FIGURE 1 from Exogenous Sequences in Tumors and Immune Cells (Exotic): A Tool for Estimating the Microbe Abundances in Tumor RNA-seq Data
Year: 2023
Type: other
Abstract: Summary and validation of the {exotic} tool. A, Schematic of the {exotic} tool, showing the process of aligning raw RNA-seq FASTQs to databases for human and microbial identification, followed by filtering to remove contaminants. Filtering steps include the removal of samples with a high percentage of exogenous reads and samples from small batches that prevent contaminant checks, as well as reads that align to microbes found to be contaminants by statistical or literature review–based filtering. The remaining samples’ microbe counts are normalized by VOOM-SNM. B, The loss of reads at each step of the {exotic} tool. C, Normalization removes batch effects from the sequencing center (all ORIEN samples were sequenced at TCC, and all TCGA at UNC) and preservation method from decontaminated counts. D, Microbe-level filtering removes taxa that align with input RNA concentration and are consistently found in negative controls. Microbes with strong literature precedence as commensals are returned. E, Comparison of the prevalence of Fusobacterium found by {exotic} compared with literature values captured by non–RNA-seq–based approaches, with a much higher prevalence appearing in colorectal samples compared with all cancer types. F, A comparison of the prevalence of various taxa to those reported by Poore and colleagues (9) for TCGA dataset finds mostly lower prevalences of bacteria and viruses but includes the identification of fungi (Malassezia). G, The abundance of microbes found in a 16S-based validation dataset compared with the RNA-seq–based approach. H, Comparison of the distances between microbes identified by 16S and RNA-seq for samples from the same patient and tumor (Paired = TRUE, Tumor) and adjacent normal tissue (Paired = TRUE, Normal) versus samples from different patients (Paired = FALSE).
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4388865973