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How does one deal with spatial effects detected on single channel microarrays?
Microarray Normalization hu6800 affy gcrma marray nnNorm Harshlight Microarray hu6800
12.3 years ago Scott Robinson ▴ 130
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How does one deal with spatial effects detected on single channel microarrays?
Microarray Normalization affy marray nnNorm Microarray Normalization affy marray nnNorm
updated 12.4 years ago by ★ 3.9k • written 12.4 years ago by ★ 13k
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nnNorm loading problem
nnNorm nnNorm
updated 19.4 years ago by ★ 7.4k • written 19.4 years ago by ▴ 360
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900
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need a neural network package for microarray data
Normalization nnNorm Normalization nnNorm
20.1 years ago Tarca, Adi ▴ 570
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Bug in maNormNN
Microarray Normalization GO Visualization Network nnNorm Microarray Normalization GO
20.2 years ago Tarca, Adi ▴ 570
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Answer: limpa analysis advice by Gordon Smyth 53k
It is actually very hard to estimate the DPC from observed data, because the curve is function of unobserved intensities rather than a func…
Answer: When to use edgeR or limma by Gordon Smyth 53k
The short answer is that we generally prefer edgeR for applications with lots of small counts and limma for complex designs with random eff…
Comment: limpa-blank normalization and Spectronaut's PTM stoichiometry by Gordon Smyth 53k
I updated the above answer today.
Answer: When to use edgeR or limma by James W. MacDonald 68k
I would use edgeR's quasi-likelihood model for any analysis with a smaller number of observations (like 3 vs 3 or similar), but if you have…
Answer: limpa-blank normalization and Spectronaut's PTM stoichiometry by Gordon Smyth 53k
The short answer is that limpa reads standard feature-level intensities from Spectronaut or other quantifications tools. limpa is designed …
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Answer: When to use edgeR or limma
Answer: When to use edgeR or limma
Answer: When to use edgeR or limma
Answer: When to use edgeR or limma
A: deseq2 - paired samples in 2 sequencing types with very different library sizes
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