PLINK

To convert raw DNA data from 23andMe, AncestryDNA, MyHeritage, or FamilyTreeDNA (FTDNA) to PLINK binary format (.bed, .bim, .fam), you will have to first convert the raw file to 23andMe format. You can then convert it with PLINK 1.9 using --23file. Converting Raw DNA to 23andMe Format with AWK Windows users can use WSL to access awk; see How to Download the AADR Dataset (Linux & WSL). If your DNA file is already in 23andMe format, skip this section. ...

In an earlier post, PLINK PCA Tutorial: Running PCA in PLINK (Commands + Output), I showed the manual way to build a subset from the .ind/.fam. That works, but if you want to keep thousands of samples it gets tedious fast. Below is a one-liner using awk that generates a PLINK --keep file automatically from a list of populations. Prepare a list of populations to keep: Create a text file (e.g. pops) in the same directory as your reference .ind and .fam. Put one population label per line: ...

This post is a continuation of the previous one, where I demonstrated how to perform PCA with PLINK. While PLINK’s PCA is great for quick, exploratory analysis, smartpca (part of the EIGENSOFT toolset) is more commonly used in published genetic studies. Smartpca needs to be compiled on Linux or macOS, or alternatively installed via conda. I covered both methods in this earlier post: From EIGENSTRAT to PACKEDPED. As before, I’ll use a small subset. The focus here is on the technical process. One key difference in this post is that I’ll perform Linkage Disequilibrium (LD) pruning, which helps reduce SNP redundancy and improves the detection of population structure in PCA. ...

In this post, I’ll demonstrate how to perform a PCA on a PLINK dataset. Before we begin, we need to prepare a subset of samples we’re interested in analyzing. To do this, we’ll extract sample information from the .fam file. But first, we need to identify the samples of interest. For example, those from a specific population such as Sardinians. The easiest way is to open the corresponding .ind file and look at the population column, which is the third column in each row. Open the file in a text editor, and search for the population name, in this case, Sardinian. ...

The files downloaded in the previous blog post are distributed as an EIGENSTRAT-style .geno/.snp/.ind dataset. This naming can be confusing: the .snp and .ind files are the usual EIGENSTRAT metadata files, but the .geno file may either be plain-text EIGENSTRAT or binary PACKEDANCESTRYMAP. PACKEDPED format allows for easier downstream processing using the PLINK toolset. With PLINK, it becomes straightforward to extract sample subsets, filter SNPs, and perform a wide range of analyses. ...