The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
R generic interface to Hi-C contact matrices in `.(m)cool`, `.hic` or HiC-Pro derived formats, as well as other Hi-C processed file formats. Contact matrices can be partially parsed using a random access method, allowing a memory-efficient representation of Hi-C data in R. The `HiCExperiment` class stores the Hi-C contacts parsed from local contact matrix files. `HiCExperiment` instances can be further investigated in R using the `HiContacts` analysis package.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
library(HiCExperiment)
library(HiContactsData)
# Retrieve a sample cool file path
cool_file <- HiContactsData('yeast_wt', format = 'cool')
# Import the contact matrix as a HiCExperiment object
hic <- import(cool_file, format = 'cool', focus = 'I:20001-80000')
# Inspect the imported object
resolution(hic)
Input: A path to a .cool, .mcool, .hic, or HiC-Pro contact matrix file.
Output: A parsed HiCExperiment object containing contact frequencies, genomic bins, and metadata.
.cool, .mcool, .hic, or HiC-Pro formats using import().focus argument.GInteractions, ContactMatrix, or base matrix using as().HiContacts instead of HiCExperiment alone.HiCExperiment does not support the focus argument for HiC-Pro files (they must be fully imported into memory)..cool, .mcool, .hic, or HiC-Pro format (which consists of a .matrix and a .bed file)..pairs or .pairs.gz files can be linked using CoolFile(), HicFile(), or HicproFile() via the pairsFile argument.'cool', 'pairs').'I:20001-80000' or 'II:1-500000|II:100001-300000') to subset contacts within a genomic locus of interest.availableResolutions() before importing.availableChromosomes() to construct valid focus queries.bins() or unique regions using regions().focus: This is unsupported and will cause the entire matrix to be imported into memory.scores(hic) first.InteractionSet: For general representation of genomic interactions without specialized Hi-C file parsers.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This tool uses the label-tree function from HyPhy to annotate a phylogenetic tree. It allows users to select a subset of leaves using either a regular expression or a list of sequence names, and then apply a specified label to these selecte
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, En
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
apeglm provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
ASURAT is a software for single-cell data analysis. Using ASURAT, one can simultaneously perform unsupervised clustering and biological interpretation in terms of cell type, disease, biological process, and signaling pathway activity. Inputting a single-cell RNA-seq data and knowledge-based databases, such as Cell Ontology, Gene Ontology, KEGG, etc., ASURAT transforms gene expression tables into original multivariate tables, termed sign-by-sample matrices (SSMs).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AUCell allows to identify cells with active gene sets (e.g. signatures, gene modules...) in single-cell RNA-seq data. AUCell uses the "Area Under the Curve" (AUC) to calculate whether a critical subset of the input gene set is enriched with
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.