With consent, collect additional population descriptor types and data along non-genetic dimensions, anticipating multiple possible study types during re-use.
Go to B STUDY PURPOSE and C ENVIRONMENT
Go to B STUDY PURPOSE and C ENVIRONMENT to guide use of population descriptors
Review consents/community agreements provided by sources of the pre-exisiting data. While following existing consent structures, use the available meta-data (e.g. geographic origin data, ethnicity data) to form the population descriptors. If necessary to create new labels, share and describe the formation of individual-level new labels/descriptors when publishing.
Go to B STUDY PURPOSE to guide use of population descriptors
Proceed with analysis. Emphasize any limitations of the pre-existing descriptors in all communications of results. If modifications to the group-level data were made, share and describe the formation of the new labels when publishing.
Do not proceed with your study.
Use a genetic relatedness matrix (i.e. pedigree informed or based on genetic similarity) and/or factor loadings (e.g. principal components) to determine and describe study population as well as control for genetic background
If you need to control for environment (e.g. as a covariate, to prevent spurious associations and/or to improve power), then go to C ENVIRONMENT
Population descriptors not needed. Type the variants themselves.
If you need to control for environment (e.g. as a covariate, to prevent spurious associations and/or to improve power), then go to C ENVIRONMENT
Kinship/descent-associated descriptors may be useful to find additional carriers (e.g. close or distant relatives) if done at a fine scale (e.g. genetic similarity, geographic origins, ethnicity of already sampled carriers).
If you need to control for environment (e.g. as a covariate, to prevent spurious associations and/or to improve power), then go to C ENVIRONMENT
Use a pedigree, genetic relatedness matrix (i.e. pedigree informed or based on genetic similarity) and/or factor loadings (e.g. principal components) to control for genetic background/analyze transmission patterns.
If you need to control for environment (e.g. as a covariate, to prevent spurious associations and/or to improve power), then go to C ENVIRONMENT
Possibly no population descriptor needed
If you need to control for environment (e.g. as a covariate, to prevent spurious associations and/or to improve power), then go to C ENVIRONMENT
If you need to control for environment (e.g. due to gene by environment interaction), then go to C ENVIRONMENT
Population descriptors no longer needed. Type the variants themselves
If you need to control for environment (e.g. due to gene by environment interaction), then go to C ENVIRONMENT
Genetic similarity could be useful proxy of similar modifier loci
If you need to control for environment (e.g. due to gene by environment interaction), then go to C ENVIRONMENT
You might consider measures of genetic similarity to identify individuals with similar allele frequencies and evolutionary histories
Go to C ENVIRONMENT
No population descriptors necessary given mechanisms are expected to be universal
Go to C ENVIRONMENT
Go to C ENVIRONMENT
Go to C ENVIRONMENT
No population descriptor may be needed (e.g. in an ancestral recombination graph)
If ancient DNA...
Avoid conflating cultural and genetic group namings - see Eisenmann et al 2018
Incorporate these variables.
Carefully consider use of proxy variables if needed. Possible proxies:
Collect information for as many potential environmental factors as possible and describe their source.
Incorporate these variables.
Carefully consider use of proxy variables if needed. Possible proxies:
Collect information for as many potential environmental factors as possible and describe their source.
Incorporate these variables.
Carefully consider use of proxy variables if needed. Possible proxies:
Collect information for as many potential environmental factors as possible and describe their source.
Incorporate these variables.
Carefully consider use of proxy variables if needed. Possible proxies:
Collect information for as many potential environmental factors as possible and describe their source.
Incorporate these variables.
Carefully consider use of proxy variables if needed. Possible proxies:
Collect information for as many potential environmental factors as possible and describe their source.