Hi,
I'm trying to plot the scatterplot of direct vs. moderated log-ratios and I keep getting an error:
Error in plot.window(...) : need finite 'ylim' values
In addition: Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
This is what I have put in:
> cdsBlind <- estimateDispersions( cds, method="blind" )
> vsd <- getVarianceStabilizedData( cdsBlind )
> mod_lfc <- (rowMeans( vsd[, conditions(cds)=="treated", drop=FALSE] ) -
+ rowMeans( vsd[, conditions(cds)=="untreated", drop=FALSE] ))
> lfc <- res$log2FoldChange
> finite <- is.finite(lfc)
> table(as.character(lfc[!finite]), useNA="always")
-Inf Inf NaN <NA>
83 212 285 0
> largeNumber <- 10
> lfc <- ifelse(finite, lfc, sign(lfc) * largeNumber)
> plot( lfc, mod_lfc, pch=20, cex=.3,
+ col = ifelse( finite, "#80808040", "red" ) )
Is it because I am running analysis on samples with no replicates? (I know - not good, but it's all that I have...). Any ideas? Thanks.
I'm trying to plot the scatterplot of direct vs. moderated log-ratios and I keep getting an error:
Error in plot.window(...) : need finite 'ylim' values
In addition: Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
This is what I have put in:
> cdsBlind <- estimateDispersions( cds, method="blind" )
> vsd <- getVarianceStabilizedData( cdsBlind )
> mod_lfc <- (rowMeans( vsd[, conditions(cds)=="treated", drop=FALSE] ) -
+ rowMeans( vsd[, conditions(cds)=="untreated", drop=FALSE] ))
> lfc <- res$log2FoldChange
> finite <- is.finite(lfc)
> table(as.character(lfc[!finite]), useNA="always")
-Inf Inf NaN <NA>
83 212 285 0
> largeNumber <- 10
> lfc <- ifelse(finite, lfc, sign(lfc) * largeNumber)
> plot( lfc, mod_lfc, pch=20, cex=.3,
+ col = ifelse( finite, "#80808040", "red" ) )
Is it because I am running analysis on samples with no replicates? (I know - not good, but it's all that I have...). Any ideas? Thanks.
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