Package: groHMM 1.39.0

Tulip Nandu

groHMM: GRO-seq Analysis Pipeline

A pipeline for the analysis of GRO-seq data.

Authors:Charles G. Danko, Minho Chae, Andre Martins, W. Lee Kraus

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groHMM.pdf |groHMM.html✨
groHMM/json (API)
NEWS

# Install 'groHMM' in R:

install.packages('groHMM', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kraus-lab/grohmm/issues

On BioConductor:groHMM-1.39.0(bioc 3.20)groHMM-1.38.0(bioc 3.19)

bioconductor-package

26 exports 1.16 score 50 dependencies 6 mentions

Last updated 2 months agofrom:d83ee483c8

Exports:averagePlot breakTranscriptsOnGenes combineTranscripts countMappableReadsInInterval detectTranscripts evaluateHMMInAnnotations expressedGenes getCores getTxDensity limitToXkb makeConsensusAnnotations metaGene metaGene_nL metaGeneMatrix pausingIndex polymeraseWave readBed RgammaMLE Rnorm Rnorm.exp runMetaGene tlsDeming tlsLoess tlsSvd windowAnalysis writeWiggle

Dependencies:abind askpass BH Biobase BiocGenerics BiocIO BiocParallel Biostrings bitops codetools cpp11 crayon curl DelayedArray formatR futile.logger futile.options GenomeInfoDb GenomeInfoDbData GenomicAlignments GenomicRanges httr IRanges jsonlite lambda.r lattice MASS Matrix MatrixGenerics matrixStats mime openssl R6 RCurl restfulr Rhtslib rjson Rsamtools rtracklayer S4Arrays S4Vectors snow SparseArray SummarizedExperiment sys UCSC.utils XML XVector yaml zlibbioc

groHMM tutorial

Rendered fromgroHMM.Rnwusingutils::Sweaveon Jun 13 2024.

Last update: 2022-05-11
Started: 2017-10-19

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
groHMM: GRO-seq Analysis Pipeline	groHMM-package groHMM
Returns the average profile of tiling array probe intensity values or wiggle-like count data centered on a set of genomic positions (specified by 'Peaks').	averagePlot
breakTranscriptsOnGenes Breaks transcripts on genes	breakTranscriptsOnGenes
combineTranscripts Combines transnscipts.	combineTranscripts
countMappableReadsInInterval counts the number of mappable reads in a set of genomic features.	countMappableReadsInInterval
detectTranscripts detects transcripts de novo using a two-state hidden Markov model (HMM).	detectTranscripts
evaluateHMM Evaluates HMM calling.	evaluateHMMInAnnotations
Function identifies expressed features using the methods introduced in Core, Waterfall, Lis; Science, Dec. 2008.	expressedGenes
Returns the number of cores.	getCores
getTxDensity Calculates transcript density.	getTxDensity
limitToXkb truncates a set of genomic itnervals at a constant, maximum size.	limitToXkb
makeConsensusAnnotations Makes a consensus annotation	makeConsensusAnnotations
Returns a histogram of the number of reads in each section of a moving window centered on a certain feature.	metaGene
Returns a histogram of the number of reads in each section of a moving window of #' variable size across genes.	metaGene_nL
Returns a matrix, with rows representing read counts across a specified gene, or other features of interest.	metaGeneMatrix
Returns the pausing index for different genes. TODO: DESCRIBE THE PAUSING INDEX.	pausingIndex
Given GRO-seq data, identifies the location of the polymerase 'wave' in up- or down- regulated genes.	polymeraseWave
readBed Returns a GenomicRanges object constrcuted from the specified bed file.	readBed
RgammaMLE fits a gamma distribution to a specified data vector using maximum likelihood.	RgammaMLE
Rnorm fits a normal distribution to a specified data vector using maximum likelihood.	Rnorm
Rnorm.exp fits a normal+exponential distribution to a specified data vector using maximum likelihood.	Rnorm.exp
Runs metagene analysis for sense and antisense direction.	runMetaGene
A 'total least squares' implementation using demming regression.	tlsDeming
A 'total least squares'-like hack for LOESS. Works by rotating points 45 degrees, fitting LOESS, and rotating back.	tlsLoess
A 'total least squares' implementation using singular value demposition.	tlsSvd
windowAnalysis Returns a vector of integers representing the counts of reads in a moving window.	windowAnalysis
writeWiggle writes a wiggle track or BigWig file suitable for uploading to the UCSC genome browser.	writeWiggle