@article {Rau827022, author = {Andrea Rau and Regina Manansala and Michael J. Flister and Hallgeir Rui and Florence Jaffr{\'e}zic and Denis Lalo{\"e} and Paul L. Auer}, title = {Individualized multi-omic pathway deviation scores using multiple factor analysis}, elocation-id = {827022}, year = {2020}, doi = {10.1101/827022}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Malignant progression of normal tissue is typically driven by complex networks of somatic changes, including genetic mutations, copy number aberrations, epigenetic changes, and transcriptional reprogramming. To delineate aberrant multi-omic tumor features that correlate with clinical outcomes, we present a novel pathway-centric tool based on the multiple factor analysis framework called padma. Using a multi-omic consensus representation, padma quantifies and characterizes individualized pathway-specific multi-omic deviations and their underlying drivers, with respect to the sampled population. We demonstrate the utility of padma to correlate patient outcomes with complex genetic, epigenetic, and transcriptomic perturbations in clinically actionable pathways in breast and lung cancer.Competing Interest StatementThe authors have declared no competing interest.}, URL = {https://www.biorxiv.org/content/early/2020/05/30/827022}, eprint = {https://www.biorxiv.org/content/early/2020/05/30/827022.full.pdf}, journal = {bioRxiv} }