User: mannoulag1

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mannoulag110
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Posts by mannoulag1

<prev • 20 results • page 1 of 2 • next >
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Comment: C: filtering genes by pearson correlation
... Thank you Jean-karim ...
written 3 months ago by mannoulag110
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Comment: C: filtering genes by pearson correlation
... Thank you Jean-Karim, I do this : #cor is symmetric, so we can keep only the half of the pairs of indices idx<-which( (abs(cor) > 0.8) & (upper.tri(cor)), arr.ind=TRUE) correlated.genes <- matrix[idx, ] Then I have to remove the duplicated genes from 'correlated.genes' ? ...
written 3 months ago by mannoulag110
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filtering genes by pearson correlation
... Hi biostars, I did a pearson correlation to my data (expression matrix), and I keep only the correlation >0.8 . How can I obtain the sub expression matrix of only these highly correlated genes. Thank you data<-t(matrix) cor = cor(data, use="pairwise.complete.obs", method="pearson") ...
cor() R rna-seq written 3 months ago by mannoulag110 • updated 3 months ago by Jean-Karim Heriche16k
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isa biclustering algorithm
... Hi, I need to do the isa biclustering algorithm on gene expression data matrix using ISA function of the Package ‘eisa’ library(eisa) thr.gene <- 2.7 thr.cond <- 1.4 set.seed(1) # to get the same results, always modules<- ISA(matrix, thr.gene=thr.gene, thr.cond= ...
R biclustering isa eisa gene expression data written 4 months ago by mannoulag110
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Comment: C: How filter genes to construct co-expression network?
... you can use the following code to filter 50% of genes: Library(genefilter) genes<-varFilter(exp) or this code for example to keep only 20%of genes: genes<-varFilter(exp, var.func=IQR, var.cutoff=0.8, filterByQuantile=TRUE) ...
written 6 months ago by mannoulag110
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Comment: C: Analysis of GEO2R
... thank you, I am analysing this dataset from the Affymetrix ATH1 microarray: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5632 ...
written 6 months ago by mannoulag110
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Comment: C: Analysis of GEO2R
... Hi Kevin and Happy new year 2018 , Thank you for your answer , ok, for the normalisation I already did it with the function rma in my R code, this give the same result? and also I tested the gcrma normalisation with the function gcrma, what is the best method for normalisation? for defining groups ...
written 6 months ago by mannoulag110
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Analysis of GEO2R
... Hi, Can I continue the analysis after obtening the toptable of differentially expressed genes using the R code of GEO2R or I should do my own analysis? I have many samples in my dataset, how can I define the groups in GEO2R because it influence the result of the toptable. The normalization in GEO2R ...
gene R geo2r written 6 months ago by mannoulag110 • updated 6 months ago by Kevin Blighe24k
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Comment: C: extracting submatrix from microarray
... Hi Kevin, yes , thank you very much ...
written 9 months ago by mannoulag110
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Comment: C: extracting submatrix from microarray
... thank you very much, with the following code I get a submatrix but with probe-ID, this can seem true? geneList<- biomaRt::getBM(attributes = c( "ensembl_gene_id", "go_id", "affy_ath1_121501"), filters = "go", values = "GO:.....", mart = mart) subMatrix<- MyExpressionMatrix[which(rown ...
written 9 months ago by mannoulag110

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