R/mia.R
Tito2024QMP.RdThe study combined Quantitative Microbiome Profiling (QMP) with extensive patient phenotyping from a group of 589 colorectal cancer (CRC) patients, advanced adenoma (AA) patients, and healthy controls. By implementing confounder control and quantitative profiling methods, the study was able to reveal potential misleading associations between microbial markers and colorectal cancer development that were driven by other factors like intestinal inflammation, rather than the cancer diagnosis itself.
data(Tito2024QMP)A TreeSummarizedExperiment with 676 features and 589 samples. The rowData contains species. The colData includes:
(character) Sample ID from the corresponding study
(factor) Diagnosis type, with possible values: "ADE" (advanced adenoma), "CRC" (colorectal cancer), "CTL" (control)
(factor) Colonoscopy result, with possible values: "FIT_Positive", "familial_risk_familial_CRC_FCC", "familial_risk_no", "abdomil_complaints"
Raúl Y. Tito, Sara Verbandt, Marta Aguirre Vazquez, Leo Lahti, Chloe Verspecht, Verónica Lloréns-Rico, Sara Vieira-Silva, Janine Arts, Gwen Falony, Evelien Dekker, Joke Reumers, Sabine Tejpar & Jeroen Raes (2024). Microbiome confounders and quantitative profiling challenge predicted microbial targets in colorectal cancer development. Nature Medicine,30, 1339-1348. https://doi.org/10.1038/s41591-024-02963-2