CONFINED: distinguishing biological from technical sources of variation by leveraging multiple methylation datasets
Sign Up to like & getrecommendations! Published in 2019 at "Genome Biology"
DOI: 10.1186/s13059-019-1743-y
Abstract: Methylation datasets are affected by innumerable sources of variability, both biological (cell-type composition, genetics) and technical (batch effects). Here, we propose a reference-free method based on sparse canonical correlation analysis to separate the biological from… read more here.
Keywords: methylation datasets; variability; confined distinguishing; biological technical ... See more keywords
Comprehensive analysis of gene expression and DNA methylation datasets identify valuable biomarkers for rheumatoid arthritis progression
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DOI: 10.18632/oncotarget.22918
Abstract: Rheumatoid arthritis (RA) represents a common systemic autoimmune disease which lays chronic and persistent pain on patients. The purpose of our study is to identify novel RA-related genes and biological processes/pathways. All the datasets of… read more here.
Keywords: methylation; analysis; methylation datasets; gene expression ... See more keywords