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Create a New Project

  1. Create a directory for your project (written as [ProjectDir] for the rest of this documentation).
  2. Within [ProjectDir], create a subdirectory for the raw data; internally we use the naming convention 00src (i.e., [ProjectDir]/00src), but this is not mandatory.
  3. Within 00src, place either the FinalReport files from GenomeStudio (either .csv or .csv.gz format) or Affymetrix .CEL files. Only Final Report or .CEL files should be in this directory. Click here for a tutorial on how to process a project using GenomeStudio. Click here for a tutorial on how to recluster data using only the high-quality samples as seeds. Best practices recommend reclustering the data even if the project was previously processed through GenomeStudio.
  4. In [ProjectDir], place

    • (Illumina only) The .csv version of the project’s manifest file (with probe sequences)

    • pedigree.txt and linker.txt (within a data subdirectory (i.e., [ProjectDir]/data))

    • If your samples were processed in batches, batch.text [within a data subdirectory (i.e., [ProjectDir]/data)] listing sample IDs and batch names (no header) so Genvisis can control for batch effects. For example:

        ID001	California
  ID002 California
  ID003	NBS
  ID004	NBS
  ID005	COG
  ID006	COG

    • (Illumina only) If available, the SNP_Map.csv file that was produced by GenomeStudio at the same time as the reports. This is necessary only if your manifest does not contain probe sequences.

  5. Once the directories are set up and the necessary files are in place, run genvisis.jar.
    • Linux/Mac
      • Open a terminal and run java -Xmx#g -jar [path]/genvisis.jar
      • #g is the number of gigabytes of memory
      • [path] is the location of the genvisis.jar file
      • e.g., java -Xmx24g -jar ~/genvisis.jar (if genvisis.jar is saved in your home directory)
      • Alternatively, locate genvisis.jar within a file manager and double-click on the Genvisis icon
    • Windows
      • Open a text file and write java -Xmx#g -jar genvisis.jar
      • #g is the number of gigabytes of memory
      • Save the text file as vis.bat in the same directory as genvisis.jar
      • Double-click vis.bat
  6. In the Genvisis window that opens, click File → New Project
  7. Enter a Project Name
  8. Click ... next to Project Directory
  9. Choose the [ProjectDir] → Select
  10. Click ... next to Source File Directory
  11. Choose the 00src directory created earlier → Select
  12. Genvisis will automatically detect the number of source files and the extension (eg. .csv, .csv.gz, .CEL, etc.).
  13. Choose the Array Type with which the data was collected:
    • ILLUMINA
    • AFFY_GW6
      • Only SNP probesets
    • AFFY_GW6_CN
      • SNP probesets plus copy number probesets
    • NGS_WES
    • NGS_WGS
    • AFFY_AXIOM
    • If you choose one of the Affymetrix arrays, there will an additional option, Start From. Select the appropriate option:
      • CEL files
      • APT results
        • Must have the same name as the Project Name
  14. Genome Build allows you to specify which version of the human genome to run the project in (e.g., Genome Reference Consortium Human Build 38 aka GRCh38).
    • Unless there is a specific need to use an older version of the genome, set Genome Build to hg38, even if the manifest is in an older build. Genvisis can liftover marker positions to hg38 in the Create Marker Positions step of the Workflow.
    • To determine which version of the genome your data is in, check the GenomeBuild column of your manifest.
  15. Select locations for the following files:
    • Pedigree file
    • Sample ID linker file
    • Batch file
    • Marker subset file [optional]
      • Used only if you are not analyzing all markers in the manifest
  16. If using Illumina reports, Create will launch the Validation Review window. Fields will be automatically populated from the source files.
    • Allele 1/2 - Genotype: These are important when combining data sets from multiple sources. In that case, a reference genome with a reference allele and an alternate allele are necessary. Illumina doesn't use that designation, so the categories used here for Illumina reports don't matter too much (can be forward allele or top allele designations).
    • Allele 1/2 - AB: This is more important than Allele 1/2 - Genotype. The genotype can either be AA, BB, AB, or missing.
    • X/Y: This is intensity data. If you want to do anything with Copy Number Variation calling or review cluster plots, this is necessary. What sets Genvisis apart is its ability to review raw data. X/Y are the most important variables followed by the Allele 1/2 AB genotype.
    • B Allele Frequency and Log-R Ratio: Genvisis can compute these from X and Y, so it's not critical to import these, but you can import them if they're available in the report.
    • Confidence: An optional category that is useful if you have only genotypes and no raw intensity data (X/Y). Defaults to GC score. The confidence score can be used to set a higher threshold than what the GenomeStudio report originally produced.
  17. If the reports don’t have consistent headers, there will be a separate validation review window for each group of reports.
  18. Click **OK. **A new window will appear: Genvisis Project Workflow
  19. If using Affymetrix CEL files, there will be no Validation Review and Genvisis will go directly to the Project Workflow.
  20. Inside [ProjectDir], two new directories will appear: data/ and logs/. A file named source_headers.ser will also appear in [ProjectDir].