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research [2014/11/24 00:35]
ivan
research [2016/06/20 19:52]
dvuzman
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 ===== Research Overview ===== ===== Research Overview =====
  
-We are a computational genetics and genomics lab. Our main research is on genetic variation, including mechanisms of spontaneous mutagenesis,​ functional effects of mutations and allelic variants, population genetics and relationship between genotype and phenotype. As part of our research we develop new computational and statistical methods to assist DNA sequencing studies. ​+We are a computational genetics and genomics lab. Our main research is on genetic variation, including mechanisms of spontaneous mutagenesis,​ functional effects of mutations and allelic variants, population genetics and relationship between genotype and phenotype. As part of our research we develop new computational and statistical methods to assist DNA sequencing studies.
  
-<WRAP clear></​WRAP>​+----
  
-**Understanding mutations from sequencing data**\\ +<WRAP rightalign>//​**Understanding mutations from sequencing data**//</​WRAP>​
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 Mutations are the source of population genetic variation; they fuel evolution and cause disease. Data on de novo germ-line mutations are now available from whole genome sequencing of parent-child trios. Cancer genomics provides data on somatic cancer mutations. We analyze statistical properties of germ-line and somatic cancer mutations alongside epigenomic datasets. We believe that this analysis has a potential to generate biologically relevant hypotheses on leading mechanisms of spontaneous mutations in humans. From an evolutionary viewpoint, it can be informative about the evolution of mutation rate. On the practical side, accurate models of mutation rate will enhance statistical methods of cancer genomics and neuropsychiatric genetics aimed at mapping genes using recurrent de novo mutations. Mutations are the source of population genetic variation; they fuel evolution and cause disease. Data on de novo germ-line mutations are now available from whole genome sequencing of parent-child trios. Cancer genomics provides data on somatic cancer mutations. We analyze statistical properties of germ-line and somatic cancer mutations alongside epigenomic datasets. We believe that this analysis has a potential to generate biologically relevant hypotheses on leading mechanisms of spontaneous mutations in humans. From an evolutionary viewpoint, it can be informative about the evolution of mutation rate. On the practical side, accurate models of mutation rate will enhance statistical methods of cancer genomics and neuropsychiatric genetics aimed at mapping genes using recurrent de novo mutations.
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- +<WRAP leftalign>//​**Functional effect of allelic variants**//</​WRAP>​
-**Functional effect of allelic variants**\\ +
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 It is essential to identify, among a myriad of allelic variants, those with the effect on molecular function. For predicting the functional effect of sequence variants in protein coding regions we rely on the comparative sequence analysis and analysis of protein structure. We are continuously developing and maintaining PolyPhen-2 – a computational method for predicting the effect of missense mutations and SNPs. We are interested in dependence of the functional effect of coding variants on genetic background, and are using comparative genomics to identify suppressors of coding mutations. It is essential to identify, among a myriad of allelic variants, those with the effect on molecular function. For predicting the functional effect of sequence variants in protein coding regions we rely on the comparative sequence analysis and analysis of protein structure. We are continuously developing and maintaining PolyPhen-2 – a computational method for predicting the effect of missense mutations and SNPs. We are interested in dependence of the functional effect of coding variants on genetic background, and are using comparative genomics to identify suppressors of coding mutations.
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- +<WRAP rightalign>//​**Population genetics**//</​WRAP>​
-**Population genetics**\\ +
 {{ :​bottleneck_2.png?​nolink&​550|}} {{ :​bottleneck_2.png?​nolink&​550|}}
 We are interested in population genetics as a lens through which we can study microevolution. Dynamics of allele propagation in populations depends on a number of evolutionary forces. Now, development of theoretical models is enhanced by the availability of massive sequencing datasets. We are interested in population genetics as a lens through which we can study microevolution. Dynamics of allele propagation in populations depends on a number of evolutionary forces. Now, development of theoretical models is enhanced by the availability of massive sequencing datasets.
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- +<WRAP leftalign>//​**Evolution,​ maintenance and allelic architecture of complex traits**//</​WRAP>​
-**Evolution,​ maintenance and allelic architecture of complex traits**\\ +
 {{:​heritability.png?​nolink&​400 |}} {{:​heritability.png?​nolink&​400 |}}
 Despite widespread interest in the genetics of complex traits (including common human diseases), basic principles of complex trait genetics are still poorly understood. We attack the problem from three directions. First, we develop theoretical models of evolution and maintenance of complex trait variation under various allelic architectures. Second, we are involved in a large zebrafish screen aiming at identification of key parameters of allelic architecture of complex traits. Third, we work on statistical methods for the analysis of available genomic data in phenotyped human populations. This includes methods for predicting complex phenotypes from genotypes. Despite widespread interest in the genetics of complex traits (including common human diseases), basic principles of complex trait genetics are still poorly understood. We attack the problem from three directions. First, we develop theoretical models of evolution and maintenance of complex trait variation under various allelic architectures. Second, we are involved in a large zebrafish screen aiming at identification of key parameters of allelic architecture of complex traits. Third, we work on statistical methods for the analysis of available genomic data in phenotyped human populations. This includes methods for predicting complex phenotypes from genotypes.
  
 <WRAP clear></​WRAP>​ <WRAP clear></​WRAP>​
- +<WRAP rightalign>//​**Computational and statistical methods for sequencing studies**//</​WRAP>​
-**Computational and statistical methods for sequencing studies**\\ +
 {{ :​sung.png?​nolink&​300|}} {{ :​sung.png?​nolink&​300|}}
 We develop computational and statistical methods for sequencing studies. VT-test is designed to detect combined association of rare variants with a complex phenotype. SNPTrack has been developed for gene mapping in model organisms. We continue developing new methods including methods that benefit from pedigree collection and functional genomic data. We actively participate in collaborative projects devoted to sequencing of populations with common diseases. We develop computational and statistical methods for sequencing studies. VT-test is designed to detect combined association of rare variants with a complex phenotype. SNPTrack has been developed for gene mapping in model organisms. We continue developing new methods including methods that benefit from pedigree collection and functional genomic data. We actively participate in collaborative projects devoted to sequencing of populations with common diseases.
  
 <WRAP clear></​WRAP>​ <WRAP clear></​WRAP>​
- +<WRAP leftalign>//​**[[Brigham Genomic Medicine ​(BGM)]]**//</​WRAP>​ 
-**Personal Genome Consultation Service ​(PGCS)**\\ +[[http://​genetics.bwh.harvard.edu/​vuzmanlab]]
 {{:​pgcs.png?​nolink&​400 |}} {{:​pgcs.png?​nolink&​400 |}}
 The lab is intertwined with the computational component of Personal Genome Consultation Service. This service aims at discovering genes underlying previously uncharacterized human Mendelian diseases of rare diseases with unknown genetic etiology. We use genomic data of individual pedigrees to identify mutations potentially causing the phenotypes. The lab is intertwined with the computational component of Personal Genome Consultation Service. This service aims at discovering genes underlying previously uncharacterized human Mendelian diseases of rare diseases with unknown genetic etiology. We use genomic data of individual pedigrees to identify mutations potentially causing the phenotypes.
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