In fact, it wants to express the idea that you can evaluate different approaches

by analysing its false positive rate

How to do it?

In our normal experiments, we design a sample with a control

They are the same

so they should show no variation in theory

But when your approaches find they are different, then it means your approaches is not reliable

How to see this picture? Firstly, from top to bottom in order is 25%、50%、75% to 100%

According to the number of reads you have got and the kurtosis

from top to the bottom

you will find that when the kurtosis is low, their SNR (signal to noise ratio) is high

When it comes to bottom, in theory

it means two samples are same

its X axis P values and Y axis Density

their curve should be flat, little change

But we can see when the P value is less than 0.05

cuffdiff appears an increase in its curve

This is the main idea in this picture

Which means its false positive rate is high at that time

cuffdiff is not reliable

The next slide mainly show the sequence depth and number of sample

have effects on gene expression variation analysis

This picture is complex

each line stands for different analysis approach

The rightmost of the picture tells the name of approach

and the left Y axis means the false positive rate

And the X axis tells us the reads’ dilution ratio

100% means there is no dilution

50% means there are half of the reads to test

25% is 25% reads tested

We could use these methods to get the false positive rate

But what is the meaning of this approach?

It tells us this percent number can stand for the sequence depth

The deeper the sequence depth, the lower the false positive rate

These four boxes are on behalf of the kurtosis of 25%, 50%, 75% and 100%