Additional file 1 of Assessing the female urogenital-rectal axis microbiome: focus on endometriosis and recurrent implantation failure

Supplementary Material 1: Supplementary Table S1. List of taxa identified at each of the study sites. Supplementary Table S2. Pairwise PERMANOVA results evaluating beta-diversity dissimilarities between groups, with covariates included in the model. Supplementary Table S3. Differential abundance analysis between body sites. Microbial taxa with a relative abundance > 0.01% were compared between groups using metagenomeSeq, which employs a zero-inflated Gaussian model to handle sparsity and variability in microbiome count data. Supplementary Table S4. Comparisons between vagina, cervix and uterus for each patient based on Bray-Curtis distance. Supplementary Table S5. Differential abundance analysis between body sites in sensitivity analysis. Microbial taxa with a relative abundance > 0.01% were compared between groups using metagenomeSeq, which employs a zero-inflated Gaussian model to handle sparsity and variability in microbiome count data. Supplementary Table S6. Differential abundance analysis between groups (endometriosis, RIF (recurrent implantation failure), and male factor) in vagina. Microbial taxa with a relative abundance > 0.01% were compared between groups using metagenomeSeq, which employs a zero-inflated Gaussian model to handle sparsity and variability in microbiome count data. Supplementary Table S7. Differential abundance analysis between groups (endometriosis, RIF (recurrent implantation failure), and male factor) in cervix. Microbial taxa with a relative abundance > 0.01% were compared between groups using metagenomeSeq, which employs a zero-inflated Gaussian model to handle sparsity and variability in microbiome count data. Supplementary Table S8. Differential abundance analysis between groups (endometriosis, RIF (recurrent implantation failure), and male factor) in uterus. Microbial taxa with a relative abundance > 0.01% were compared between groups using metagenomeSeq, which employs a zero-inflated Gaussian model to handle sparsity and variability in microbiome count data. Supplementary Table S9. Differential abundance analysis between groups (endometriosis, RIF (recurrent implantation failure), and male factor) in urine. Microbial taxa with a relative abundance > 0.01% were compared between groups using metagenomeSeq, which employs a zero-inflated Gaussian model to handle sparsity and variability in microbiome count data. Supplementary Table S10. Differential abundance analysis between groups (endometriosis, RIF (recurrent implantation failure), and male factor) in rectum. Microbial taxa with a relative abundance > 0.01% were compared between groups using metagenomeSeq, which employs a zero-inflated Gaussian model to handle sparsity and variability in microbiome count data. Supplementary Table S11. Differential abundance analysis of microbial taxa between endometriosis and control groups across all evaluated anatomical sites. Taxa with a relative abundance > 0.01% were analysed using the metacoder R package, which estimates effect sizes and statistical significance across taxonomic levels based on observed count differences and group contrasts. Supplementary Table S12. Differential abundance analysis of microbial taxa between RIF (recurrent implantation failure) and control groups across all evaluated anatomical sites. Taxa with a relative abundance > 0.01% were analysed using the metacoder R package, which estimates effect sizes and statistical significance across taxonomic levels based on observed count differences and group contrasts.