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MendelAimSelection.jl

This analysis option selects the SNPs that are most informative at predicting ancestry for your data — the best Ancestry Informative Markers (AIMs).

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Overview

Mendel AIM Selection is a component of the umbrella OpenMendel project. This analysis option selects the SNPs that are most informative at predicting ancestry for your data — the best Ancestry Informative Markers (AIMs).

Installation

Note: The three OpenMendel packages (1) SnpArrays, (2) MendelSearch, and (3) MendelBase must be installed before any other OpenMendel package will run. It is easiest if these three packages are installed in the above order and before any other OpenMendel package.

Within Julia, use the package manager to install MendelAimSelection:

pkg> add https://github.com/OpenMendel/MendelAimSelection.jl.git

This package supports Julia v1.0+

Input Files

The MendelAimSelection analysis package uses the following input files. Example input files can be found in the data subfolder of the MendelAimSelection project. (An analysis won’t always need every file type below.)

Control File: Specifies the names of your data input and output files and any optional parameters (keywords) for the analysis. (For a list of common keywords, see Keywords Table).
Locus File: Names and describes the genetic loci in your data.
Pedigree File: Gives information about your individuals, such as name, sex, family structure, and ancestry.
Phenotype File: Lists the available phenotypes.
SNP Definition File: Defines your SNPs with information such as SNP name, chromosome, position, allele names, allele frequencies.
SNP Data File: Holds the genotypes for your data set. Must be a standard binary PLINK BED file in SNP major format. If you have a SNP data file you must have a SNP definition file.

Control file

The Control file is a text file consisting of keywords and their assigned values. The format of the Control file is:

Keyword = Keyword_Value(s)

Below is an example of a simple Control file to run AIM Selection:

#
# Input and Output files.
#
snpdata_file = 1000genomes_chr1_eas.bed
snpdefinition_file = 1000genomes_chr1_eas.snp
pedigree_file = 1000genomes_chr1_eas.ped
output_file = 1000genomes_chr1_eas Output.txt
#
# Analysis parameters for AIM Selection option.
#

In the example above, the four keywords specify the input and output files: 1000genomes_chr1_eas.bed, 1000genomes_chr1_eas.snp, 1000genomes_chr1_eas.ped and 1000genomes_chr1_eas Output.txt. The text after the ‘=’ are the keyword values. The names of keywords are not case sensitive. (The keyword values may be case sensitive.) A list of OpenMendel keywords common to most analysis package can be found here.

Data Files

AIM Selection requires a Control file, and a Pedigree file. Genotype data can be included in the Pedigree file, in which case a Locus file is required. Alternatively, genotype data can be provided in a SNP data file, in which case a SNP Definition File is required. OpenMendel will also accept PLINK format FAM and BIM files. Details on the format and contents of the Control and data files can be found on the MendelBase documentation page. There are example data files in the AIM Selection data folder.

Running the Analysis

To run this analysis package, first launch Julia. Then load the package with the command:

 julia> using MendelAimSelection

Next, if necessary, change to the directory containing your files, for example,

 julia> cd("~/path/to/data/files/")

Finally, to run the analysis using the parameters in your Control file, for example, Control_file.txt, use the command:

 julia> AimSelection("Control_file.txt")

Note: The package is called MendelAimSelection but the analysis function is called simply AimSelection.

Citation

If you use this analysis package in your research, please cite the following reference in the resulting publications:

OPENMENDEL: a cooperative programming project for statistical genetics. Zhou H, Sinsheimer JS, Bates DM, Chu BB, German CA, Ji SS, Keys KL, Kim J, Ko S, Mosher GD, Papp JC, Sobel EM, Zhai J, Zhou JJ, Lange K. Hum Genet. 2019 Mar 26. doi: 10.1007/s00439-019-02001-z. [Epub ahead of print] PMID: 30915546

Acknowledgments

This project is supported by the National Institutes of Health under NIGMS awards R01GM053275 and R25GM103774 and NHGRI award R01HG006139.