Inbreeding increases homozygosity and therefore additive relationships within and among related individuals. The main cause of inbreeding is breeding of related individuals in which case the inbreeding coefficient (Fs) = 0.5asd where asd is the additive relationship among the individual's parents. An extreme case of inbreeding is the self-breeding occurring in plant inbred lines such as those generated by multiple generations of self-pollination, or by double haploid production. In the case of selfing generations, Fs = 1 - 0.5n where n is the number of selfing generations. If the parents of an individual are related and then it is self-bred, both sources for inbreeding should be accounted for in the progeny and Fs = 1 - 0.5n + 0.5n (0.5asd). In order to perform Best Linear Unbiased Prediction (BLUP), accurate calculation of the additive relationship coefficients matrix (A) or its inverse (A-1) is needed depending on the solving algorithm, or for single-step genomic BLUP where the submatrix A22 is used. Current methods to calculate A accounting for selfing generations require the expansion of the pedigree, which is computationally inefficient. Furthermore, freely available algorithms for setting up A-1 without generating A and inverting it do not contemplate selfing generations. The objective of this work was to develop efficient methods for calculating A and A-1 matrices accounting for inbreeding in self-bred individuals. Existing algorithms were adapted to account for selfing generations in A that require less memory than existing methods, and algorithms for the direct construction of A-1 accounting for inbreeding and selfing where developed in R. These algorithms are freely available at https://github.com/minesrebollo. In the future, these methods will be tested in large datasets and their performance will be reported.