@article {138,
	title = {Comprehensive cell type decomposition of circulating cell-free DNA with CelFiE.},
	journal = {Nat Commun},
	volume = {12},
	year = {2021},
	month = {2021 05 11},
	pages = {2717},
	abstract = {<p>Circulating cell-free DNA (cfDNA) in the bloodstream originates from dying cells and is a promising noninvasive biomarker for cell death. Here, we propose an algorithm, CelFiE, to accurately estimate the relative abundances of cell types and tissues contributing to cfDNA from epigenetic cfDNA sequencing. In contrast to previous work, CelFiE accommodates low coverage data, does not require CpG site curation, and estimates contributions from multiple unknown cell types that are not available in external reference data. In simulations, CelFiE accurately estimates known and unknown cell type proportions from low coverage and noisy cfDNA mixtures, including from cell types composing less than 1\% of the total mixture. When used in two clinically-relevant situations, CelFiE correctly estimates a large placenta component in pregnant women, and an elevated skeletal muscle component in amyotrophic lateral sclerosis (ALS) patients, consistent with the occurrence of muscle wasting typical in these patients. Together, these results show how CelFiE could be a useful tool for biomarker discovery and monitoring the progression of degenerative disease.</p>},
	keywords = {Adult, Algorithms, Amyotrophic Lateral Sclerosis, B-Lymphocytes, Biomarkers, Case-Control Studies, Cell-Free Nucleic Acids, DNA Methylation, Epigenesis, Genetic, Female, Humans, Macrophages, Male, Monocytes, Muscle, Skeletal, Neutrophils, Organ Specificity, Pregnancy, Pregnancy Trimesters, T-Lymphocytes},
	issn = {2041-1723},
	doi = {10.1038/s41467-021-22901-x},
	author = {Caggiano, Christa and Celona, Barbara and Garton, Fleur and Mefford, Joel and Black, Brian L and Henderson, Robert and Lomen-Hoerth, Catherine and Dahl, Andrew and Zaitlen, Noah}
}
@article {134,
	title = {Regulatory genomic circuitry of human disease loci by integrative epigenomics.},
	journal = {Nature},
	volume = {590},
	year = {2021},
	month = {2021 02},
	pages = {300-307},
	abstract = {<p>Annotating the molecular basis of human disease remains an unsolved challenge, as 93\% of disease loci are non-coding and gene-regulatory annotations are highly incomplete. Here we present EpiMap, a compendium comprising 10,000~epigenomic maps across 800~samples, which we used to define chromatin states, high-resolution enhancers, enhancer modules, upstream regulators and downstream target genes. We used this resource to annotate 30,000~genetic loci that were associated with 540~traits, predicting trait-relevant tissues, putative causal nucleotide variants in enriched tissue enhancers and candidate tissue-specific target genes for each. We partitioned multifactorial traits into tissue-specific contributing factors with distinct functional enrichments and disease comorbidity patterns, and revealed both single-factor monotropic and multifactor pleiotropic loci. Top-scoring loci frequently had multiple predicted driver variants, converging through multiple enhancers with a common target gene, multiple genes in common tissues, or multiple genes and multiple tissues, indicating extensive pleiotropy. Our results demonstrate the importance of dense, rich, high-resolution epigenomic annotations for the investigation of complex traits.</p>},
	keywords = {Chromatin, Disease, Enhancer Elements, Genetic, Epigenesis, Genetic, Epigenomics, Female, Gene Regulatory Networks, Genetic Loci, Genome-Wide Association Study, Humans, Male, Multifactorial Inheritance, Organ Specificity, Reproducibility of Results},
	issn = {1476-4687},
	doi = {10.1038/s41586-020-03145-z},
	author = {Boix, Carles A and James, Benjamin T and Park, Yongjin P and Meuleman, Wouter and Kellis, Manolis}
}
