TY - GEN
T1 - Correlating cellular features with gene expression using CCA
AU - Subramanian, Vaishnavi
AU - Chidester, Benjamin
AU - Ma, Jian
AU - Do, Minh N.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/5/23
Y1 - 2018/5/23
N2 - To understand the biology of cancer, joint analysis of multiple data modalities, including imaging and genomics, is crucial. We propose the use of canonical correlation analysis (CCA) and a sparse variant as a preliminary discovery tool for identifying connections across modalities, specifically between gene expression and features describing cell and nucleus shape, texture, and stain intensity in histopathological images. Applied to 615 breast cancer samples from The Cancer Genome Atlas, CCA revealed significant correlation of several image features with expression of PAM50 genes, known to be linked to outcome, while Sparse CCA revealed associations with enrichment of pathways implicated in cancer without leveraging prior biological understanding. These findings affirm the utility of CCA for joint phenotype-genotype analysis of cancer.
AB - To understand the biology of cancer, joint analysis of multiple data modalities, including imaging and genomics, is crucial. We propose the use of canonical correlation analysis (CCA) and a sparse variant as a preliminary discovery tool for identifying connections across modalities, specifically between gene expression and features describing cell and nucleus shape, texture, and stain intensity in histopathological images. Applied to 615 breast cancer samples from The Cancer Genome Atlas, CCA revealed significant correlation of several image features with expression of PAM50 genes, known to be linked to outcome, while Sparse CCA revealed associations with enrichment of pathways implicated in cancer without leveraging prior biological understanding. These findings affirm the utility of CCA for joint phenotype-genotype analysis of cancer.
UR - http://www.scopus.com/inward/record.url?scp=85048073411&partnerID=8YFLogxK
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U2 - 10.1109/ISBI.2018.8363694
DO - 10.1109/ISBI.2018.8363694
M3 - Conference contribution
AN - SCOPUS:85048073411
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 805
EP - 808
BT - 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018
PB - IEEE Computer Society
T2 - 15th IEEE International Symposium on Biomedical Imaging, ISBI 2018
Y2 - 4 April 2018 through 7 April 2018
ER -