An interesting thing happened at the first day of GAW 17 presentation. The group discussing collapsing methods announced that the collapsing methods don’t work. Two questions come out quickly. One is from Qunyuan Zhang (working with Michael Province). He basically asked whether such announcement is proper since so many works about collapsing methods have done and published. We also got pretty good results using collapsing schemes, so I asked another question, did your group members test on pathway level? If not, whether it’s because of the problem of collapsing methods or the genetic units.
Now, it turns out people are interesting on the tests using signaling pathways. Actually we did the tests on SNPs and Genes level, we didn’t get good results except two genes either. We didn’t do type I error and power tests because of the tight timeline. So two groups are interested in asking me to join in now. I may join the group with more signaling pathways based approaches to see whether I can get more helpful information.
The good part of the meeting is that people are working on the same dataset and you can see the position of your work among people. The bad part of the meeting with many junior discussants is that they can make some rather basic mistakes.
It seems most found only FLT1 and/or KDR which can be found using Plink. We detected these two genes significantly as well. In general, our work maybe among one of the qualified ones. People are crowed in front of our poster until the late of the next session.
The rest day is much easier since the similar works are distributed among the different topics. The impressive one is that Robert Elston and one group presented their work using the style similar "are you smarter than a 5th grader?" Another group used cartoon movie which is very interesting. Good to meet and communicate with all types of people who are working with you in the same field.
Sunday, October 17, 2010
Wednesday, October 13, 2010
IGES meeting
IGES is finished today. Try to write down something before I may forget.
IGES oral presentations include many interesting topics including rare variants, secondary phenotype, gene pleiotropy, multiple phenotypes, gene-gene interactions, gene-environment interactions, and signaling pathways. I list some about rare variants and secondary/multiple phenotype discussion.
Though it's still early, it looks that people has started to work on mapping rare variants that are associated with diseases. I noticed that there are interesting and new methods about rare variants. Particularly, a work from David Conti and his student considered two directions when collapsing rare variants. A work from Qunyuan Zhang and Michael Province used p-value based sum which considered both the significance and the direction of rare variants. The work from Joon Sang Lee et al. also tried to identify the optimal pooling size for rare variants.
A secondary phenotype from J Wang and S. Shete considered the problem differently from ours. We and the ones including Danyu Lin considered the secondary phenotype conditional on the primary disease status. However, this work tries to correct the bias that may be brought in if consider the secondary phenotype as either a case or a control. There are also a bunch of studies about multiple phenotypes. This intrigues me to wonder whether the problem of multiple phenotypes should include the problem of the secondary phenotype. Or any inherent connection between them.
People used a lot of linear or logistic regression based models by adding more variants including GXG, GXE and others. A simple mind comes up: can we get better models instead of only logistic or linear models?
People also tried to use Bayesian to do some works. According to my observation, most people used Bayesian is only for the convenience of calculation. The strategies of incorporating prior information are not that mature now.
IGES oral presentations include many interesting topics including rare variants, secondary phenotype, gene pleiotropy, multiple phenotypes, gene-gene interactions, gene-environment interactions, and signaling pathways. I list some about rare variants and secondary/multiple phenotype discussion.
Though it's still early, it looks that people has started to work on mapping rare variants that are associated with diseases. I noticed that there are interesting and new methods about rare variants. Particularly, a work from David Conti and his student considered two directions when collapsing rare variants. A work from Qunyuan Zhang and Michael Province used p-value based sum which considered both the significance and the direction of rare variants. The work from Joon Sang Lee et al. also tried to identify the optimal pooling size for rare variants.
A secondary phenotype from J Wang and S. Shete considered the problem differently from ours. We and the ones including Danyu Lin considered the secondary phenotype conditional on the primary disease status. However, this work tries to correct the bias that may be brought in if consider the secondary phenotype as either a case or a control. There are also a bunch of studies about multiple phenotypes. This intrigues me to wonder whether the problem of multiple phenotypes should include the problem of the secondary phenotype. Or any inherent connection between them.
People used a lot of linear or logistic regression based models by adding more variants including GXG, GXE and others. A simple mind comes up: can we get better models instead of only logistic or linear models?
People also tried to use Bayesian to do some works. According to my observation, most people used Bayesian is only for the convenience of calculation. The strategies of incorporating prior information are not that mature now.
Monday, October 11, 2010
IGES first day impression
The theme of first day workshop is “Next Generation Sequencing (NGS) in Genetic Epidemiological Studies”. Besides academic people, the presenting panel also includes people from companies such as Affymetrix, Illumina, and Gold Helix. The talks are interesting especially the ones from Suzanne Leal and Scott Williams. Scott talks about NGS from evolution point of view. Suzanne’s talk is more related to our works.
