## User: Andrew_McDavid

Andrew_McDavid •

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- 1 year, 2 months ago
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#### Posts by Andrew_McDavid

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... This all depends on how you define "batch." As I understand your design, statistics won't be able to tell you if any differences you see should be ascribed to "treatment" or "plate". Unless you run some replicates to estimate, or bound, the plate-to-plate variability, these two factors are confoun ...

written 18 days ago by
Andrew_McDavid •

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... The L2-norm makes some sense to me, since the residuals may be approximately N(0,1) distributed under a null distribution of exchangeable cells, given the covariates included in the model. The clustering in this case could seen as searching for latent Gaussian structure among the residuals? The opt ...

written 6 weeks ago by
Andrew_McDavid •

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... Can you be more specific when you say "interface for contrasts" The contrasts(colData(x)$strain) = "contr.sum" business is base R and determines the coding for your factors, hence interpretation of your coefficients. Venables & Ripley is the canonical reference for that.
Specifying linear co ...

written 9 weeks ago by
Andrew_McDavid •

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You can fit such a model a "cellmean model" (zlm_cellmean = zlm(~ 0 + group, x)) though it is possibly a little less statistically efficient [1] than using contrasts that explicitly includes an intercept:
## assuming you manually crossed strain and condition to get group
zlm_dummy = zlm(~stra ...

written 9 weeks ago by
Andrew_McDavid •

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... TL;DR
One of the classes you are comparing has no detectable expression for a gene. The log-fold change is trying to get an estimate of effect size, but that is not well-defined when we never observe expression in a class. P-values from lrTest or waldTest are still well-defined.
Fine print
From t ...

written 3 months ago by
Andrew_McDavid •

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... I noticed that MAST sometimes has NA for the continuous coefficient. When this happens, it also has NA for the estimated fold change. I couldn't find much in the documentation about this, but I was wondering if someone can explain it?
This is a problem for me because I'm trying to select the most d ...

written 3 months ago by
Andrew_McDavid •

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... You might also try
Bacher R, Chu L, Leng N, Gasch AP, Thomson JA, Stewart RM, Newton MA and Kendziorski C (2017). “SCnorm: robust normalization of single-cell RNA-seq data.” Nature Methods. https://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.4263.html.
Software is available in Bioconduct ...

written 3 months ago by
Andrew_McDavid •

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... The model coefficients that are being tested for enrichment are the coefficients from the zlmfit objects. With A as a ref, then positive coefficients in the ZlmFit object means that the mean of B > mean of A. The GSEA is calculating the average ZlmFit coefficient inside the set. So a positive Z-s ...

written 3 months ago by
Andrew_McDavid •

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... Our goal is to support any model that you can run with `lm`. Using the numeric values for your ordered factor corresponds to a very particular model: it will estimate the linear effect of dose. That is a restriction from the factor model, which allows the mean function to follow *any* effect of do ...

written 3 months ago by
Andrew_McDavid •

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... First off, in base R, I have only dabbled with the ordered factor contrasts so don't know them well enough to give reliable advice about how to interpret them. That being said, there are two ways to apply them with MAST.
First, you can set the contrasts attribute to the column of interest:
librar ...

written 3 months ago by
Andrew_McDavid •

**80**#### Latest awards to Andrew_McDavid

Scholar
7 months ago,
created an answer that has been accepted.
For A: MAST reported warning "Coefficients ... are never estimible and will be dropped.

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