SomaLogic

SomaLogic data analysis

A summary

File Description
doc/ Documents and auxiliary files
SomaLogic_analysis_plan.md Analysis plan
SomaLogic.R Generation of axuiliary files such as SomaLogic.list for a list of proteins
format.sh GWAS summary statistics reformat using GNU Parallel, e.g., format.sh FHS
format.sb SLURM scripts
format.subs Processing of a particular study and array job
list.sh Generation of received and output file lists and directories
metal.sh Generation and execution of individual METAL entries
metal.sb SLURM routine
QCGWAS.sb QCGWAS – SLURM
QCGWAS.R QCGWAS – R
clump.sh PLINK clumping
clump.sb SLURM routine
qml.sh Q-Q, Manhattan (qqman.R) and LocusZoom plots
qml.sb SLRUM routine

The workflows involve the following components,

  1. Data are downloaded from the Box server to dedicated directories; as noted in box.md.
  2. Available entries are catalogued in a list, as done by list.*.
  3. GWAS summary statistics associated with the list are reformatted by format.* according to the analysis plan.
  4. When necessary, the summary statistics are examined with R/QCGWAS.
  5. Batch scripts for metal analysis are then generated and executed with metal.*.
  6. Downstream analysis according to plan.

Installation

The repository can be downloaded locally with

git clone https://github.com/jinghuazhao/SomaLogic

References

SomaLogic, wiki, GenomeWeb reports, the 1129 assay (1129.tsv, derived from SSM-011-Rev-11-SOMAscan-Assay-V1-1k-Content.pdf), 1310 assay (1310.tsv, derived from SSM-045-REV-1-SOMAscan-Assay-1-3k-Content-1.pdf, and Rev-2), and SOMAscan Proteomic Assay Technical White Paper.

Behar M (2018). Proteomics might have saved my mother’s life and it may yet save mine. The New York Times Magazine, https://www.nytimes.com/interactive/2018/11/15/magazine/tech-design-proteomics.html, also here (PDF).

Ganz P, et al. (2016). Development and validation of a protein-based risk score for cardiovascular outcomes among patients with stable coronary heart disease. JAMA 315(23):2532-2541. doi:10.1001/jama.2016.5951, https://jamanetwork.com/journals/jama/fullarticle/2529627

Suhre K, et al. (2017). Connecting genetic risk to disease end points through the human blood plasma proteome. Nat Commun 8, 14357, https://doi.org/10.1038/ncomms14357 (https://metabolomics.helmholtz-muenchen.de/pgwas/).

Sun BB, et al. (2018). Genomic atlas of the human plasma proteome. Nature 558: 73–79 (http://www.phpc.cam.ac.uk/ceu/proteins/).

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