Data from 6 gpr files aims to identify differential expressed genes between the beta 7+ and beta 7- memory T helper cells.

Gene expression data from a breast cancer study published by Sotiriou et al. in 2007, provided as an eSet.

Full genome sequences for Bos taurus (Cow) as provided by UCSC (bosTau6, Nov. 2009) and stored in Biostrings objects. The sequences are the same as in BSgenome.Btaurus.UCSC.bosTau6, 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 Homo sapiens (Human) as provided by UCSC (hg17, May 2004) and stored in Biostrings objects. The sequences are the same as in BSgenome.Hsapiens.UCSC.hg17, 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.

The package contains data of the Primary Blood Cancer Encyclopedia (PACE) project together with a complete executable transcript of the statistical analysis and reproduces figures presented in the paper "Drug-perturbation-based stratification of blood cancer" by Dietrich S, Oleś M, Lu J et al., J. Clin. Invest. (2018) 128(1):427-445. doi:10.1172/JCI93801.

Full genome sequences for Canis lupus familiaris (Dog) as provided by UCSC (canFam3, Sep. 2011) and stored in Biostrings objects.

`BatchSVG` is a feature-based Quality Control (QC) to identify SVGs on spatial transcriptomics data with specific types of batch effect. Regarding to the spatial transcriptomics data experiments, the batch can be defined as "sample", "sex", and etc.The `BatchSVG` method is based on binomial deviance model (Townes et al, 2019) and applies cutoffs based on the number of standard deviation (nSD) of relative change in deviance and rank difference as the data-driven thresholding approach to detect the batch-biased outliers.

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.

Saccharomyces cerevisiae (Yeast) full genome as provided by UCSC (sacCer3, April 2011) and stored in Biostrings objects.

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

The barbieQ package provides a series of robust statistical tools for analysing barcode count data generated from cell clonal tracking (i.e., lineage tracing) experiments. In these experiments, an initial cell and its offspring collectively form a clone (i.e., lineage). A unique barcode sequence, incorporated into the DNA of the inital cell, is inherited within the clone. This one-to-one mapping of barcodes to clones enables clonal tracking of their behaviors. By counting barcodes, researchers can quantify the population abundance of individual clones under specific experimental perturbations. barbieQ supports barcode count data preprocessing, statistical testing, and visualization.

Full genome sequences for Caenorhabditis elegans (Worm) as provided by UCSC (ce2, Mar. 2004) and stored in Biostrings objects.

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 Arabidopsis thaliana as provided by TAIR (TAIR9 Genome Release) and stored in Biostrings objects. Note that TAIR10 is an "annotation release" based on the same genome assembly as TAIR9.

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

Full genome sequences for Macaca fascicularis (long-tailed macaque) as provided by NCBI (Macaca_fascicularis_5.0, 2013-06-12) and stored in Biostrings objects.

This Rcpp-based package implements a highly efficient data structure and algorithm for performing alignment of short reads from CRISPR or shRNA screens to reference barcode library. Sequencing error are considered and matching qualities are evaluated based on Phred scores. A Bayes classifier is employed to predict the originating barcode of a read. The package supports provision of user-defined probability models for evaluating matching qualities. The package also supports multi-threading.

Full genomic sequences for UCSC genome hs1 (the hs1 genome is based on assembly T2T-CHM13v2.0, with GenBank assembly accession GCA_009914755.4). The sequences are stored in DNAString objects.

This package provides a novel approach utilizing a homogeneous hidden Markov model. And effectively model untransformed beta values. To identify DMCs while considering the spatial. Correlation of the adjacent CpG sites.

Full genome sequences for Drosophila virilis (assembly dvir_caf1, GenBank assembly accession GCA_000005245.1) as provided by Ensembl and stored in Biostrings objects.

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

This package provides a tabular style data object where most data is stored outside main memory. A buffer is used to speed up access to data.