User: TriS
TriS • 2.9k
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Posts by TriS
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... two approaches you could try are in perl and unix
perl: [from previous question in biostar][1]
UNIX: [AWK solution][2]
[1]: https://www.biostars.org/p/4346/
[2]: https://stackoverflow.com/questions/28289363/awk-solution-for-pattern-matching-and-allowing-one-ambiguity-mismatch ...
written 8 hours ago by
TriS • 2.9k
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... a little bit of disclaimer first, just for safety: here we do NOT provide information that lead to choosing or altering a medical treatment, all info are for educational purpose and the investigator assumes the final responsibility of what to do with the info provided.
that said...what you did in t ...
written 5 weeks ago by
TriS • 2.9k
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... you can assign groups to patients that have high/low expression, i.e. high=1, low=2, middle=0, remove the 0s and run survival as above.
as warm suggestion, look a lil more into how to run survival analyses in R, don't just copy and paste the code above without knowing what's doing what. that will b ...
written 5 weeks ago by
TriS • 2.9k
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... the description is in the voom paper "[voom: precision weights unlock linear model analysis tools for RNA-seq read counts.
Charity W Law, Yunshun Chen, Wei Shi and Gordon K Smyth][1]"
for my understanding voom keeps in consideration the experimental design, i.e. treatments/replicates/etc, to weight ...
written 5 weeks ago by
TriS • 2.9k
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... that is pretty simple, use disease free survival data, generally as DFS in the clinical data. then there should be a column saying "tumor free/with tumor". ...
written 5 weeks ago by
TriS • 2.9k
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Comment:
C: Problem with Manhattan plot
... how do your data look? what's the code that you used? I suppose you are using R for the plot? what does the image look like (we can't see it, or at least I can't)? hard to help without info ...
written 9 weeks ago by
TriS • 2.9k
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... I had a similar situation, I used limma, not DESeq2 but the concept is the same.
the first thing I did was to use your approach #1, which worked fine. then I started working on the contrast matrix.
let's say your data look like
> data
A A B ...
written 9 weeks ago by
TriS • 2.9k
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... this is also a good read for your analysis
[RNA-seq analysis for detecting quantitative trait-associated genes][1]
[1]: https://www.nature.com/articles/srep24375 ...
written 9 weeks ago by
TriS • 2.9k
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... fusion gene event could cause that. are those cancer samples? ...
written 9 weeks ago by
TriS • 2.9k
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33
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33
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... hmmm, ok, try to run `s1` and `summary(s1)`
you should get something like the following
> s1
Call:
survdiff(formula = f ~ a)
N Observed Expected (O-E)^2/E (O-E)^2/V
a=1 77 44 45.5 0.0464 0.0794
a=2 106 69 67.5 0.0312 0.0794
...
written 11 weeks ago by
TriS • 2.9k
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