Closed:GWAS on different forms of phenotype variable.
Entering edit mode
4 months ago

Dear all, These days, i am doing GWAS and read a lot of literatures about the standards of gwas followed by researchers. The literature is flooded with different methods of GWAS. So far, I read different types of GWAS articles, like in humans, plants, animals etc. But my field is related to plant sciences. I have a confusion about the phenotype data, that is used as a variable in GWAS studies. Let me explain in detail. In some studies, I read that mean values has been used as a phenotype variable. For example, A person has applied a treatment to different varieties of plants >400. He took data of different parameters of plant, such as plant height, grain length, grain width(suppose in wheat) etc. after the treatment. He also used control group to compare the effect of treatment on the treated group i-e he took the data for both control and treatment. After collecting the data he calculated the mean values by the adding the replicates, and applied gwas on mean values of treatment and control separately . How can we compare the gwas results of treatment and control in this case? The second method used in some studies is, they calculated the mean values for control and treatment by adding each replication of individual plant varieties and calculated the ratio by dividing treatments with control, and used the ratio values for GWAS. The reasons for this could be to control the variation in the data, as in field conditions, plants are exposed to different types of stresses, in addition to the stress applied by the researcher. This creates a lot of variation in the dataset. So to control the variation, ratio is calculated. For example, if mean plant height in a variety is 30 in treatment and 20 in control, then the ratio would be 30/20 =1.5. In this case, the plant height is increased, because the treated chemical could be any phytohormone, that increases the height of plant. But incase where the plant height is decreased, like in any salt or drought treatment, the ratio value should be zero. Like in treatment the height is 15 and in control the height is 20, then the ratio will be 15/20 =0.75.
Third type of phenotypic variables used in some gwas studies PCA scores. They took the phenotype data, calculated the mean values of each replication and then applied PCA . They used the PC scores of PC1, which captured most of variation, as a phenotype variable in GWAS for association with genotype data and identified key genes controlling complex traits. So my confusion is that, if we want to use Principal component scores of phenotype data in GWAS, what does it refers to, If ratio values of phenotype data is used, as I discussed earlier, what should be the standards. Need expert suggestions, Thanks in Advance.

SNP R genome • 203 views
This thread is not open. No new answers may be added
Traffic: 2387 users visited in the last hour
Help About
Access RSS

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6