R studio v1

The 16S rRNA gene sequences of known free-living bacterial relatives or endosymbionts belonging to three host association categories such as obligate, long-term symbionts that co-occur with obligate endosymbionts, and facultative endosymbionts were obtained from NCBI GenBank to compare AT/GC content with the same 16S rRNA region of sequences in this study (Supplementary Table 2). All NCBI sequences were aligned with the 16S sequences here to obtain the same 16S rRNA gene region using NCBI BLASTn. The percent GC nucleotide composition was calculated for each of these aligned 16S rRNA sequence regions using BBMap (Bushnell, 2014 ) and Genomics % G–C Content Calculator (Science Buddies 2021). The box and whisker plot were generated based on GC content data using the package “ggplot” (Wickham, 2016 ) in R v.4.0.2 integrated in Rstudio v.1.3.959 (R Core Team, 2021 ).

Droplet data were extracted from the QuantaSoft Analysis software and imported into Microsoft Excel.
The data were filtered by removing runs in which any single droplet cluster had 100 or fewer accepted droplets and runs in which the total accepted droplet count was 10,000 or less. Runs on whole-genome amplified DNA (n = 4), samples from patients with known mosaicism in NEB (n = 1), samples with other CNVs in NEB (n = 9), samples run successfully in only one of the assays (n = 15), and samples with no successful runs in either assay were excluded. After the filtering steps, results from 98 independent samples remained, with 176 and 162 data rows for NEB IV and NEB VIII, respectively. Of these 98 samples, 39 were controls and 59 were from neuromuscular disorder patients and healthy family members thereof. The filtered data were extracted as comma-separated value (CSV) files. Subsequent statistical analyses were performed in RStudio v.1.3.959.

To accurately measure the effects of inbreeding with SNPs, statistical power depends on the variation in inbreeding in a given population, the depth and accuracy of the SNPs called, as well as sample and effect sizes (Keller et al. 2011 (link)). Methods used to estimate inbreeding in this study have considered these criteria during parameter selection, such as subsetting the data, depth adjustment for the GRM (Dodds et al. 2015 (link)), and using ID to confirm there was nonzero variation in heterozygosity measures (Weir and Cockerham 1973 (link); Szulkin et al. 2010 (link)). All statistical analyses and plotting were performed in R Studio v1.3.959, using the following packages: ggplot2 v3.3.2, ggpubr v0.4.0, ggfortify v0.4.10, and inbreedR (Stoffel et al. 2016 ; Tang et al. 2016 ; Wickham 2016 ; Kassambara 2020 ; R Core Team 2020 ). The inbreeding estimates F_H, F_GRM, and F_RoH were compared with Pearson’s correlations using the corr.test in R (Schielzeth 2010 ; Kardos et al. 2018 (link)) using the three datasets described above. Differences in inbreeding between mainland and Stewart Island founders and descendants were compared with F_RoH using the lm linear regression function in R, since linear regression is robust to violations of the normality assumption (Knief and Forstmeier 2018 (link)).

Statistical analyses were performed using statistical software (R v4.0.3; R Foundation for Statistical Computing; RStudio v1.3.959; RStudio, Auckland, New Zealand). The R packages used in this study were rms, reader, table one, pROC, ResourceSelection, and rmda. The predictive accuracy of the nomogram was measured using the C-statistic (bootstrap method, 1000 times). Calibration was evaluated using the Hosmer–Lemeshow statistics. Categorical variables were presented as frequencies with percentages, normally distributed continuous variables as means ± standard deviation, and other data as medians with interquartile ranges. Categorical variables were compared using the chi-square test or Fisher's test if the expected cell count was <5. The Student's t-test was used to compare normally distributed continuous variables. The Mann–Whitney U-test was used to compare non-normally distributed data. The significance level was set at 0.05 and two-sided tests were used.