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File Version Author Date Message
Rmd e0d6032 Sjaarda Jennifer Lynn 2019-12-06 edit typos
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html 9f1ba5e Jenny Sjaarda 2019-12-06 Build site.
Rmd c1d579b Jenny 2019-12-04 add details on data

provided from iGE3

General information

  • Files received from: Mylene Docquier (Mylene.Docquier@unige.ch), iGE3 Genomics Platform Manager, University of Geneva
  • ftp server details:
  • Genotype data received in genomestudio format on August 28, 2019; for processing and converting to PLINK format see docs/miscellaneous/data_processing.md

Genotype data

  • Genotype data found in data/raw/genotypes
  • Each folder contains:
    • Initial data provided from Mylene in genomestudio format, with the original folder name (‘XXX/’).
    • Cluster files in genomestudio format (see docs/miscellaneous/data_processing.md), and named ‘XXX_cluster/’.
    • PLINK files exported from genomestudio.

Miscellaneous GSA information provided in the following files:

  1. GSA v2 + MD Consortium.csv
  2. GSAMD-24v2-0_20024620_A1.csv
  3. GSAMD-24v2-0_A1-ACMG-GeneAnnotation.xlsx
  4. GSAMD-24v2-0_A1-ADME-CPIC-GeneAnnotation.xlsx
  5. GSAMD-24v2-0_A1-HLA-GeneAnnotation.xlsx
  6. GSAMD-24v2-0_A1-TruSight-GeneAnnotation.xlsx
  7. GSAv2_MDConsortium.bpm
  8. GSPMA24v1_0-A_4349HNR_Samples.egt

Details

  • Files 1 and 2 appear to be identical and correspond to strand illumina strand information, same file can be found here.
  • xlsx files contain 2 tabs: “Coverage Summary” and “GSAMD-24v2-0_A1-XXX-GeneAnnota”
  • bpm file corresponds to manifest file for use in genomestudio. Manifest files provide a description of the SNP or probe content on a standard BeadChip or in an assay product.
  • egt file corresponds to cluster file for making genotype calls.
  • all saved in data/reference_files

Chip details from Illumina

  • Files received from: Fe Magbanua (techsupport@illumina.com),Technical Applications Scientist, Technical Support, Illumina
  • GSAMD-24v2-0_20024620_A4_StrandReport_FDT.txt: strand report build38 (build37 not available).
  • GSAMD-24v2-0_20024620_A1_b151_rsids.txt: loci to rsid conversion file build37.
  • GSAMD-24v2-0_20024620_A4_b151_rsids.txt: loci to rsid conversion file build38.
  • all saved in data/reference_files (copied using FileZilla)

Strand files from Welcome Centre

  • The data for each chip and genome build combination are freely downloadable from the links localted here, each zip file contains three files, these are:
    • .strand file
    • .miss file
    • .multiple file
  • More details can be found at the link above
  • Chipendium was used to comfirm that bim files are on the TOP strand .
  • Contacted William Rayner (wrayner@well.ox.ac.uk) to find out what to do about custom SNPs, all correspondence on 22/07/2019.
    • Query:

    The chip used to generate the data was the GSAMD-24v2, however about 10,000 custom SNPs were also added to the chip. Do you have any recommendations for adding such SNPs to the strand file for processing?

    • Response:

    If you have a chip with custom content on it as you do if you are able to send me the .csv annotation file (that contains the TopGenomicSeq information) I can use that to create you a custom strand file that you can then download on a private link, this will ensure the extra SNPs are not lost in the strand update (at the moment they would be removed as non-matching).

    • Trying to obtain such .csv file from Mylene or Smita at Illumina (spathak@illumina.com) who designed the chip.
    • On 15/07/2019 Smita provided such a file: GSA_UPPC_20023490X357589_A1_custom_only.csv.
    • The file was downloaded and save to UPPC (Jenny/PSYMETAB_GWAS/GSA).
    • Sent .csv file to William Rayner and he provided the strand file for the custom SNP list on 16/07/2019:
      • GSA_UPPC_20023490X357589_A1_custom_only-b37-strand.zip
      • GSA_UPPC_20023490X357589_A1_custom_only-b37-strand.zip
    • Zipped strand files were copied to SGG server (${project_dir}/data/raw/reference_files/) and subsequently unzipped and used in QC (only b37 files was needed).

