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It provides methods for fast and memory efficient\nparsing of Affymetrix files using the Affymetrix' Fusion SDK.\nBoth ASCII- and binary-based files are supported. Currently,\nthere are methods for reading chip definition file (CDF) and a\ncell intensity file (CEL). These files can be read either in\nfull or in part. For example, probe signals from a few\nprobesets can be extracted very quickly from a set of CEL files\ninto a convenient list structure.","biocViews":["Software","Infrastructure","Technology","Microarray","DataImport","ProprietaryPlatforms","OneChannel"],"Author":["Henrik Bengtsson","James Bullard","Robert Gentleman","Kasper Daniel Hansen","Jim Hester","Martin Morgan"],"Maintainer":["Kasper Daniel Hansen "],"git_url":"https://git.bioconductor.org/packages/affxparser","git_branch":"RELEASE_3_16","git_last_commit":"d2779bf","git_last_commit_date":"2022-11-01","Date/Publication":"2022-11-01","source.ver":"src/contrib/affxparser_1.70.0.tar.gz","win.binary.ver":"bin/windows/contrib/4.2/affxparser_1.70.0.zip","mac.binary.ver":"bin/macosx/contrib/4.2/affxparser_1.70.0.tgz","mac.binary.big-sur-arm64.ver":"bin/macosx/big-sur-arm64/contrib/4.2/affxparser_1.70.0.tgz","vignettes":[null],"vignetteTitles":[null],"hasREADME":"FALSE","hasNEWS":"TRUE","hasINSTALL":"FALSE","hasLICENSE":"FALSE","Rfiles":[null],"dependencyCount":"0","Imports":[null],"Enhances":[null],"dependsOnMe":["ITALICS","pdInfoBuilder"],"suggestsMe":["TIN","aroma.affymetrix","aroma.apd"],"URL":"https://github.com/HenrikBengtsson/affxparser","BugReports":"https://github.com/HenrikBengtsson/affxparser/issues","importsMe":["affyILM","cn.farms","crossmeta","EventPointer","GCSscore","GeneRegionScan","ITALICS","oligo"],"Archs":["x64"],"LinkingTo":[null],"linksToMe":[null],"url_github":"https://github.com/HenrikBengtsson/affxparser","url":"https://github.com/HenrikBengtsson/affxparser","owner_repo":"HenrikBengtsson/affxparser","owner":"HenrikBengtsson","repo":"affxparser"} {"r_repo":"BioCsoft","Package":"affy","Version":"1.76.0","Depends":["R (>= 2.8.0)","BiocGenerics (>= 0.1.12)","Biobase (>= 2.5.5)"],"Suggests":["tkWidgets (>= 1.19.0)","affydata","widgetTools"],"License":"LGPL (>= 2.0)","MD5sum":"53cbffc6730bbac4cd93bbd70fb87414","NeedsCompilation":"yes","Title":"Methods for Affymetrix Oligonucleotide Arrays","Description":"The package contains functions for exploratory\noligonucleotide array analysis. 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In the process of analyzing\nseveral ATAC-seq dataset produced in our labs, we learned some\nof the unique aspects of the quality assessment for ATAC-seq\ndata.To help users to quickly assess whether their ATAC-seq\nexperiment is successful, we developed ATACseqQC package\npartially following the guideline published in Nature Method\n2013 (Greenleaf et al.), including diagnostic plot of fragment\nsize distribution, proportion of mitochondria reads, nucleosome\npositioning pattern, and CTCF or other Transcript Factor\nfootprints.","biocViews":["Software","Technology","Sequencing","BiologicalQuestion","WorkflowStep","ResearchField","DNASeq","ATACSeq","GeneRegulation","QualityControl","Coverage","NucleosomePositioning","ImmunoOncology"],"Author":["Jianhong Ou","Haibo Liu","Feng Yan","Jun Yu","Michelle Kelliher","Lucio Castilla","Nathan Lawson","Lihua Julie Zhu"],"Maintainer":["Jianhong Ou "],"git_url":"https://git.bioconductor.org/packages/ATACseqQC","git_branch":"RELEASE_3_16","git_last_commit":"be03c44","git_last_commit_date":"2022-11-01","Date/Publication":"2022-11-01","source.ver":"src/contrib/ATACseqQC_1.22.0.tar.gz","win.binary.ver":"bin/windows/contrib/4.2/ATACseqQC_1.22.0.zip","mac.binary.ver":"bin/macosx/contrib/4.2/ATACseqQC_1.22.0.tgz","mac.binary.big-sur-arm64.ver":"bin/macosx/big-sur-arm64/contrib/4.2/ATACseqQC_1.22.0.tgz","vignettes":["vignettes/ATACseqQC/inst/doc/ATACseqQC.html"],"vignetteTitles":["ATACseqQC Vignette"],"hasREADME":"FALSE","hasNEWS":"TRUE","hasINSTALL":"FALSE","hasLICENSE":"FALSE","Rfiles":["vignettes/ATACseqQC/inst/doc/ATACseqQC.R"],"dependencyCount":"189","Imports":["BSgenome","Biostrings","ChIPpeakAnno","IRanges","GenomicRanges","GenomicAlignments","GenomeInfoDb","GenomicScores","graphics","grid","limma","Rsamtools (>= 1.31.2)","randomForest","rtracklayer","stats","motifStack","preseqR","utils","KernSmooth","edgeR"],"Enhances":[null],"dependsOnMe":[null],"suggestsMe":["ATACseqTFEA"],"VignetteBuilder":"knitr","importsMe":[null],"Archs":[null],"LinkingTo":[null],"linksToMe":[null]} {"r_repo":"BioCsoft","Package":"ATACseqTFEA","Version":"1.0.1","Depends":["R (>= 4.2)"],"Suggests":["BSgenome.Drerio.UCSC.danRer10","knitr","testthat","ATACseqQC","rmarkdown","BiocStyle"],"License":"GPL-3","MD5sum":"e5de11a5adccff977b830f09981cca58","NeedsCompilation":"no","Title":"Transcription Factor Enrichment Analysis for ATAC-seq","Description":"Assay for Transpose-Accessible Chromatin using sequencing\n(ATAC-seq) is a technique to assess genome-wide chromatin\naccessibility by probing open chromatin with hyperactive mutant\nTn5 Transposase that inserts sequencing adapters into open\nregions of the genome. 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