User: Matina
Matina • 150
- Reputation:
- 150
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- Location:
- United Kingdom/University of Edinburgh
- Last seen:
- 1 month ago
- Joined:
- 5 years ago
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Posts by Matina
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... Hi Atakan,
This is correct - I got an answer from one of the developers of TCGAbiolinks at the [Github account][1] saying that everything that starts with `subtype_` is actually metadata from papers that analyzed the samples suggested to use `days_to_death`. In any case what is strange is that the ...
written 3 months ago by
Matina • 150
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... Thank you very much Igor!
I will have a look at this! ...
written 3 months ago by
Matina • 150
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... Hi Efstathios,
I have a set of genes that I am interested in and I want to see if they are associated with clinical outcomes and molecular subtype patterns. You are right, I got an answer in the GitHub account.
Thanks a lot for your answer!
Matina
...
written 3 months ago by
Matina • 150
9
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... Hi all,
I have downloaded the TCGA-BRCA RNA-seq data and the associated clinical information using the code below.
CancerProject <- "TCGA-BRCA"
query <- GDCquery(project = CancerProject,
data.category = "Transcriptome Profiling",
dat ...
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Comment:
C: Similar samples in RNAseq
... Have you looked at Pearson correlation between the samples of interest? ...
written 4 months ago by
Matina • 150
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... Hi vinayjrao,
I think the problem is with the `data` matrix; `molecular.subtyping` fuction expects a matrix of samples(rows) x genes(cols). As I can see above your data matrix is genes x samples, right? Try transposing the matrix.
From the genefu vignette for do.mapping: `TRUE if the mapping thro ...
written 4 months ago by
Matina • 150
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... Great! Happy to help! I'll post it as an answer then. ...
written 4 months ago by
Matina • 150
1
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1
answer
436
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1
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... Hi vinayjrao,
I think the problem is with the `data` matrix; `molecular.subtyping` fuction expects a matrix of samples(rows) x genes(cols). As I can see above your data matrix is genes x samples, right? Try transposing the matrix. Let me know if it solved your problem!
From the genefu vignette fo ...
written 4 months ago by
Matina • 150
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... Ok, so have you tried using lets say EdgeR or DESeq2 with the raw read counts? If you would prefer to use the normalised data you could use a limma-voom solution. As for GSEA, after you determine differentially expressed genes between the groups of interest you can rank the genes based on some crite ...
written 4 months ago by
Matina • 150
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... So like a kind of feature selection type of analysis? If that is the case you could look for co-expression patterns in genes in specific samples/groups of samples. Another option is to use machine learning methods such as Recursive feature elimination (RFE). For my own analysis I have been using the ...
written 4 months ago by
Matina • 150
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For A: PAM50 subtype classification by genefu
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