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quality
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First principal component variance stabilised RNA-seq data correlates with total read counts per sample / library concentration
RNA-seq
PCA
control
DESeq2
Quality
2.2 years ago • updated 2.0 years ago
9906201a
▴ 20
0
votes
0
replies
611
views
AffyExpress choose relative path folder
folder
quality
QualityControl
AffyExpress
3.4 years ago
bastien_chassagnol
• 0
0
votes
1
reply
858
views
Array quality metrics for large sample size
microarray
quality
updated 5.3 years ago by
Wolfgang Huber
★ 13k • written 5.3 years ago by
RV
▴ 10
0
votes
3
replies
2.2k
views
what does "mean base quality" mean?
base quality
quality
mean base quality
updated 7.6 years ago by
Mike Smith
★ 6.5k • written 7.6 years ago by
christiangriffioen
• 0
4 results • Page
1 of 1
Recent ...
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Comment: deseq2 results
by
sajadahmad41454
• 0
thank you for your response, should i remove or discard that sample? since the red outlier on left represents one of healthy samples.
Comment: deseq2 results
by
swbarnes2
★ 1.4k
It looks like the PCA plot of a real RNASeq experiment. The red outlier on the left might be the mathematical reason why you have few vali…
Comment: Multi-factorial, longitudinal disease progression analysis with unbalanced patie
by
Dylan.Sheerin
• 0
Thank you very much, Gordon. I'll give voomLmFit a go!
Answer: Multi-factorial, longitudinal disease progression analysis with unbalanced patie
by
Gordon Smyth
50k
Including subjectID in the design matrix always accounts for unbalanced sampling and patient variation but subjects with incomplete records…
Comment: Log-cpm values from limma
by
Gordon Smyth
50k
No, it does not mean that. `voom()` uses the design matrix with the W covariates, to compute precision weights but not to adjust the log-cp…
Votes
Comment: deseq2 results
Comment: deseq2 results
Answer: Multi-factorial, longitudinal disease progression analysis with unbalanced patie
Answer: Extremely small p-values using Limma for proteomic data
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