<p>Like the comments I'm not sure what the scores represent, it could be several different possibilities. Generally, we avoid recommendation if it's difficult to understand the underlying experiment.</p>
<p>However, regardless as a generic rule of thumb, I would transform via binary log (log2) and access the fold differences by simple subtraction. This exploits an interesting property of logarithms log(x/y) = log(x) - log(y). Binary log is a common standard across the field. Thus log2-fold difference is calculation because you just subject one log2 value against the other.</p>

CC BY-SA 4.0
2024-06-21T07:46:15.037Z
Thanks. Score is the so-called ConClave score (accumulated alignment score), from all reads that were accepted to match this template.
dim
CC BY-SA 4.0
2024-06-21T13:23:28.330Z
@dim upvotes and/or accepts are much preferred than notes of thanks. I would stick with the above transformation, because it's an accepted standard
M__
CC BY-SA 4.0
2024-06-21T04:16:11.537Z
2024-06-21T04:16:11.537Z
M__
<p>I am currently engaged in a research project that involves DNA sequence analysis, utilizing nanopore and KMA alignment software (k-mer alignment). As I delve deeper into my research, I am faced with a question regarding the normalization of my data and I am hoping to gain some insights from your collective expertise.</p>
<p>In my dataset, I have two tables: a &quot;before treatment&quot; table that contains 17 genes with corresponding scores (by score what I mean is the so-called ConClave score (accumulated alignment score), from all reads that were accepted to match this template.), and an &quot;after treatment&quot; table that includes 8 genes, also with their respective scores. All other genes aren't present anymore likely due to the treatment. My query pertains to the normalization process.</p>
<p>Should I normalize based on the total score for all genes in the &quot;before&quot; table, or should I only consider the genes that are present in both the &quot;before&quot; and &quot;after&quot; tables?</p>
<p>Originally these were reads extracted from genome DNA of bacteria from samples of interest and applied directly to nanopore device (with barcodes and adapters, as requested).</p>
<p>These reads were aligned vs resfinder database.</p>
<p>After thre treatment some genes are not present anymore and I wonder how can I figure out if the genes that are still present in both samples (before and after the treatment) are less expressed, at the same level or more expressed.</p>
<p>Here's the example:</p>
<p><a href="https://i.sstatic.net/txPNjByf.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/txPNjByf.png" alt="enter image description here" /></a></p>
<p>Basically I wonder how can I say if there is an effect of treatment for, say, gene1 and gene6.</p>
<p>I am seeking the most effective method for normalization in this particular scenario. Your suggestions and recommendations would be greatly appreciated.</p>

CC BY-SA 4.0
2024-06-19T16:40:42.427Z
This question is worded in a really vague manner. For starters, please define normalization and scores - be as specific as possible.
Ram RS
CC BY-SA 4.0
2024-06-19T22:28:23.803Z
By "KMA alignment", do you mean [k-mer alignment](https://gensoft.pasteur.fr/docs/kma/1.4.14/KMAspecification.pdf)? Please expand out any acronyms or initialisms the first time you use them, especially if they're not well-known.
gringer
CC BY-SA 4.0
2024-06-19T22:29:25.230Z
Please provide some examples of the tables that you describe. It helps us understand the question you are asking.
gringer
CC BY-SA 4.0
2024-06-23T13:40:18.337Z
Before and after _what_? What sequences are these? DNA? RNA? Are you looking at transcripts here? Are you using some sort of quantitative method looking at relative abundance of transcripts? What are you aligning against? Is there a reference genome? Are you aligning to known transcripts? Or can your treatment alter DNA and genes are actually lost as you say? We need to understand the experiment to be able to help.
terdon
<r><nanopore><normalization><k-mer>
Normalization in Sequence Analysis Research
# Normalization in Sequence Analysis Research

(Asked by: username_0 on 2024-06-19)

I am currently engaged in a research project that involves DNA sequence analysis, utilizing nanopore and KMA alignment software (k-mer alignment). As I delve deeper into my research, I am faced with a question regarding the normalization of my data and I am hoping to gain some insights from your collective expertise.

In my dataset, I have two tables: a "before treatment" table that contains 17 genes with corresponding scores (by score what I mean is the so-called ConClave score (accumulated alignment score), from all reads that were accepted to match this template.), and an "after treatment" table that includes 8 genes, also with their respective scores. All other genes aren't present anymore likely due to the treatment. My query pertains to the normalization process.

Should I normalize based on the total score for all genes in the "before" table, or should I only consider the genes that are present in both the "before" and "after" tables?

Originally these were reads extracted from genome DNA of bacteria from samples of interest and applied directly to nanopore device (with barcodes and adapters, as requested).

These reads were aligned vs resfinder database.

After thre treatment some genes are not present anymore and I wonder how can I figure out if the genes that are still present in both samples (before and after the treatment) are less expressed, at the same level or more expressed.

Here's the example:

[![enter image description here](https://i.sstatic.net/txPNjByf.png)](https://i.sstatic.net/txPNjByf.png)

Basically I wonder how can I say if there is an effect of treatment for, say, gene1 and gene6.

I am seeking the most effective method for normalization in this particular scenario. Your suggestions and recommendations would be greatly appreciated.

**Tags:** r, nanopore, normalization, k-mer
> **Comments:**
> **username_1**: This question is worded in a really vague manner. For starters, please define normalization and scores - be as specific as possible.  
> **username_2**: By "KMA alignment", do you mean [k-mer alignment](https://gensoft.pasteur.fr/docs/kma/1.4.14/KMAspecification.pdf)? Please expand out any acronyms or initialisms the first time you use them, especially if they're not well-known.  
> **username_2**: Please provide some examples of the tables that you describe. It helps us understand the question you are asking.  
> **username_3**: Before and after _what_? What sequences are these? DNA? RNA? Are you looking at transcripts here? Are you using some sort of quantitative method looking at relative abundance of transcripts? What are you aligning against? Is there a reference genome? Are you aligning to known transcripts? Or can your treatment alter DNA and genes are actually lost as you say? We need to understand the experiment to be able to help.  

---

## 1 answers

### Answer by username_4 on 2024-06-21. Score: 0 | Accepted answer

Like the comments I'm not sure what the scores represent, it could be several different possibilities. Generally, we avoid recommendation if it's difficult to understand the underlying experiment.

However, regardless as a generic rule of thumb, I would transform via binary log (log2) and access the fold differences by simple subtraction. This exploits an interesting property of logarithms log(x/y) = log(x) - log(y). Binary log is a common standard across the field. Thus log2-fold difference is calculation because you just subject one log2 value against the other.

> **Comments:**
> **username_0**: Thanks. Score is the so-called ConClave score (accumulated alignment score), from all reads that were accepted to match this template.  
> **username_4**: @dim upvotes and/or accepts are much preferred than notes of thanks. I would stick with the above transformation, because it's an accepted standard  

---

