling framework to identify which of these regulatory processes are most likely to explain the observed mRNA and pre-mRNA concentrations. Software performance is tested on a synthetic dataset, instrumental to guide the choice of the modeling parameters and the experimental design.
  Authors: Stefano de Pretis and Mattia Pelizzola
  
  This package was principally developed using RADIANT funding.

• IONiseR
  IONiseR provides tools for the quality assessment of Oxford Nanopore MinION data in R. It extracts summary statistics from a set of fast5 files and can be used either before or after base calling. In addition to standard summaries of the read-types produced, it provides a number of plots for visualizing metrics relative to experiment run time or spatially over the surface of a flowcell.
  Author: Mike Smith
  
  This package was principally developed using RADIANT funding.

• methylPipe
  An R package for memory efficient analysis of base resolution DNA methylation data in both the CpG and non-CpG sequence context. Integration of DNA methylation data derived from any methodology providing base- or low-resolution data.
  Authors: Kamal Kishore and Mattia Pelizzola
  
  This package was principally developed using RADIANT funding.

• PyPol-II
  Python code used to study the dynamicsc of RNA polymerase II transcription from chromatin immunoprecipitation time course data.
  Authors: Ciira wa Maina, Antti Honkela, Filomena Matarese, Korbinian Grote, Hendrik G. Stunnenberg, George Reid, Neil D. Lawrence, Magnus Rattray
  
  This package was principally developed using RADIANT funding.

• RADIANT Genome Browser
  The Radiant Genome Browser is a visualization tool for methyl seq analysed data from the MethylPipe Package, available from Bioconductor (Kishore, 2014).
  Authors: Paolo Pavan and Alessandro Guffanti (Genomnia)
  
  This package was principally developed using RADIANT funding.

• Repitools
  R tools for the analysis of enrichment-based epigenomic data. Features include summarization and visualization of epigenomic data across promoters according to gene expression context, finding regions of differential methylation/binding, and BayMeth for quantifying methylation.
  Authors: Mark Robinson, Dario Strbenac, Aaron Statham, Andrea Riebler
  
  The development of this package was partially supported by RADIANT. Added features include: Baymeth for quantifying methylation from MBD-seq data.

• Hic-Pro
  HiC-Pro is an optimized and flexible pipeline for processing Hi-C data from raw reads to normalized contact maps. HiC-Pro maps reads, detects valid ligation products, performs quality controls and generates intra- and inter-chromosomal contact maps. It includes a fast implementation of the iterative correction method and is based on a memory-efficient data format for Hi-C contact maps. In addition, HiC-Pro can use phased genotype data to build allele-specific contact maps. We applied HiC-Pro to different Hi-C datasets, demonstrating its ability to easily process large data in a reasonable time
  Authors: N. Servant, N. Varoquaux, B.R. Lajoie, E. Viara, C.J. Chen, J-P Vert, J. Dekker, E. Heard, E., Barillot
  
  The development of this package was partially supported by RADIANT.

• Centurion
  Centurion is a Python software to jointly infers the locations of all centromeres in a single yeast genome from Hi-C data by exploiting the centromeres’ tendency to cluster in 3D space
  Authors: N. Varoquaux
  
  The development of this package was partially supported by RADIANT.

• PASTIS
  PASTIS is a Python software to infer the 3D structure of a genome from Hi-C data.
  Authors: N. Varoquaux, F. Ay, W.S Noble, J-P Vert
  
  The development of this package was partially supported by RADIANT.

• DEtime
  DEtime is an R package for two-sample time series analysis using Gaussian process methods. This package implements the Gaussian regression framework for perturbation time point inferrence in a two sample case..
  Authors: J. Yang
  
  The development of this package was principally developed unsing RADIANT funding.