Phenotype data

Sex/ethnicity data

  • Provided by Celine (via email) for each batch on July 18, 2019: GSA_sex-ethnicity.xlsx.
  • Used for genetic quality control.
  • Downloaded and saved to UPPC folder (Jenny/PSYMETAB_GWAS/).
  • Opened, manually changed all accents to standard letters (ctrl-F and replace) and re-saved as csv/xlsx file (with no_accents) for easier use in R.
  • Moved to SGG folders via filezilla (manually).
  • Name was changed, as follows:
mv data/raw/phenotype_data/GSA_sex-ethnicity.xlsx data/raw/phenotype_data/QC_sex_eth.xlsx

Full phenotype data

  • Phenotype data to be used in GWAS (and other) analyses.
  • All data was saved on sgg folders to: PSYMETAB/data/raw/phenotype_data/.
  • Iniitial data provided by Celine (via email) on October 24, 2019: PHENO_GWAS_241019.xlsx.
    • Saved to sgg folder PSYMETAB/data/phenotype_data/.
    • Opened in excel, saved as a .csv file.
    • Manually changed all accents to standard letters (ctrl-F and replace) and re-saved as csv file (with extension _no_accents.csv) for easier use in R.
  • Discovered problems with phenotype database in early 2020, new phenotype data was provided on March 16, 2020: PHENO_GWAS_160320.xlsx.
    • Same process as above was followed to remove accents and convert to csv file.
    • Details on problems detected can be found on the Phenotype Quality Control page.
  • Additional problems were discovered and a new dataset was provided on April 16, 2020: PHENO_GWAS_160420.xlsx (processed the same as above).

Caffeine data

  • Requested to perform analysis using Nermine’s caffeine data.
  • All data was saved on sgg folders to: PSYMETAB/data/raw/phenotype_data/.
  • Initial data provided by Claire (via email) on March 11, 2020: Code_GEN_CG_11.03.2020.xlsx.
  • New variables (data of blood draw and age) were provided by Claire on May 5, 2020: CAF_Sleep_Jenny_05_05_2020_CG.xlsx.
    • Noticed that there was a problem with the data set (email describing problem to Nermine on 07/05/2020):

    I am a bit confused by the age and date columns in some cases. For example, for the participant below we have measurements at 4 time points: age 34, 52, 53 and 39 and the date of measurement in the next column. Does the date correspond to the date the blood draw took place? If so, I don’t understand why in 2018 (row 4) this participant was 39 and in 2012 (row 3) they were 53! Or does this column represent the date caffeine was measured (which could be very different from date of extraction)? Ideally I need the age the participant was when the extraction took place.

    GEN age Date
    UXEWHQEZ 52 2011-04-26
    UXEWHQEZ 34 2013-04-02
    UXEWHQEZ 52 2011-03-24
    UXEWHQEZ 53 2012-02-27
    UXEWHQEZ 39 2018-05-07
    • After discussing with Nermine and Claire, Claire discovered the problem (as per email on 07/05/2020):

    I spotted the problem, it was a mismatch in the ambulatory codes as some of them are written XXXAMB instead of AMBXXX or XXX+letter. I will send Jenny a new version of the file with paying attention to these codes if ok for you?

  • A New dataset was provided by Cliare on May 7, 2020: CAF_Sleep_Jenny_07_05_2020_CG.xlsx.
    • There were still issues with this dataset (as per email on 07/07/2020):

    Il y a toujours un petit problème avec les IDs : GAWZCNNL et WIFRYNSK. Je mets les problèmes en dessous. Je crois que deux participants ont reçu le meme GEN ID. Peut-être il y avait encore un problème avec le merge ?

    GEN Date age age2 Date2 days_difference age_plus_days age_check
    GAWZCNNL 2011-02-03 53 22 2018-02-22 2576 60.05753 problem
    GAWZCNNL 2011-02-03 53 60 2018-05-08 2651 60.26301 sensible
    GAWZCNNL 2018-02-22 22 60 2018-05-08 75 22.20548 sensible
    WIFRYNSK 2009-01-19 31 31 2018-09-10 3521 40.64658 problem
  • Celine performed the anonymization to compare to Claire’s data to see if the same problems arose: GEN_CAF_Sleep_Jenny_05_05_2020.xlsx.
    • There was still one issue with the dataset at ID WIFRYNSK.
      GEN Date age age2 Date2 days_difference age_plus_days age_check
      WIFRYNSK 2009-01-07 31 31 2018-08-29 3521 40.64658 problem
    • After asking Celine about this problem (08/05/2020), she said:

    Okay alors j’ai vérifié et cette erreur est déjà présente dans le fichier que Nermine nous a envoyé, donc ce n’est pas un problème lié au changement de codes.

    • Nermine responded (08/05/2020) with the explanation:

    Je viens de vérifier et en effet j’avais changé l’âge manuellement et il était changé dans les deux observations même si j’ai précisé la date de l’observation… je ne sais pas comment j’ai fais. Alors à la date du 22.12.2008, le patient avait 21 ans, et à la date du 13.08.2018 le patient avait 31 ans.

