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VERSION:2.0
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20180703T155624Z
DTSTART:20180709T130000Z
DTEND:20180709T140000Z
SUMMARY:Centre for Biostatistics Seminar
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}sax-jj5vli6
 y-dkcvzq
DESCRIPTION:Our next seminar talk is at 2pm on Monday 11 June\, in Room G
 306A. Qian Liu will be speaking. \n\nGenetic causal pathways:  Mendelian
  randomization\, fine-mapping and colocalization\n\nA number of single n
 ucleotide polymorphisms (SNPs) are found to be associated with certain c
 linical outcomes and exposures. To date\, several statistical approaches
  have been developed with the aim to understand genetic causal pathways\
 , which are of clinical importance.\n\nExisting methods\, such as Mendel
 ian randomization\, fine-mapping and colocalization\, make the use of su
 mmary statistics from SNP-exposure and SNP-outcome association studies. 
 Mendelian randomization is designed for estimating causal effect of the 
 exposure on the outcome\, using exposure associated SNPs as instruments.
  In recent applications\, Fine-mapping and colocalization are tailored t
 o quantify the likelihood of SNPs causal to both the exposure and the ou
 tcome in genetic regions. Despite the different underlying assumptions b
 etween fine-mapping and colocalization\, we see similarities of the two 
 approaches. \n\nMendelian randomization alone is insufficient to identif
 y causal pathways starting from the SNP level. Recent research has propo
 sed a method by combining Mendelian randomization with fine-mapping. We 
 aim to compare the results from Mendelian randomization and fine-mapping
  with the former coupled with colocalization. In particular\, we will ma
 ke the use of publicly available summary data of BMI and diabetes from l
 arge studies\, using both of the approaches\, to explore underlying caus
 al mechanisms of diabetes. \n
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:Room G306A\, Jean McFarlane Building \, Oxford Rd\, Manchester\,
  M139PY
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