User: newbie
newbie • 30
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Posts by newbie
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... Thanks for the answer. Have a similar doubt. What answer I can give if the DEA heatmap looks like above, where 9 samples of subtype A are away from the main cluster? ...
written 2 days ago by
newbie • 30
4
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... Hello,
I'm working with rnaseq data of breast cancer samples. There are a total of 40 samples. Among 40 samples, 26 samples are of subtype A and 14 are subtype B.
I did differential analysis with samples between Subtype A and Subtype B with edgeR. Differentially expressed genes are based on FDR &l ...
written 2 days ago by
newbie • 30
• updated
3 hours ago by
eric.audemard • 0
0
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... @ATpoint Could you please tell me what is wrong in my above code ...
written 23 days ago by
newbie • 30
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... Instead of showing in table, I'm showing the counts data for all samples with some genes.
data <- structure(list(Cell1_foxcut12 = c(4L, 8L, 3L, 4L, 7318L, 25317L,
41L, 0L, 0L, 0L), Cell2_foxcut11 = c(9L, 11L, 2L, 6L, 4959L,
2621L, 38L, 0L, 0L, 0L), Cell1_foxcut11 = c(0L, 3L, 2L, 0 ...
written 23 days ago by
newbie • 30
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... May I know how this can be done please. I haven't seen anywhere about this type of analysis, so I'm not at all aware about how to do this. ...
written 23 days ago by
newbie • 30
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... @ATpoint Hi, could you please tell me how to create design matrix for the differential analysis within the same cell-line
Do you think the below code is right?
library(edgeR)
group <- factor(paste0(coldata$TYPE))
y <- DGEList(data,group = group)
y$samples
## Filteri ...
written 23 days ago by
newbie • 30
0
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166
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... Yes, differential analysis needs to be done within the same cell-line. I edited my question. Could you please tell me how to give the syntax for group, design matrix and contrasts using edgeR? thanq ...
written 24 days ago by
newbie • 30
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... Sorry, my mistake. It should be something like this
Cell1_foxcut samples vs Cell1_HA samples
Cell2_foxcut samples vs Cell2_HA samples ...
written 24 days ago by
newbie • 30
0
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... Please check this:
### Differential Analysis
library(edgeR)
group <- factor(paste0(coldata$Type))
y <- DGEList(data,group = group)
y$samples
## Filtering (Based on smallest number of samples among two groups do the filtering)
keep <- rowSums(cpm(y) > 0. ...
written 24 days ago by
newbie • 30
0
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... I have a total of 8 samples, 4 controls and 4 Foxcut gene over expressed samples.
The column data for all the 8 samples look like below with replicate and cell-line information:
Samples TYPE Replicate Cell-lines
Cell1_HA1 Control 1 1
...
written 24 days ago by
newbie • 30
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