{
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  "Type": "Package",
  "Title": "An Integrative Tool for ChIP- And RNA-Seq Based Primary\nTranscripts Detection and Quantification",
  "Version": "1.41.0",
  "Date": "2021-11-20",
  "Author": "Armen R. Karapetyan <armen.karapetyan87@gmail.com>",
  "Maintainer": "Armen R. Karapetyan <armen.karapetyan87@gmail.com>",
  "Description": "The differences in the RNA types being sequenced have an\nimpact on the resulting sequencing profiles. mRNA-seq data is\nenriched with reads derived from exons, while GRO-, nucRNA- and\nchrRNA-seq demonstrate a substantial broader coverage of both\nexonic and intronic regions. The presence of intronic reads in\nGRO-seq type of data makes it possible to use it to\ncomputationally identify and quantify all de novo continuous\nregions of transcription distributed across the genome. This\ntype of data, however, is more challenging to interpret and\nless common practice compared to mRNA-seq. One of the\nchallenges for primary transcript detection concerns the\nsimultaneous transcription of closely spaced genes, which needs\nto be properly divided into individually transcribed units. The\nR package transcriptR combines RNA-seq data with ChIP-seq data\nof histone modifications that mark active Transcription Start\nSites (TSSs), such as, H3K4me3 or H3K9/14Ac to overcome this\nchallenge. The advantage of this approach over the use of, for\nexample, gene annotations is that this approach is data driven\nand therefore able to deal also with novel and case specific\nevents. Furthermore, the integration of ChIP- and RNA-seq data\nallows the identification all known and novel active\ntranscription start sites within a given sample.",
  "License": "GPL-3",
  "Collate": "'utils.R' 'TranscriptionDataSet-class.R' 'ChipDataSet-class.R'\n'show.R' 'TranscriptionDataSet-generics.R'\n'TranscriptionDataSet-methods.R' 'ChipDataSet-generics.R'\n'ChipDataSet-methods.R'",
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  "Date/Publication": "2026-04-28 12:42:20 UTC",
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