Replication of the principal component analyses of the human genome diversity panel

Genotype data

The dataset consisted of two files: a zip file including the genotype data of 660,918 SNPs from 1,043 individuals with the annotations of the SNPs, and a text file composed of the annotations of 953 individuals (see Data and software availability).

The annotations of individuals were used to create two subsets of the data. The first contained 157 individuals from Europe and the second contained 163 individuals from the Middle East & North Africa.

Analysis sets

For each geographic region subset of the data, we verified that no individuals had missing value rates above 3% and excluded SNPs with missing value rates above 1%. An additive genetic model was then used to encode each A/B SNP (A/A = 0, A/B = 1, B/B = 2), which converts categorical SNP values to numerics by assuming that the effect of the A/B heterozygote and B/B homozygote are proportional to the number of B alleles. SNPs with minor allele frequency below 5% were excluded to remove rare variants, which are more prone to genotyping errors. In addition, in order to decrease the required computation time and memory usage, redundant SNPs were removed by applying TagSNP⁴ (r2 > 0.8, window of 500,000 base pairs). The missing values were imputed by random sampling of each SNP. Then each SNP was centered and scaled to unit variance. All steps were performed using the SNPClust R package v1.0.0².

For the Europe subset, a total of 375,164 SNPs from 157 individuals were selected for analysis. This defines our Europe analysis set.

For the Middle East & North Africa subset, a total of 412,979 SNPs from 163 samples were selected for analysis. This defines our Middle East & North Africa analysis set.

For comparison, the supporting online material of Li et al. reported that individuals with missing value rates above 2.5% and SNPs with missing value rates above 5% were excluded. Table S1 of Li et al. reports that 156 individuals from Europe and 160 from the Middle East & North Africa were used and the supporting online material reports that 642,690 SNPs were used.

Principal component analyses

PCAs were applied on the two analysis sets and displayed using the SNPClust R package v1.0.0². Principal component analysis (PCA) is a dimensionality reduction method, which projects SNPs by linear combination to maximize the variance on successive axes, i.e. principal components, while constraining the axes to be orthogonal.

The supporting online material of Li et al. reports that they first computed the Identity-by-State (IBS) matrix among the 938 individuals by using PLINK (version not provided)⁵ and then performed PCAs on the IBS matrix for each region separately. In this study, PCAs were applied on the analysis sets and not on IBS matrices.

PCA of the Europe analysis set

The PCA of the Europe analysis set was displayed on the two first principal components (Figure 1). Individuals were grouped by population and the replicated figure matched closely with Li et al.'s Figure 2A.

Figure 1. Two first principal components of the Europe analysis set.

Visualization of the principal component analysis on 375,164 SNPs from 157 individuals from Europe. Individuals from North and South were differentiated in the first principal component and located in the lower and upper sides, respectively. Individuals from East and West were differentiated in the second and located in the right and left sides, respectively.

The explained variance was almost identical, as the replication stated 2.1% in PC1 and 1.6% in PC2, while Li et al.'s Figure 2A stated 2.4% and 1.6%, respectively.

Figure 2. Two first principal components of the Middle East & North Africa analysis set.

Visualization of the principal component analysis on 412,979 SNPs from 163 individuals from the Middle East & North Africa. Individuals from East and West were differentiated in the first principal component and located in the right and left sides, respectively. Individuals from North and South were differentiated in the second and located in the lower and upper sides, respectively.

PCA of the Middle East & North Africa analysis set

The PCA of the Middle East & North Africa analysis set was displayed on the two first principal components (Figure 2). Individuals were grouped by populations and the replicated figure matched closely with Li et al.'s Figure 2B.

Two differences from Li et al.'s analysis were noted, first the Bedouin and Druze populations exhibited a larger spread on PC1 in the original figure. Second, one Bedouin individual was located with Mozabite individuals, which did not appear in Li et al.'s Figure 2B.

The explained variance was slightly smaller, as the replication stated 3.1% in PC1 and 2.2% in PC2, while Li et al.'s Figure 2B stated 5.0% and 2.6%, respectively.