**0**wrote:

Hi I have downloaded a mass spec dataset from maxqb (http://maxqb.biochem.mpg.de/mxdb/).

I have then imported the data Into R specifying 0 values as NA (as I think this is correct for analysis using the Limma package):

```
exprs <- read_excel("exprs.xlsx", na="0")
```

I then normalise using normalizeBetweenArrays and remove any columns with all NA values:

```
y <- normalizeBetweenArrays(log2(exprs), method="cyclicloess", iterations=10)
y <- exprs[rowSumsis.na(exprs)) != ncol(exprs), ]
```

Then I carry out DE analysis:

```
group <- factor(pData$MV_only)
design <- model.matrix(~0+group)
contrast.matrix <- makeContrasts(
mv_vs_other = MV-other,levels=design)
fit <- lmFit(y, design)
fit2 <- contrasts.fit(fit, contrast.matrix)
fit2 <- eBayes(fit2, trend=T)
```

and I get the following warning: Warning message:

```
Partial NA coefficients for 2885 probe(s)
```

But the analysis seems to work fine.

I have a couple of questions here.

1) Is this the correct way to deal with 0 values? It should be dealt with in normalizeBetweenArrays?

2) To then visualise any of the data in PCA or coolmap (heat map) I convert the NA's back to 0 in the normalised data:

```
y[is.na(y)] <- 0
```

Is this also correct?

Thank you

Reuben

**39k**• written 8 months ago by reubenmcgregor88 •

**0**