User: Rahil
Rahil • 180
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Posts by Rahil
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... Hi all,
I have RNAseq of 12 mouse models (4 condition) that are all normalized together using Deseq2 (median of ratios). I want to do ssGSEA analysis to see the enrichment of one signature for each sample.
Should they be normalized for gene length as well? or can I do it with what I have (normaliz ...
written 6 days ago by
Rahil • 180
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... Hi all,
I have microarray data of two conditions.
When I did GSEA using fgsea the signature/ geneset was significantly higher in group1 vs group2.
However, when I did ssGSEA and used boxplot to show and assess significancy, that signature it is not significantly enriched in group1?
Can anyone ...
written 8 days ago by
Rahil • 180
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... Hi all, I got CNA data from TCGA. They provided putative copy-number calls on 616 cases determined using GISTIC 2.0. The values are -2, -1, 0, 1, 2.
I have two groups, high-risk & low-risk.
I would like to compare the frequency of CNA for each gene, between two groups.
How can I find which ge ...
written 12 days ago by
Rahil • 180
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... Hi, I have the same question. Could you find a way to determine which genes are more frequently deleted or amplified in group 1 vs group 2? ...
written 18 days ago by
Rahil • 180
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... Hello all,
I have expression profile of 5 different conditions with 2 different time point, all in one matrix.
I am using RMA to normalize them.
Can I normalize them all together? or I have to normalize each condition with control group separately?
If I normalize them all together don't I lose the ...
written 3 months ago by
Rahil • 180
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... Try this https://www.r-bloggers.com/2016/10/converting-mouse-to-human-gene-names-with-biomart-package/
or this https://syngoportal.org/convert.html ...
written 4 months ago by
Rahil • 180
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Comment:
C: PCA in a RNA seq analysis
... Dear @Kevin
Is it possible to find the genes that best characterizing each group using PCA?
I have 630 genes and 300 samples that are annotated in 4 cancer subtypes, using PCA, 4 groups are clear. I want to find genes that best characterize each subtype.
Using PC1 loadings I could find the genes th ...
written 5 months ago by
Rahil • 180
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... Many thanks @Kevin for being always helpful! Ah, it was a mistake I change it to alpha =1. Yes, I read that and used cv.glmnet. Then I built a new model with 47 genes/predictors that I got with `rownames(co.se$CMS1)[which(co.se$type > 0)]`
finalLasso <- glm(as.factor(modellingLasso$type) ...
written 5 months ago by
Rahil • 180
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... Hi @Kevin I'll be very thankful if you advice me on this result.
all my 475 genes that I included in this analysis have non-zero coefficient.
Call: glmnet(x = data.matrix(modellingLasso[, -1]), y = modellingLasso$type, family = "multinomial", alpha = 0, standardize = TRUE)
...
written 5 months ago by
Rahil • 180
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... Thanks @Kevin, after applying anova pval < 0.001 I got 497 genes. Then to do multinomial penalised regression I followed your comprehensive reply in this [post][1] and did every step as you said and now after applying this chunk of the script:
g1 <- rownames(co.se$S1)[which(co.se$S1 != 0) ...
written 5 months ago by
Rahil • 180
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