The MA plot shows log fold change as a function of
mean log expression level. A set of 14 arrays representing a single
experiment from the Affymetrix spike-in data are used for this plot.
A total of 13 sets of fold changes are generated by comparing the
first array in the set to each of the others. Spiked-in genes are
symbolized by numbers representing the nominal $\log_2$ fold change
for the gene. Non-differentially expressed genes with observed fold
changes larger than 2 are plotted in red. All other probesets are
represented with black dots.
The MA plot shows log fold change as a function of
mean log expression level. A set of 28 arrays representing a single
experiment from the Affymetrix spike-in data are used for this plot.
Fold changes are generated for all possible comparisons of the
the first 14 arrays and the second 14 arrays.
Spiked-in genes are
symbolized by numbers representing the nominal $\log_2$ fold change
for the gene. Of the genes that are spiked to be differentially
expressed, only genes with small nominal fold changes are
shown. The colors represent
four different groups: nominal concentration of genes being compared
less than or equal to 2 picoMolar (blue), between 4 and 32 picoMolar
(green), greater than or equal to 64 picoMolar (blue).
Non-differentially expressed genes with observed fold
changes larger than 2 are plotted in red. All other probesets are
represented with black dots.
For each gene,
and each experimental condition in the dilution data set, we
calculate the mean log
expression and the observed standard deviation across 5
replicates. The
resulting scatterplot is smoothed to generate a single curve
representing mean standard deviation as a function of mean log
expression.
For each non-spiked-in gene in the 28 arrays used in
Figure 1b, we calculate the mean log
expression and the observed standard deviation across the 28
replicates. The
resulting scatterplot is smoothed to generate a single curve
representing mean standard deviation as a function of mean log
expression.
This plot, using the GeneLogic dilution data,
shows the sensitivity of fold change calculations to total RNA
abundance. Average log fold-changes between liver and CNS for the
lowest concentration and the highest in the dilution data set are
computed. Orange and red color is used to denote genes with
$M_{6g}-M_{1g}$ bigger than $\log_2(2)$ and $\log_2(3)$
respectively. The rest are denoted with black.
Average observed $log_2$ intensity plotted
against nominal $log_2$ concentration for each spiked-in gene for
all arrays in Affymetrix spike-In experiment. The dashed line has the ideal slope of 1.
For the GeneLogic
dilution data, log expression values are regressed against their
log nominal concentration. The slope estimates are plotted against
average log intensity across all concentrations.
Using the 28 arrays of Figure 1b, we compute local
slopes. As the slopes shown in Figure 4a, the local slopes
represent the expected observed log fold-change for probesets
with true fold-change of 2 but they are presented as a
function of the total nominal probeset concentration in the two
samples being compared. In theory the local slopes should be one so
we show the bias (difference between the observed local slope and one).
A typical identification rule for differential
expression filters
genes with fold change exceeding a given threshold.
This figure shows average ROC curves which offer a graphical
representation of both specificity and sensitivity for such a
detection rule. Average ROC curves based on comparisons with
nominal fold changes ranging from 2 to 4096.
As 5a, but with nominal fold changes equal to 2.
As 5a, but for comparisons with both nominal concentrations at most 4
picoMolar and nominal fold changes at most 2.
As 5a, but for comparisons with both nominal concentrations between 4 and
64 picoMolar and nominal fold changes at most 2.
As 5a, but for comparisons with both nominal concentrations at least 64 and
with nominal fold changes at most 2.
Observed log fold changes plotted against
nominal log fold changes. The dashed lines represent highest, 25th
highest, 100th highest, 25th percentile, 75th percentile,
smallest 100th, smallest 25th, and smallest log fold change for
the genes that were not differentially expressed.
Like 6a, but
the observed fold changes were calculated for spiked in genes with
nominal concentrations no higher than 2pM.
Figure definitions
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