Last updated: 2019-12-06

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Knit directory: PSYMETAB/

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Rmd b503ef0 Sjaarda Jennifer Lynn 2019-12-06 add more details to website
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Rmd 487b5f5 Sjaarda Jennifer Lynn 2019-12-06 update website, add qc description

The following document outlines and summarizes the quality control and processing procedure that was followed to create a clean, imputed dataset.

randomize_IDs.r

  • Script run on CHUV computer before building GenomeStudio project.
  • Creates a new csv file which was used to create a GenomeStudio project with data provided by lab in Geneva.
  • Requires manual addition of header before uploading to GenomeStudio.
  • Some samples were found to be duplicates (i.e. 2 samples at 2 different time points were analyzed for the same individual) and they were recoded to have ID ${ID}002.

Pre quality control data prep

  • Processes sex and ethnicity files to be used in QC scripts.
  • Sex file was created according to the input specified on plink man page (FID, IID, sex [M/F]).
  • Ethnicity input file to be used in R script for comparison to genetically derived ethnic groups (by snpWeights).
  • Recodes ethnic groups as follows:
    • Changes French codes to English.
    • Changes missing to unknown.
    • Groups small ethnic groups to missing.
  • A1 rsid conversion file was updated to remove all SNPs labeled with a [.] (see ‘data/README.md’).

Quality control steps

results are saved to analysis/QC

  1. Preprocessing
  2. Strand alignment
  3. MAF zero
  4. Missingness
  5. Sex check
  6. Imputation (preparation and run)
  7. Run and download imputation
  8. Check imputation
  9. PLINK conversion
  • Output of Michigan Impuation server is in format chr:bp:ref:alt.
  • Convenient to have SNPs in regular rsIDs for extraction, etc.
  • If there is no known rsID, SNP name is left as chr:bp:ref:alt.
  • Reference file for determining rsIDs can be found here: ‘/data/sgg2/jenny/data/dbSNP/dbSNP_SNP_list_chr${chr}.txt’, which was processed according to description in ‘/SGG_generic/scripts/public_data.sh’.
  1. Extract typed SNPs
  2. Merge imputed SNPs
  3. Relatedness
  4. Ethnicty check and admixture estimation
  5. HWE check
  6. MAF check
  7. Final processing

Results