## User: LJ

LJ210
Reputation:
210
Status:
Trusted
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Last seen:
2 years, 11 months ago
Joined:
3 years, 10 months ago
Email:
j*************@gmail.com

#### Posts by LJ

<prev • 29 results • page 2 of 3 • next >
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... Can anyone tell me what the difference between the following code1 and code2 is? code1: pheno<-read.table(file="pdata.txt",header=T,row.names=1) head(d) subgroups batch sample1 1 1 sample2 1 1 sample3 1 1 sample4 ...
written 3.8 years ago by LJ210
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... ok,but i just saw a explanation for Covariates in ComBat [here][1] from Dr.Johnson (the author of "sva" package),it seems that he gave a opposite meaning of covariates, and the following is the answer to the purpose of including covariates in the mode: > Sorry about the late response. However, th ...
written 3.8 years ago by LJ210
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... So the code modcombat<-model.matrix(~1, data=pheno) combat_mydata<-ComBat(dat=mydata, batch=batch, mod=modcombat, par.prior=TRUE, prior.plots=FALSE) only removes batch effects but subgroups variation retained. However,when i add a covariate level--subgroups,the following code m ...
written 3.8 years ago by LJ210
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... Thanks.One more question for you,and the following code is what i used in ComBat: > pheno subgroups batch sample1 N 1 sample2 N 1 sample3 N 1 sample4 N 1 sample5 T ...
written 3.8 years ago by LJ210
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... Thank you guys for your replies. ...
written 3.8 years ago by LJ210
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... for example,n=10,m=1000,so the result returns a 10X10 matrix, and the 10 PCs explains 100% variance, but 10 components is far smaller than 1000 features,is it reasonable? ...
written 3.8 years ago by LJ210
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... Dear all， i have a dataset(n samples containing m dimensions,and **n﹤m**),and i would like to reduce the dimensionality of this data using PCA method("prcomp" function in R).However,it only returns a n-by-n matrix,So how to perform PCA when the dimensionality is greater than the number of sample ...
written 3.8 years ago by LJ210 • updated 3.8 years ago by Carlo Yague4.9k
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... Thanks for your reply. (1)My microarrays data was collected in two experiments,and I do the PCA plot, finding the samples are clustering based on the two experiment batches. So,i just set the batch information as the two experiment batches(1,1,1,...,2,2,2,...),then run the ComBat with the batches ...
written 3.8 years ago by LJ210
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... Dear all, I have a problem in processing my microarrays data.And I know how the batch effect is structured,soI would like to remove batch effect using ComBat. But I also want to adjust for unknown sources of noise using sva. Is there a way of combining these two methods? And is it feasible that i r ...
written 3.8 years ago by LJ210 • updated 14 months ago by Agustin Gonzalez-Vicente50
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... Thanks for you reply.Two questions for you : (1)So you mean the author used the residuals from the linear model to represent the protein levels and the residuals were protein levels after removing the population effects ? (2)As you can see in the following code: a<-rnorm(100) b<-rnorm ...
written 3.8 years ago by LJ210

#### Latest awards to LJ

Popular Question 3.1 years ago, created a question with more than 1,000 views. For removing batch effects using ComBat and SVA
Popular Question 3.3 years ago, created a question with more than 1,000 views. For removing batch effects using ComBat and SVA
Popular Question 3.3 years ago, created a question with more than 1,000 views. For Gaussian mixture model in R

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