I have around 90 Samples (taken from same tissues from different patients) in my .maf files, and i am planning to use deconstructsigs package . I am not stuck about how should be determining the signatures contributing to these 90 samples at a go? Its very difficult to provide sample.id every time. It would be really helpful if you can please help me in this case
Should i manually change this every time and generate a graph or can i run these 90 samples together and generate graph at once? Its very confusing to run manually every sample.Please help.
Thanks a lot for your reply, i have sample ids as tumor sample bar codes, like TCGA-IC-A6RF-01A-13D-A33E-09 (96 samples altogether), Can you please guide how best i can run this? i have limited knowledge about coding.
Thanks alot
NB: This can maybe be obtained elsewhere. If you have a dataframe that contain all the IDs in one column you could load this dataframe and extract the IDs:
data <- read.table("file", sep="\t", header=T)
ids <- unique(data$sampleID)
Hi VHahaut, using this method I have a dataframe of my samples. However when I try to do sapply(ids, function(x) makePie(x, sub = x) it gives me an error saying Error in[[.default(sigs.output, "weights") : subscript out of bounds. Any way I should be processing this data?
If your sample IDs are 1 to 90 why not simply do a loop instead of manually test them all?
Then combine the results as a single dataframe and process it to graph your results as you like (all together or one by one)
Thanks a lot for your reply, i have sample ids as tumor sample bar codes, like TCGA-IC-A6RF-01A-13D-A33E-09 (96 samples altogether), Can you please guide how best i can run this? i have limited knowledge about coding. Thanks alot