Identification of patterns related to linkage groups or disequilibrium by factor analysis

Abstract

Empirical patterns of linkage disequilibrium (LD) can be used to increase the statistical power of genetic mapping. This study was carried out with the objective of verifying the efficacy of factor analysis (AF) applied to data sets of molecular markers of the SNP type, in order to identify linkage groups and haplotypes blocks. The SNPs data set used was derived from a simulation process of an F2 population, containing 2000 marks with information of 500 individuals. The estimation of the factorial loadings of FA was made in two ways, considering the matrix of distances between the markers (A) and considering the correlation matrix (R). The number of factors (k) to be used was established based on the graph scree-plot and based on the proportion of the total variance explained. Results indicated that matrices A and R lead to similar results. Based on the scree-plot we considered k equal to 10 and the factors interpreted as being representative of the bonding groups. The second criterion led to a number of factors equal to 50, and the factors interpreted as being representative of the haplotypes blocks. This showed the potential of the technique, making it possible to obtain results applicable to any type of population, helping or corroborating the interpretation of genomic studies. The study demonstrated that AF was able to identify patterns of association between markers, identifying subgroups of markers that reflect factor binding groups and also linkage disequilibrium groups.

Análise de fatores para redução de dimensionalidade em estudos de predição genômica

“…Como o eixo X da Figura 2 representa também um ordenamento dos marcadores estudados, tendo por base o mapa genético da soja, constata-se que o desequilíbrio de ligação tende a ser mais forte entre marcadores localizados mais próximos no genoma. Assim padrões similares a blocos de haplótipos podem ser identificados OLIVEIRA et al, 2021;.…”

“…A fim de inferir sobre quantos e quais seriam os grupos de LD utilizou-se a análise de fatores (AF). A AF pode ser utilizada para examinar padrões reconhecendo grupos em que as correlações entre as variáveis sejam retidas dentro de cada grupo (OLIVEIRA et al, 2021).…”