Moderator: seidel
seidel ♦ 6.8k
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I work as a scientist at a non-profit research institute.
Posts by seidel
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... Sorry about that. I updated the references. ...
written 15 days ago by
seidel ♦ 6.8k
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... Your graphic is cut off - so we can only see what's happening in the top portion of your heat map - but assuming the pattern is preserved in the unseen portion, the simple answer is that the averages of the columns making up C3 are more similar to those of C2 and C4 than to C1, so the dendrogram was ...
written 15 days ago by
seidel ♦ 6.8k
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... The simplest answer would be to use the Poisson distribution. Assuming your data is normalized for read depth, you have a background estimate for your window of interest (lambda = 50), and an observed count for that window in your IP (1000), so in R you could estimate this with:
ppois(100, lamb ...
written 18 days ago by
seidel ♦ 6.8k
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... Can't you just grep for the gene name of interest and redirect the output to a file? All the lines relevant to that gene should have the ID, and this would select and place all lines with the given gene id into a single file. ...
written 3 months ago by
seidel ♦ 6.8k
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... Yes...assuming the same set of transcripts is quantified between experiments, and the the non-zero count transcripts are identical between sets (i.e. the set of "expressed" transcripts is the same between conditions). In the case above, we both both different conditions AND different transcriptomes. ...
written 3 months ago by
seidel ♦ 6.8k
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... You want to convert "15:" to ">"? Or in general, do you want to convert anything to the left of the colon, including the colon, to ">"? For any number of lines in a file? There are ways to do both. One could easily use sed, or awk, or perl, with a one-liner (so no real script required), but as ...
written 9 months ago by
seidel ♦ 6.8k
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Answer:
A: Reproducing this plot in R
... Something like the following would work with base R functions:
# make some data
a <- data.frame(sample=paste0("A", 1:50), log10_total_counts=rnorm(50, 6))
# get x points
x <- 1:length(a$log10_total_counts)
# create plot, drop x axis
plot(x, a$log10_total_cou ...
written 9 months ago by
seidel ♦ 6.8k
2
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1.3k
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Answer:
A: Creating Count Matrix
... One suggestion using R would be:
# only return file names with a given pattern
dir(pattern="ReadsPerGene.out.tab")
# save the results to a variable
files <- dir(pattern="ReadsPerGene.out.tab")
counts <- c()
for( i in seq_along(files) ){
x <- read.tab ...
written 9 months ago by
seidel ♦ 6.8k
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Comment:
C: Creating Count Matrix
... What language/method would you like to use? This can be done using shell, R, python, perl, etc.....you name it. What are you familiar with? ...
written 9 months ago by
seidel ♦ 6.8k
0
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... One straightforward approach would be to use STAR to generate a count table that you can use with edgeR. Look up the edgeR userguide - it has a rich description of how to quantify differential gene expression given various experimental designs. ...
written 10 months ago by
seidel ♦ 6.8k
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