    • The following line was added to the script to manually change this entry: caffeine_raw %>% mutate(age=replace(age, GEN=="WIFRYNSK" & as.Date(Date)=="2009-01-07", 21)

sessionInfo()
R version 3.5.3 (2019-03-11)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS: /data/sgg2/jenny/bin/R-3.5.3/lib64/R/lib/libRblas.so
LAPACK: /data/sgg2/jenny/bin/R-3.5.3/lib64/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] fuzzyjoin_0.1.5         kableExtra_1.1.0        R.utils_2.9.2          
 [4] R.oo_1.23.0             R.methodsS3_1.7.1       TwoSampleMR_0.4.25     
 [7] reader_1.0.6            NCmisc_1.1.6            optparse_1.6.4         
[10] readxl_1.3.1            ggthemes_4.2.0          tryCatchLog_1.1.6      
[13] futile.logger_1.4.3     DataExplorer_0.8.0      taRifx_1.0.6.1         
[16] qqman_0.1.4             MASS_7.3-51.5           bit64_0.9-7            
[19] bit_1.1-14              rslurm_0.5.0            rmeta_3.0              
[22] devtools_2.2.1          usethis_1.5.1           data.table_1.12.8      
[25] clustermq_0.8.8.1       future.batchtools_0.8.1 future_1.15.1          
[28] rlang_0.4.5             knitr_1.26              drake_7.12.0.9000      
[31] forcats_0.4.0           stringr_1.4.0           dplyr_0.8.3            
[34] purrr_0.3.3             readr_1.3.1             tidyr_1.0.3            
[37] tibble_2.1.3            ggplot2_3.2.1           tidyverse_1.3.0        
[40] pacman_0.5.1            processx_3.4.1          workflowr_1.6.0        

loaded via a namespace (and not attached):
 [1] backports_1.1.6      plyr_1.8.5           igraph_1.2.5        
 [4] lazyeval_0.2.2       storr_1.2.1          listenv_0.8.0       
 [7] digest_0.6.25        htmltools_0.4.0      fansi_0.4.1         
[10] magrittr_1.5         checkmate_1.9.4      memoise_1.1.0       
[13] base64url_1.4        remotes_2.1.0        globals_0.12.5      
[16] modelr_0.1.5         prettyunits_1.1.0    colorspace_1.4-1    
[19] rvest_0.3.5          rappdirs_0.3.1       haven_2.2.0         
[22] xfun_0.11            callr_3.4.0          crayon_1.3.4        
[25] jsonlite_1.6         brew_1.0-6           glue_1.4.0          
[28] gtable_0.3.0         webshot_0.5.2        pkgbuild_1.0.6      
[31] scales_1.1.0         futile.options_1.0.1 DBI_1.1.0           
[34] Rcpp_1.0.3           viridisLite_0.3.0    progress_1.2.2      
[37] txtq_0.2.0           htmlwidgets_1.5.1    httr_1.4.1          
[40] getopt_1.20.3        calibrate_1.7.5      ellipsis_0.3.0      
[43] pkgconfig_2.0.3      dbplyr_1.4.2         tidyselect_0.2.5    
[46] reshape2_1.4.3       later_1.0.0          munsell_0.5.0       
[49] cellranger_1.1.0     tools_3.5.3          cli_2.0.1           
[52] generics_0.0.2       broom_0.5.3          evaluate_0.14       
[55] yaml_2.2.0           fs_1.3.1             packrat_0.5.0       
[58] nlme_3.1-143         whisker_0.4          formatR_1.7         
[61] proftools_0.99-2     xml2_1.2.2           compiler_3.5.3      
[64] rstudioapi_0.10      filelock_1.0.2       testthat_2.3.1      
[67] reprex_0.3.0         stringi_1.4.5        highr_0.8           
[70] ps_1.3.0             desc_1.2.0           lattice_0.20-38     
[73] vctrs_0.2.4          pillar_1.4.3         lifecycle_0.1.0     
[76] networkD3_0.4        httpuv_1.5.2         R6_2.4.1            
[79] promises_1.1.0       gridExtra_2.3        sessioninfo_1.1.1   
[82] codetools_0.2-16     lambda.r_1.2.4       assertthat_0.2.1    
[85] pkgload_1.0.2        rprojroot_1.3-2      withr_2.1.2         
[88] batchtools_0.9.12    parallel_3.5.3       hms_0.5.3           
[91] grid_3.5.3           rmarkdown_1.18       git2r_0.26.1        
[94] lubridate_1.7.4