<ol>
<li>We cannot be sure about this. For all we know, they could have been sequenced to the same depth and there is a biological difference that drives the 1000x (ridiculously large) fold change.</li>
<li>See above</li>
</ol>

<p>The only thing you can say for sure is that gene B is expressed twice as much as gene A in samples 1 and 2. That's what "relative" means - relative expression of genes within a sample.</p>

CC BY-SA 4.0
2020-06-13T14:41:27.217Z
thanks this was helpful. just want to see what others have to say as well before I accept the answer
An Ignorant Wanderer
CC BY-SA 4.0
2020-06-14T06:08:51.013Z
Oh of course. I’m no expert at this, but this is what I’ve encountered in our experiments.
Ram RS
CC BY-SA 4.0
2020-06-12T23:54:26.690Z
2020-06-12T23:54:26.690Z
Ram RS
<p>The process of RNA-seq is a sampling process of all the RNA molecules. We cannot make reliable comparisons before we know how deep we sample. And since we know it is a sample from a population, the absolute value does not make sense.</p>

CC BY-SA 4.0
2020-06-13T14:38:44.350Z
So can we know how deep we sample? And knowing that, what would that allow us to do exactly? And how does this tie to sequencing "depth"?
An Ignorant Wanderer
CC BY-SA 4.0
2020-06-14T02:01:52.857Z
This is usually the sequencing depth when I think about this problem.
Phoenix Mu
CC BY-SA 4.0
2020-06-13T02:09:39.163Z
2020-06-13T02:09:39.163Z
Phoenix Mu
<p>Let's say we have two samples, sample 1 and sample 2, and we're running an RNA seq experiment. Consider genes A and B for both. For simplicity, let's say that when we run the RNA seq experiment, we get the following results:</p>

<p>gene A sample 1 count: 2</p>

<p>gene B sample 1 count: 4</p>

<p>gene A sample 2 count: 2000</p>

<p>gene B sample 2 count: 4000</p>

<p>Based on my understanding, RNA seq gives relative results. So I guess in this guess, how can you tell whether either one of the following are true:</p>

<p>1- You sequenced sample 2 a thousand fold more compared to sample 1</p>

<p>2- Sample 2 really has a thousand fold more expression in both genes A and B </p>

<rna-seq>
Understanding the "relativeness" in RNA seq experiments
# Understanding the "relativeness" in RNA seq experiments

(Asked by: username_0 on 2020-06-12)

Let's say we have two samples, sample 1 and sample 2, and we're running an RNA seq experiment. Consider genes A and B for both. For simplicity, let's say that when we run the RNA seq experiment, we get the following results:

gene A sample 1 count: 2

gene B sample 1 count: 4

gene A sample 2 count: 2000

gene B sample 2 count: 4000

Based on my understanding, RNA seq gives relative results. So I guess in this guess, how can you tell whether either one of the following are true:

1- You sequenced sample 2 a thousand fold more compared to sample 1

2- Sample 2 really has a thousand fold more expression in both genes A and B

**Tags:** rna-seq

---

## 2 answers

### Answer by username_1 on 2020-06-12. Score: 2 | Accepted answer

1. We cannot be sure about this. For all we know, they could have been sequenced to the same depth and there is a biological difference that drives the 1000x (ridiculously large) fold change.
2. See above

The only thing you can say for sure is that gene B is expressed twice as much as gene A in samples 1 and 2. That's what "relative" means - relative expression of genes within a sample.

> **Comments:**
> **username_0**: thanks this was helpful. just want to see what others have to say as well before I accept the answer  
> **username_1**: Oh of course. I’m no expert at this, but this is what I’ve encountered in our experiments.  

---

### Answer by username_2 on 2020-06-13. Score: 0

The process of RNA-seq is a sampling process of all the RNA molecules. We cannot make reliable comparisons before we know how deep we sample. And since we know it is a sample from a population, the absolute value does not make sense.

> **Comments:**
> **username_0**: So can we know how deep we sample? And knowing that, what would that allow us to do exactly? And how does this tie to sequencing "depth"?  
> **username_2**: This is usually the sequencing depth when I think about this problem.  

---

