Hi everyone,
I'm quite new to this field, so excuse me for any misuse of jargon or anything else. My project is about integrating GWAS data with scRNA-seq. In this project, I'm using MAGMA software, you can look the manual in this website https://ctg.cncr.nl/software/MAGMA/doc/manual_v1.07.pdf . In the gene-level analysis section of the manual, it said that it uses linear regression model, to see whether a particular gene-set is associated to the phenotype of interest. But, I just can't understand how can they reach to that conclusion using linear regression. I guess it will be easier for me to understand it if someone can elaborate in more details each term in the regression model, since in the manual it's just to brief for me to understand. And for side question, why do they use linear model instead of any other model? I would like to thank you in advance.
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andreas131298 •
Indeed one should know why they use such method before executing the work. For the above query, Why linear model was used? Here is a relatable link Introduction to Linear Regression. There in motivation section you will find "but by looking at the plot above he deduces that the position should follow a parabola" might give you glimpse of linear regression model. Please go through the link you will have some clarity. I hope You have your answer.
Hi, thank you for your response, I will take a look at it and and give you updates soon
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Have you read the MAGMA paper? I expect you will find your answer there.
Hi, Yeah I briefly read that already, however I have so much trouble going through the technicalities, so I would be happy if someone don't mind to explain it in a simpler way.