The kallisto | bustools pipeline is a fast and modular set of tools to convert single cell RNA-seq reads in fastq files into gene count or transcript compatibility counts (TCC) matrices for downstream analysis. Central to this pipeline is the barcode, UMI, and set (BUS) file format. This package serves the following purposes: First, this package allows users to manipulate BUS format files as data frames in R and then convert them into gene count or TCC matrices. Furthermore, since R and Rcpp code is easier to handle than pure C++ code, users are encouraged to tweak the source code of this package to experiment with new uses of BUS format and different ways to convert the BUS file into gene count matrix. Second, this package can conveniently generate files required to generate gene count matrices for spliced and unspliced transcripts for RNA velocity. Here biotypes can be filtered and scaffolds and haplotypes can be removed, and the filtered transcriptome can be extracted and written to disk. Third, this package implements utility functions to get transcripts and associated genes required to convert BUS files to gene count matrices, to write the transcript to gene information in the format required by bustools, and to read output of bustools into R as sparses matrices.

Precise knowledge on the binding sites of an RNA-binding protein (RBP) is key to understand (post-) transcriptional regulatory processes. Here we present a workflow that describes how exact binding sites can be defined from iCLIP data. The package provides functions for binding site definition and result visualization. For details please see the vignette.

Full genome sequences for Rattus norvegicus (Rat) as provided by UCSC (rn4, Nov. 2004) and stored in Biostrings objects. The sequences are the same as in BSgenome.Rnorvegicus.UCSC.rn4, except that each of them has the 4 following masks on top: (1) the mask of assembly gaps (AGAPS mask), (2) the mask of intra-contig ambiguities (AMB mask), (3) the mask of repeats from RepeatMasker (RM mask), and (4) the mask of repeats from Tandem Repeats Finder (TRF mask). Only the AGAPS and AMB masks are "active" by default.

This is a probabilistic modelling pipeline for computing per- nucleotide posterior probabilities of modification from the data collected in structure probing experiments. The model supports multiple experimental replicates and empirically corrects coverage- and sequence-dependent biases. The model utilises the measure of a "drop-off rate" for each nucleotide, which is compared between replicates through a log-ratio (LDR). The LDRs between control replicates define a null distribution of variability in drop-off rate observed by chance and LDRs between treatment and control replicates gets compared to this distribution. Resulting empirical p-values (probability of being "drawn" from the null distribution) are used as observations in a Hidden Markov Model with a Beta-Uniform Mixture model used as an emission model. The resulting posterior probabilities indicate the probability of a nucleotide of having being modified in a structure probing experiment.

Full genome sequences for Taeniopygia guttata (Zebra finch) as provided by UCSC (taeGut2, Feb. 2013) and stored in Biostrings objects.

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 Bsubtilis\_probe\_tab.

BEER implements a Bayesian model for analyzing phage-immunoprecipitation sequencing (PhIP-seq) data. Given a PhIPData object, BEER returns posterior probabilities of enriched antibody responses, point estimates for the relative fold-change in comparison to negative control samples, and more. Additionally, BEER provides a convenient implementation for using edgeR to identify enriched antibody responses.

Full genome sequences for Arabidopsis thaliana as provided by TAIR (snapshot from April 23, 2008) and stored in Biostrings objects.

Full genome sequences for Sus scrofa (Pig) as provided by UCSC (susScr11, Feb. 2017) and stored in Biostrings objects.

Full genome sequences for Homo sapiens (Human) as provided by UCSC (hg38, based on GRCh38.p12) with minor alleles injected from dbSNP151, and stored in Biostrings objects. Full genome sequences for Homo sapiens (Human) as provided by UCSC (hg38, based on GRCh38.p12) with minor alleles injected from dbSNP151, and stored in Biostrings objects. Only common single nucleotide variants (SNVs) with at least one alternate allele with frequency greater than 0.01 were considered. For SNVs with more than 1 alternate allele, the most frequent allele was chosen as the minor allele to be injected into the reference genome.

The BioPlex package implements access to the BioPlex protein-protein interaction networks and related resources from within R. Besides protein-protein interaction networks for HEK293 and HCT116 cells, this includes access to CORUM protein complex data, and transcriptome and proteome data for the two cell lines. Functionality focuses on importing the various data resources and storing them in dedicated Bioconductor data structures, as a foundation for integrative downstream analysis of the data.

Full reference nuclear genome sequences for Vitis vinifera subsp. vinifera PN40024 (derived from Pinot Noir and close to homozygosity after 6-9 rounds of selfing) as assembled by the IGGP (version 12Xv2) and available at the URGI (INRA).

Full genome sequences for Bos taurus (Cow) as provided by UCSC (genome bosTau9) and stored in Biostrings objects. The sequences are the same as in BSgenome.Btaurus.UCSC.bosTau9, except that each of them has the 4 following masks on top: (1) the mask of assembly gaps (AGAPS mask), (2) the mask of intra-contig ambiguities (AMB mask), (3) the mask of repeats from RepeatMasker (RM mask), and (4) the mask of repeats from Tandem Repeats Finder (TRF mask). Only the AGAPS and AMB masks are "active" by default.

This R package provide functions that are used in the BREW3R workflow. This mainly contains a function that extend a gtf as GRanges using information from another gtf (also as GRanges). The process allows to extend gene annotation without increasing the overlap between gene ids.

Full genome sequences for Canis lupus familiaris (Dog) as provided by UCSC (canFam3, Sep. 2011) and stored in Biostrings objects. The sequences are the same as in BSgenome.Cfamiliaris.UCSC.canFam3, except that each of them has the 4 following masks on top: (1) the mask of assembly gaps (AGAPS mask), (2) the mask of intra-contig ambiguities (AMB mask), (3) the mask of repeats from RepeatMasker (RM mask), and (4) the mask of repeats from Tandem Repeats Finder (TRF mask). Only the AGAPS and AMB masks are "active" by default.

Full genome sequences for Canis lupus familiaris (Dog) as provided by UCSC (canFam2, May 2005) and stored in Biostrings objects.

Full genome sequences for Pan troglodytes (Chimp) as provided by UCSC (panTro3, Oct. 2010) and stored in Biostrings objects.

Full genome sequences for Chlamydomonas reinhardtii (v5.6) as provided by JGI and stored in Biostrings objects. The data in this package is public. See citation("BSgenome.Creinhardtii.JGI.v5.6") for how to cite in publications.

Full genome sequences for Pan troglodytes (Chimp) as provided by UCSC (panTro2, Mar. 2006) and stored in Biostrings objects.

The bugsigdbr package implements convenient access to bugsigdb.org from within R/Bioconductor. The goal of the package is to facilitate import of BugSigDB data into R/Bioconductor, provide utilities for extracting microbe signatures, and enable export of the extracted signatures to plain text files in standard file formats such as GMT.

This package provides a set of tools to forge BSgenome data packages. Supersedes the old seed-based tools from the BSgenome software package. This package allows the user to create a BSgenome data package in one function call, simplifying the old seed-based process.

Full genome sequences for Pan troglodytes (Chimp) as provided by UCSC (panTro5, May 2016) and stored in Biostrings objects.

This package provides efficient batch-effect adjustment of data with missing values. BERT orders all batch effect correction to a tree of pairwise computations. BERT allows parallelization over sub-trees.

Extends beachmat to initialize tatami matrices from TileDB-backed arrays. This allows C++ code in downstream packages to directly call the TileDB C/C++ library to access array data, without the need for block processing via DelayedArray. Developers only need to import this package to automatically extend the capabilities of beachmat::initializeCpp to TileDBArray instances.