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Full genome sequences for Pan troglodytes (Chimp) as provided by UCSC (panTro2, Mar. 2006) and stored in Biostrings objects. The sequences are the same as in BSgenome.Ptroglodytes.UCSC.panTro2, 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 Bos taurus (Cow) as provided by UCSC (bosTau3, Aug. 2006) and stored in Biostrings objects.
This package contains several sets of omics data including Gene Expression (ExpressionSet), Methylation (GenomicRatioSet), Proteome and Exposome (ExposomeSet). This data is used in vignettes and exaples at MEAL, MultiDataSet and omicRexposome.
Full genome sequences for Apis mellifera as provided by NCBI (assembly Amel_HAv3.1, assembly accession GCF_003254395.2) and stored in Biostrings objects.
Use hail via basilisk when appropriate, or via reticulate. This package can be used in terra.bio to interact with UK Biobank resources processed by hail.is.
Full genome sequences for Glycine max as provided by NCBI (assembly Glycine_max_v4.0, assembly accession GCF_000004515.5) and stored in Biostrings objects.
Full genome sequences for Homo sapiens (Human) as provided by UCSC (hg18, Mar. 2006) and stored in Biostrings objects.
Full genome sequences for Rattus norvegicus (Rat) as provided by UCSC (rn6, Jul. 2014) and stored in Biostrings objects.
Full genome sequences for Rattus norvegicus (Rat) as provided by UCSC (rn5, Mar. 2012) and stored in Biostrings objects. The sequences are the same as in BSgenome.Rnorvegicus.UCSC.rn5, 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 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 12Xv0) and available at the URGI (INRA).
Sequencing and microarray samples often are collected or processed in multiple batches or at different times. This often produces technical biases that can lead to incorrect results in the downstream analysis. BatchQC is a software tool that streamlines batch preprocessing and evaluation by providing interactive diagnostics, visualizations, and statistical analyses to explore the extent to which batch variation impacts the data. BatchQC diagnostics help determine whether batch adjustment needs to be done, and how correction should be applied before proceeding with a downstream analysis. Moreover, BatchQC interactively applies multiple common batch effect approaches to the data and the user can quickly see the benefits of each method. BatchQC is developed as a Shiny App. The output is organized into multiple tabs and each tab features an important part of the batch effect analysis and visualization of the data. The BatchQC interface has the following analysis groups: Summary, Differential Expression, Median Correlations, Heatmaps, Circular Dendrogram, PCA Analysis, Shape, ComBat and SVA.
Full genome sequences for Sus scrofa (Pig) as provided by UCSC (susScr3, Aug. 2011) and stored in Biostrings objects.
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.
This package provides a roclet for roxygen2 that identifies and processes code blocks in your documentation marked with `@longtests`. These blocks should contain tests that take a long time to run and thus cannot be included in the regular test suite of the package. When you run `roxygen2::roxygenise` with the `longtests_roclet`, it will extract these long tests from your documentation and save them in a separate directory. This allows you to run these long tests separately from the rest of your tests, for example, on a continuous integration server that is set up to run long tests.
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 genome sequences for Gallus gallus (Chicken) as provided by UCSC (galGal3, May 2006) and stored in Biostrings objects. The sequences are the same as in BSgenome.Ggallus.UCSC.galGal3, 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 Cryptococcus neoformans var. grubii KN99 (assembly ASM221672v1 assembly accession GCA_002216725.1).
Full genome sequences for Danio rerio (Zebrafish) as provided by UCSC (danRer7, Jul. 2010) and stored in Biostrings objects. The sequences are the same as in BSgenome.Drerio.UCSC.danRer7, 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.
bettr provides a set of interactive visualization methods to explore the results of a benchmarking study, where typically more than a single performance measures are computed. The user can weight the performance measures according to their preferences. Performance measures can also be grouped and aggregated according to additional annotations.
Package for calculating aggregated isotopic distribution and exact center-masses for chemical substances (in this version composed of C, H, N, O and S). This is an implementation of the BRAIN algorithm described in the paper by J. Claesen, P. Dittwald, T. Burzykowski and D. Valkenborg.
Full genome sequences for Pan troglodytes (Chimp) as provided by UCSC (panTro2, Mar. 2006) and stored in Biostrings objects.
This package provides interfaces to selected sklearn elements, and demonstrates fault tolerant use of python modules requiring extensive iteration.
Full genome sequences for Mus musculus (Mouse) as provided by UCSC (mm8, Feb. 2006) and stored in Biostrings objects. The sequences are the same as in BSgenome.Mmusculus.UCSC.mm8, 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.
High-throughput experimental data are accumulating exponentially in public databases. However, mining valid scientific discoveries from these abundant resources is hampered by technical artifacts and inherent biological heterogeneity. The former are usually termed "batch effects," and the latter is often modelled by "subtypes." The R package BUScorrect fits a Bayesian hierarchical model, the Batch-effects-correction-with-Unknown-Subtypes model (BUS), to correct batch effects in the presence of unknown subtypes. BUS is capable of (a) correcting batch effects explicitly, (b) grouping samples that share similar characteristics into subtypes, (c) identifying features that distinguish subtypes, and (d) enjoying a linear-order computation complexity.