User: shawn.w.foley
shawn.w.foley • 1.2k
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Posts by shawn.w.foley
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... I simply run `plot(density(log10(fpkm)))` in R. In my experience a bimodal curve is generated with a trough right near 1 FPKM. I always use this as a sanity check, I do have several datasets where the trough appears new 2 or 3 FPKM and adjust my filtering criteria accordingly.
I've gone through th ...
written 4 months ago by
shawn.w.foley • 1.2k
2
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4
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316
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... Just to clarify, the methods specify >2-fold change, which would be a |log2FC| > 1, not >2 (unless I misunderstood your answer). ...
written 4 months ago by
shawn.w.foley • 1.2k
5
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... I'm not familiar with `edgeR` specifically, but I know that while `DESeq2` uses fits raw counts to a NB distribution when calculating differential expression, it includes a function to simply calculate and export RPKM/FPKM. ATPoint raises a good point about proceeding with caution, but my interpreta ...
written 4 months ago by
shawn.w.foley • 1.2k
1
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2
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290
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... My rule of thumb is FPKM >= 1, that being said I always generate a density plot of the FPKMs to view the distribution - in R I run `plot(density(log2(fpkm)))`. This (almost always) generates a bimodal distribution and I've found that 1 is very close to the trough of that distribution. However, th ...
written 5 months ago by
shawn.w.foley • 1.2k
1
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1
answer
589
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1
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... Rather than changing the sign of the p-value it's recommended to use the T-statistic. This number correlates to the p-value and is signed based on the fold change.
My recommendation would be to perform a Hypergeometric test (similar to a GO term enrichment but using the gene sets of interest). I'd ...
written 6 months ago by
shawn.w.foley • 1.2k
2
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1
answer
589
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1
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... The short answer to your question is that if you have an equal distribution of up- and down-regulated genes within a gene set your NES (Normalized Enrichment Score) should be close to zero.
The medium answer is that the NES is calculated from the ES (Enrichment Score), which is a rolling sum of the ...
written 6 months ago by
shawn.w.foley • 1.2k
1
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2
answers
207
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2
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... Of that 30% how many are categorized as "too short"? @Charles Warden makes a good point about FastQC, you want to be certain this isn't a sequencing/library prep artifact before investing too much time into determining the source of these reads. ...
written 6 months ago by
shawn.w.foley • 1.2k
0
votes
1
answer
195
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1
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... Could you post a few lines so we can see what the output looks like? ...
written 6 months ago by
shawn.w.foley • 1.2k
2
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2
answers
207
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2
answers
... If you have reads in a `.sam` file and you want to count their frequency you could make a quick `python` script:
inFile = open('unmapped.sam','r')
outFile = open('unmapped_read_count.txt','w')
countDict = {}
line = inFile.readline()
#Remove header starting with @ symbol
...
written 6 months ago by
shawn.w.foley • 1.2k
1
vote
2
answers
207
views
2
answers
... It sounds like you know where these "external" genes have come from. If you have a `fasta` file with the sequence of these "external" genes then use that for mapping and see how many of the unmapped reads map to this second fasta/genome file.
Depending on your mapping algorithm you might have an `u ...
written 6 months ago by
shawn.w.foley • 1.2k
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