Suzanne’s talk basically reviewed the papers what we discussed in Journal Club and our GAW 17 submission abstract including
Cohen JC, Kiss RS, Pertsemlidis A, Marcel YL, McPherson R, Hobbs HH. (2004) Multiple rare
alleles contribute to low plasma levels of HDL cholesterol. Science,305,869872.
Madsen BE and Browning SR. (2009) A group-wise association test for rare mutations using
a weighted sum statistic. PLOS Genet, 5(2), e1000384.
Li B and Leal SM. (2008). Methods for detecting associations with rare variants for common dis-
eases: application to analysis of sequence data. Am J Hum Genet., 83(3), 311-321.
Morris AP and Zeggini E. (2010) A evaluation of statistical approaches to rare variant analysis
in genetic association studies. Genet Epidemiol 34(2), 188-193.
Price AL, Kryukov GV, de Bakker PI, Purcell SM, Staples J, Wei LJ, Sunyaev SR.(2009)
Pooled association tests for rare variants in exon-resequencing studies. Am J Hum Genet., 86(6),
832-838.
Another one she mentioned is her new work named KBAC (didn’t write down the whole name). In this work, the basic idea is to upweight the causal genotype. She also tested it upon gene interaction. I asked two questions here for her new work. (1). How to distinct causal genotypes from non-causal ones, especially in real data, and how distinct it from functional genotypes since she also mentioned that they are different. (2). How did they simulate gene interactions? For (1), she responded that, in simulation, they know whether the genotypes are causal or not. But in general in real data, there’s no way to distinct. For (2), she used some data that are known to involved gene interactions. That is to say, they use the known information.
She also pointed out several challenging problems in this field. I list some here: (1). Population structure/admixture, (2) gene X gene, gene X environment, (3) Signaling pathways, (4) Jointly analyzing rare and common variants, and (5) qualitatively and quantitatively.
Suzanne’s talk basically reviewed the papers what we discussed in Journal Club and our GAW 17 submission abstract including
Cohen JC, Kiss RS, Pertsemlidis A, Marcel YL, McPherson R, Hobbs HH. (2004) Multiple rare
alleles contribute to low plasma levels of HDL cholesterol. Science,305,869872.
Madsen BE and Browning SR. (2009) A group-wise association test for rare mutations using
a weighted sum statistic. PLOS Genet, 5(2), e1000384.
Li B and Leal SM. (2008). Methods for detecting associations with rare variants for common dis-
eases: application to analysis of sequence data. Am J Hum Genet., 83(3), 311-321.
Morris AP and Zeggini E. (2010) A evaluation of statistical approaches to rare variant analysis
in genetic association studies. Genet Epidemiol 34(2), 188-193.
Price AL, Kryukov GV, de Bakker PI, Purcell SM, Staples J, Wei LJ, Sunyaev SR.(2009)
Pooled association tests for rare variants in exon-resequencing studies. Am J Hum Genet., 86(6),
832-838.
Another one she mentioned is her new work named KBAC (didn’t write down the whole name). In this work, the basic idea is to upweight the causal genotype. She also tested it upon gene interaction. I asked two questions here for her new work. (1). How to distinct causal genotypes from non-causal ones, especially in real data, and how distinct it from functional genotypes since she also mentioned that they are different. (2). How did they simulate gene interactions? For (1), she responded that, in simulation, they know whether the genotypes are causal or not. But in general in real data, there’s no way to distinct. For (2), she used some data that are known to involved gene interactions. That is to say, they use the known information.
She also pointed out several challenging problems in this field. I list some here: (1). Population structure/admixture, (2) gene X gene, gene X environment, (3) Signaling pathways, (4) Jointly analyzing rare and common variants, and (5) qualitatively and quantitatively.
Tuesday, October 5, 2010
Touching words
Sometimes feel heart can be tired to get some things through. Occasionally, found pieces of words from a small notebook,
"The world is bound to no man
Little drops of water,
little grains of sand
make the mighty
ocean and
the pleasant land."
Whether I can bound my heart between the sky and the land, and have a moment of peace?... (I have uncertainties to ocean, so I'd rather put me between the sky and the land)
On the corner of the small notebook,
"You are the only one that fills my heart."
Different people have the different reasons to fill the different persons to their hearts. However, I'm happy there is a one for many people so that life can look beautiful sometimes.
"The world is bound to no man
Little drops of water,
little grains of sand
make the mighty
ocean and
the pleasant land."
Whether I can bound my heart between the sky and the land, and have a moment of peace?... (I have uncertainties to ocean, so I'd rather put me between the sky and the land)
On the corner of the small notebook,
"You are the only one that fills my heart."
Different people have the different reasons to fill the different persons to their hearts. However, I'm happy there is a one for many people so that life can look beautiful sometimes.
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