Multi-Omics Factor Analysis looks for underlying causes of tumor variations by parsing and weighting genomic, epigenomic, transcriptomic, proteomic, and metabolomic data.
Researchers applied a SNP heritability model called LDAK to genetic data for a range of human traits, uncovering relatively high levels of variance explained by SNPs.
Researchers profiled the genotypes and phenotypes for more than 700 induced pluripotent stem cell lines, uncovering between-individual sources of variation.
The computational method, called DeepCpG, is designed to tease out missing epigenetic marks and related DNA motifs in single-cell DNA methylation data.
A comparison of unstimulated and stimulated CD4+ T cells from young and old mice in two subspecies showed rising cell-to-cell expression variability with age.
