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DTSTAMP:20260829T194433Z
UID:75fab72d-4422-4875-807f-380ee5b3ce54
DTSTART:20190721T090000Z
DTEND:20190721T170000Z
DESCRIPTION:Educators:\nBjoern Grüning (RBC)\, Johannes Köster\, Devon Ry
 an\n\nDate:\n21.07.2019\n\nLocation:\nISMB/ECCB Basel\n\nContent:\nThe typ
 ical data analyst must simultaneously juggle multiple projects\, each havi
 ng its own duration and software requirements. As few analysts have any fo
 rmal training on structuring or even writing the code necessary to perform
  an analysis\, it is unsurprising that the iterative analytic process can 
 produce a wide assortment of almost identically named files (e.g.\, “fin
 al_results.txt”\, “final_results.version2.txt”\, “final_results.re
 ally_final.txt”)\, all with unclear origins and produced with a hodge-po
 dge of similarly poorly named scripts. The near impossibility of tracing a
  results file to the exact process that produced it creates untold difficu
 lties both when it comes time to publish results as well as when planning 
 subsequent experiments months or years later (afterall\, which of the “f
 inal_results” files was really the “right one”?). These issues are f
 urther compounded by software paths and other similar assumptions being ha
 rd-coded into scripts\, preventing easy analysis replication elsewhere. Pe
 rforming analyses in a reproducible and traceable manner is clearly needed
  to combat such problems.\n\nSchedule Overview\n\n2:00 - 2:10 pm     Insta
 lling conda and snakeMake\n2:10 - 2:30 pm     Intro to conda and bioconda 
 (slides)\n2:30 - 3:30 pm     Hands-on Session: creating conda envs and ins
 talling packages from bioconda repo\n\n    This practical would require in
 stalling hisat\, samtools and deeptools via bioconda\n\n3:30 - 4:00 pm    
  Hands-on Session: writing conda recipes\n\n    Topics in BioVis (includin
 g examples)\n    Visualization of sequences\, macromolecules\, omics data\
 , biological networks\n\n4:00 - 4:15 am     Coffee Break\n4:15 - 4:35 pm  
    Intro to snakemake\n\n    Specific tools for visualizing large-scale bi
 ological data\n\n4:35 - 6:00     Hands On Session: Writing a snakemake wor
 kflow wrapper for mapping\, indexing and creating coverage files \n\nLearn
 ing goals:\nIn this hands-on tutorial\, we demonstrate how Conda can be us
 ed to deploy specific software versions easily\, reproducibly\, and withou
 t administrator credentials. Moreover\, we demonstrate how Conda’s abili
 ty to create isolated software environments helps to avoid side-effects be
 tween different analyses or different steps of the same analysis. Attendee
 s will also learn how to create conda recipes themselves\, so they can con
 tribute new packages to projects such as Bioconda. We further demonstrate 
 how Snakemake can be used in combination with Conda and Containers to crea
 te reproducible analysis workflows and execute them on any platform from w
 orkstations to clusters and the cloud. Finally\, using snakePipes as an ex
 ample\, we demonstrate how Conda and Snakemake can be used to define repro
 ducible and flexible workflows for complex genomics analysis.\n\nPrerequis
 ites:\n- Laptops with Linux or MacOS\n- Pre-installed Miniconda - install 
 via miniconda : https://conda.io/miniconda.html\n- Expected audience shoul
 d have basic familiarity with python\, git and the command line.\n\nKeywor
 ds:\nConda\, Bioconda\, snakemake\, Bioconductor\, reproducible research\n
 \nTools:\nConda\, Bioconda\, snakemake\,
LOCATION:Basel
SUMMARY:Tools for reproducible research - ISMB/ECCB 2019
URL;VALUE=URI:https://www.denbi.de/training/652-tools-for-reproducible-rese
 arch
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