mirror of
https://github.com/NixOS/nixpkgs.git
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commit
c7f5aae86d
2 changed files with 89 additions and 0 deletions
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@ -4832,6 +4832,12 @@
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github = "dfithian";
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githubId = 8409320;
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};
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dflores = {
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email = "dflores.country455@passinbox.com";
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name = "David Flores";
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github = "dflores1";
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githubId = 8538265;
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};
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dfordivam = {
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email = "dfordivam+nixpkgs@gmail.com";
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github = "dfordivam";
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83
pkgs/by-name/fa/fastqc/package.nix
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83
pkgs/by-name/fa/fastqc/package.nix
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@ -0,0 +1,83 @@
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{ lib,
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stdenv,
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fetchzip,
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jre,
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perl,
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makeWrapper,
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imagemagick,
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makeDesktopItem,
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copyDesktopItems,
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desktopToDarwinBundle,
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testers
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}:
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stdenv.mkDerivation (finalAttrs: {
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pname = "fastqc";
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version = "0.12.1";
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src = fetchzip {
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url = "https://www.bioinformatics.babraham.ac.uk/projects/fastqc/fastqc_v${finalAttrs.version}.zip";
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hash = "sha256-TenRG2x8ivJ2HM2ZpLaJShp0yI0Qc6K5lW5/NJFAa1I";
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};
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dontBuild = true;
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nativeBuildInputs = [ makeWrapper imagemagick ]
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++ lib.optional stdenv.isLinux copyDesktopItems # postInstallHook
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++ lib.optional stdenv.isDarwin desktopToDarwinBundle; #fixupOutputHook
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buildInputs = [ jre perl];
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desktopItem = (makeDesktopItem {
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name = "FastQC";
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exec = "fastqc";
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icon = "fastqc";
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desktopName = "FastQC";
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comment = finalAttrs.meta.description;
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categories = [ "Science" ];
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});
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desktopItems = [ finalAttrs.desktopItem ];
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installPhase = ''
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runHook preInstall
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mkdir -p $out/{bin,FastQC}
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cp -r $src/* $out/FastQC
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# Create desktop item
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mkdir -p $out/share/{applications,icons}
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# Freedesktop doesn't support windows ICO files. Use imagemagick to convert it to PNG
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convert $out/FastQC/fastqc_icon.ico $out/share/icons/fastqc.png
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runHook postInstall
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'';
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preFixup = ''
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makeWrapper $out/FastQC/fastqc $out/bin/fastqc --prefix PATH : ${jre}/bin
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'';
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passthru.tests.version = testers.testVersion {
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package = finalAttrs.finalPackage;
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version = "v${finalAttrs.version}";
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};
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meta = {
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description = "A quality control application for high throughput sequence data";
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longDescription = ''
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FastQC aims to provide a simple way to do some quality control checks on raw sequence data coming from high throughput sequencing pipelines. It provides a modular set of analyses which you can use to give a quick impression of whether your data has any problems of which you should be aware before doing any further analysis.
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The main functions of FastQC are
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- Import of data from BAM, SAM or FastQ files (any variant)
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- Providing a quick overview to tell you in which areas there may be problems
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- Summary graphs and tables to quickly assess your data
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- Export of results to an HTML based permanent report
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- Offline operation to allow automated generation of reports without running the interactive application
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'';
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homepage = "https://www.bioinformatics.babraham.ac.uk/projects/fastqc/";
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sourceProvenance = [ lib.sourceTypes.binaryNativeCode ];
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license = with lib.licenses; [ gpl3Plus asl20 ];
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maintainers = [ lib.maintainers.dflores ];
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mainProgram = "fastqc";
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platforms = lib.platforms.unix;
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};
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})
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