{ "_id": "6a14397cacfb0bcc41d413f3", "Package": "Fragman", "Version": "1.1.0", "Date": "2026-05-20", "Title": "Fragment Analysis in R", "Authors@R": "c(\nperson(\"Giovanny\",\"Covarrubias-Pazaran\", email=\"cova_ruber@live.com.mx\", role=c(\"aut\",\"cre\"),\ncomment=c(ORCID=\"0000-0002-7194-3837\")),\nperson(\"Luis\", \"Diaz-Garcia\", role = \"aut\"),\nperson(\"Brandon\", \"Schlautman\", role = \"aut\"),\nperson(\"Walter\", \"Salazar\", role = \"aut\"),\nperson(\"Juan\", \"Zalapa\", role = \"aut\")\n)", "Maintainer": "Giovanny Covarrubias-Pazaran ", "Description": "Performs fragment analysis using genetic data coming from\ncapillary electrophoresis machines. These are files with FSA\nextension which stands for FASTA-type file, and .txt files from\nBeckman CEQ 8000 system, both contain DNA fragment intensities\nread by machinery. In addition to visualization, it performs\nautomatic scoring of SSRs (Sample Sequence Repeats; a type of\ngenetic marker very common across the genome) and other type of\nPCR markers (standing for Polymerase Chain Reaction) in\nbiparental populations such as F1, F2, BC (backcross), and\ndiversity panels (collection of genetic diversity).", "LazyData": "true", "License": "GPL (>= 2)", "Repository": "https://covaruber.r-universe.dev", "Date/Publication": "2026-05-24 02:14:26 UTC", "RemoteUrl": "https://github.com/covaruber/fragman", "RemoteRef": "HEAD", "RemoteSha": "918df7bf7a44f14db34e64e6d93610eb188d7da4", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-25 11:56:19 UTC", "User": "root" }, "Author": "Giovanny Covarrubias-Pazaran [aut, cre] (ORCID:\n),\nLuis Diaz-Garcia [aut],\nBrandon Schlautman [aut],\nWalter Salazar [aut],\nJuan Zalapa [aut]", "MD5sum": "26af58f9f8bc3d549cc50fd7e43a970c", "_user": "covaruber", "_type": "src", "_file": "Fragman_1.1.0.tar.gz", "_fileid": 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"my.plants", "class": [ "list" ], "fields": [], "table": true, "tojson": true } ], "_help": [ { "page": "Fragman-package", "title": "Fragment analysis and automatic scoring", "topics": [ "Fragman" ] }, { "page": "arrange.jm", "title": "Arrange data converted to joinmap code into a joinmap readable file", "topics": [ "arrange.jm" ] }, { "page": "best.layout", "title": "complementary tools for layout", "topics": [ "best.layout" ] }, { "page": "big.peaks.col", "title": "Peak search by first derivatives", "topics": [ "big.peaks.col" ] }, { "page": "detect.ladder", "title": "Ladder detection by correlation or confidence intervals", "topics": [ "detect.ladder" ] }, { "page": "find.ladder", "title": "Ladder detection by correlation or confidence intervals", "topics": [ "find.ladder" ] }, { "page": "get.scores", "title": "complementary tools", "topics": [ "get.scores" ] }, { "page": "homo.panel", "title": "complementary tools", "topics": [ "homo.panel" ] }, { "page": "homogenize.to.parentals", 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"overview2" ] }, { "page": "plot", "title": "plot form fsa files stored with storing.inds", "topics": [ "plot.fsa_stored" ] }, { "page": "pullup", "title": "Applying pullup to channels/colors", "topics": [ "pullup" ] }, { "page": "read.abif", "title": "Read ABIF formatted files", "topics": [ "read.abif" ] }, { "page": "reals", "title": "Finding the real peaks", "topics": [ "reals" ] }, { "page": "saturate", "title": "Checking and correcting saturated peaks", "topics": [ "saturate" ] }, { "page": "score.markers", "title": "Fragment analysis scoring", "topics": [ "score.markers" ] }, { "page": "separate", "title": "Separating peaks by a shift window", "topics": [ "separate" ] }, { "page": "storing.inds", "title": "Extracting channel information", "topics": [ "storing.inds" ] }, { "page": "threshs", "title": "Customizing thresholds", "topics": [ "threshs" ] }, { "page": "transfft", "title": "Applying the fourier transformation to a data frame", "topics": [ "transfft" ] }, { "page": 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