SOP for converting LifeLines Geno Data

This SOP applies to LL3.

Data is released to researcher 'per study' (i.e. an approved research request).

• Per study a subset of the genotypes is created and made available to the researcher:
• Only individuals selected for study (e.g. 5000 out of total 17000)
• The identifiers 're-pseunomized' from 'marcel identifiers' to 'study identifiers' (so data can not be matched between studies).

Expected outputs

User expects files in PLINK format:

• TPED/TFAM genotype files (chosen for internal use as easier to produce)
• BIM/BED/FAM genotype files (with missing value phenotype, monomorphic filtered)
• IDEM but then splitted per chromosome
• MAP/PED dosage files (with missing value phenotype, monomorphic filtered)
• IDEM but then splitted per chromosome

Available inputs

The following are input for the conversion procedure:

• TriTyper? imputated data files: /target/gpfs2/lifelines_rp/releases/LL3/
• Identifier mapping file per study to select and re-pseudonomize identifiers

Example mapping file:

LL_WGA0001   STUDYPSEUDO1   0
LL_WGA0002   STUDYPSEUDO2   0
LL_WGA0003   STUDYPSEUDO3   0
...

Procedure

• Data resides on /target/gpfs2/lifelines_rp/releases/LL3/BeagleImputedTriTyper (accessible from all our new VMs)
  • Convertor from TriTyper? to PLINK resides on /target/gpfs2/lifelines_rp/releases/LL3
  • Correct Java version resides on /target/gpfs2/lifelines_rp/tools/jdk1.6.0_22/bin/
  • STEP 1: make the subset_molgenis<n>.txt file:
    • In every MOLGENIS<n> schema for a study that has geno data, there is a VW_DICT_GENO_PSEUDONYMS view
    • In this view, PA_IDs (LL IDs) are related to GNO_IDs ("Marcel" IDs, the LL_WGA numbers)
    • Export this view (tab separated, no enclosures, no headers) to molgenis<n>.txt and scp to cluster.gcc.rug.nl:/target/gpfs2/lifelines_rp/releases/LL3
    • Run the following command there: ./formatsubsetfile.sh molgenis<n>.txt
    • Your file is now available as subset_molgenis<n>.txt and looks like:
      LL_WGA0001 STUDYPSEUDO1 0
      LL_WGA0002 STUDYPSEUDO2 0
      LL_WGA0003 STUDYPSEUDO3 0
      ...
      • So: Geno individual ID's - TAB - Study pseudonyms - TAB - Phenotypes (can be all 0's as TFAM will be generated later by the user)
      • Items are TAB-separated and it doesn't end with a newline
  • STEP 2: run the convertor
    • Usage: /target/gpfs2/lifelines_rp/tools/jdk1.6.0_22/bin/java -jar TriToPlinkLifeLines.jar P BeagleImputedTriTyper/ study<n> subset_molgenis<n>.txt
  • STEP 3: copy to correct location
    • cp study<n>.tped ../../lifelines0<n>
    • May take some time!

Further Genodata

The commands above generate a single large file for the study in question. From this researchers would like some further file manipulation to be done:

• Supply the large genodata in binary format, using command:

plink --tfile <data> --make-bed --out <data> This should generate .bed, .bim and .fam files.

• Supply the data also in separate files per chromosome. This can be done with the commands:

plink --tfile <data> --make-bed --chr 1 --out <data_chr1> plink --tfile <data> --make-bed --chr 2 --out <data_chr2> ...

(a script file should take care of this series of commands)

Besides the genodata dosage information is also desired, both for the total (per-study) dataset and for that dataset split per chromosome.

• Joeri has a tool for this. NB: it is slow, reimplementing it in a compiled language might be worthwhile.

A schematic overview of the two export paths described above.