10.1186/s13059-017-1308-x, Nature Genetics, Oct 11, 2017 doi:10.1038/ng.3969, Molecular Biology and Evolution, Sep 7, 2016, Nucleic Acids Research gkw627, Jul 12, 2016, eLife 5:e10557. Human regions orthologous to increasing-level enhancers show immune-cell-specific enhancer signatures as well as immune cell expression quantitative trait loci, while decreasing-level enhancer orthologues show fetal-brain-specific enhancer activity. Shahin Mohammadi 1 , Jose Davila-Velderrain 2 , Manolis Kellis 2 Affiliations 1 MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Rather, in mice engineered to develop Alzheimerâs-like symptoms, they found that immune cells start to change even before neural changes are observed[21], Kellis is a member of the Genotype-Tissue Expression (GTEx) project that seeks to elucidate the basis of disease predisposition. We validated our predictions with the use of directed perturbations in samples from patients and from mice and with endogenous CRISPR-Cas9 genome editing in samples from patients. We show that tumor driver load from RNA-seq mutational calls are significantly different between responders and non-responders. ChromHMM is distinguished by its modeling emphasis on combinations of marks, its tight integration with downstream functional enrichment analyses, its speed, and its ease of use. Sep 3, 2015; Nature Biotechnology 33(8):825-6. [26], As of July 2018, Manolis Kellis has authored 187 journal publications[29] that have been cited 68,380 times. RiVIERA identified meaningful tissue-specific enrichments for enhancer regions defined by H3K4me1 and H3K27ac for Blood T-Cell specifically in the nine autoimmune diseases and Brain-specific enhancer activities exclusively in Schizophrenia. Here we use the same approach to identify these elements in multiple cell types and investigate their roles in cell-type-specific gene expression. Manolis Kellis is an associate professor of Computer Science in the EECS Department in the area of Computational Biology. Here we provide a systematic motif analysis for 427 human ChIP-seq data sets using motifs curated from the literature and also discovered de novo using five established motif discovery tools. Juul, Madsen, Guo, Bertl, Hobolth, Kellis, Pedersen, Understanding the mutational processes that act during cancer development is a key topic of cancer biology. We find that for several diseases, topscoring SNPs are precisely positioned within enhancer elements specifically active in relevant cell types. 2019 Aug 5. doi: 10.1038/s41592-019-0502-z, Nucleic Acids Research 47(14):7235-7246, Aug 22 2019. doi: 10.1093/nar/gkz538, Molecular Biology and Evolution. We describe a universal gauge to measure molecular brain age using transcriptome analysis of four human postmortem cohorts (n = 673, ages 25-97) free of neurological disease. In several cases a disease variant affects a motif instance for one of the predicted causal regulators, thus providing a potential mechanistic explanation for the disease association. We show that even gene trees with only a few dozen genes often have millions of optimal reconciliations and present an algorithm to efficiently sample the space of optimal reconciliations uniformly at random in O(mn(2)) time per sample, where m and n denote the number of genes and species, respectively. There is growing recognition that mammalian cells produce many thousands of large intergenic transcripts. doi: 10.26508/lsa.201900303, Nature. To overcome these limitations, we develop Causal Multivariate Mediation within Extended Linkage disequilibrium (CaMMEL), a novel Bayesian inference framework to jointly model multiple mediated and unmediated effects relying only on summary statistics. The methylation imbalances at thousands of loci are explainable by different relative frequencies of the methylated and unmethylated states for the two alleles. We find that species at a broad range of distances are comparably effective informants for pairwise comparative gene identification, but that these are surpassed by multi-species comparisons at similar evolutionary divergence. The VDR is a member of the nuclear receptor superfamily of ligand-inducible transcription factors and binds its major ligand, calcitriol, via its C-terminal ligand-binding domain. Interestingly, Eric Lander (one of the founding fathers in this country on large-scale genomic research) was Kellis’s phd advisor and was in the thesis committee of Pachter when he did his phd in math at MIT. This has increased the urgency of understanding the regulatory genome as a key component for translating genetic results into mechanistic insights and ultimately therapeutics. Kellis started comparing the genomes of yeast species as an MIT graduate student. Each link type shows a "recombination rate valley" of significantly reduced recombination rate compared to matched control regions. Here we report the genome sequences of six Candida species and compare these and related pathogens and non-pathogens. This is partly remedied by prioritization of disease-associated variants that overlap GWAS-enriched epigenomic annotations. Given a good program for this fundamental subroutine, the algorithm is quite easy to implement. Ron Rivest, Erik Demaine, Piotr Indyk, Srinivas Devadas and others. We develop a novel computational model to classify exosomal transcripts into tumor and non-tumor components and establish relevance in immune checkpoint blockade therapy. Genome Research doi:10.1101/gr.144899.112, March 19, 2013, Nature Biotechnology 30:1095-1106, Nov 2012, Nature, doi:10.1038/nature09906, Epub ahead of print: March 23, 2011, Nature Biotechnology 2010 Aug;28(8):817-25. We have previously developed a chromatin-immunoprecipitation-based microarray method (ChIP-chip) to locate promoters, enhancers and insulators in the human genome. We infer for each disorder group disease gene networks with preferential cell-type specific activity that can aid the design and interpretation of cell-type resolution experiments. It combines multiple genome-wide epigenomic maps, and uses combinatorial and spatial mark patterns to infer a complete annotation for each cell type. Long intergenic noncoding RNAs (lincRNAs) play diverse regulatory roles in human development and disease, but little is known about their evolutionary history and constraint. Moreover, by using only the overlap of functional links and DNA methylation in germ cells, we are able to predict the recombination rate with high accuracy. Here, we use a multivariate Hidden Markov Model to reveal 'chromatin states' in human T cells, based on recurrent and spatially coherent combinations of chromatin marks. The SCINET framework is applicable to any organism, cell-type/tissue, and reference network; it is freely available at https://github.com/shmohammadi86/SCINET. ( 7243 ):108-12 the predictions for over 100 lincRNAs, using cell-based.! Evolutionary signatures of protein-coding regions and disease is the representation of heterogeneous data with different qualities networks... 7243 ):108-12 large multi-exonic RNAs across four mouse cell types new,... 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