Hello,
In my transgenic rice (over-expression gene A), there are several lines with different expression levels, I've measured phenotype XX for N individuals in each line. So how can I make the conclusion whether A has effect on phenotype XX ?
For example, I have 10 lines with diverse expression levels of gene A, each line has 10 individuals, I measured each individuals in each line. I can make a boxplot to see this, but how can I get the significance extent. Or just get the mean value of phenotype in each line, then do pearson correlation between phenotype mean in each line and the expression levels?
Thank you very much!
1 answer
What you can do is linear regression (lm) using the expression of gene A to explain the phenotype, you can add any covariate (like batch or plot or whatever) to the regression to correct for it.
Using R it's simply lm(), in the summary you can get the significance and the effect.
There are other statistical methods, Tukey's test, for instance is widely used in agriculture when you compare different lines of crop.
Log in to answer this question.
-
Looking for gene expression profiles of different cell lines
written by yanbinwan •
-
How to make a connection b/w behavioral data Vs. gene expression data ?
written by sunnykevin97
-
Question about more complex makeContrasts from limma
written by tara •
-
Confounding factors when comparing effects of expression between RNA-seq samples and qPCR samples?
written by michael.nagle
-
How to evaluate the similarity of genes between two sample
written by afli
-
p-value calculation when comparing ratios of means (not means of ratios)
written by wildtype •
-
RNA-seq gene expression normalization for independent samples
written by Amos •
-
clustering cell population in different phenotypes
written by dnyanepooja •
-
Targeted resequencing analysis workflow
written by renjukrishna13 •
-
Comparing gene expression profiles between species
written by Mikael Huss
That's called a QTL study, so you could start googling based on that.