<p><em>Answer from @fabio-marroni, converted from comment:</em></p>
<p>You might try to use <a href="https://bioconductor.org/packages/release/bioc/vignettes/MutationalPatterns/inst/doc/Introduction_to_MutationalPatterns.pdf" rel="nofollow noreferrer">mutationalPatterns</a> and see if the  responders cluster together and separated from nonresponders.</p>

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2021-07-14T11:32:17.673Z
2021-07-14T11:32:17.673Z
gringer
<p>I have mutational catalogues of 4 samples like below</p>
<pre><code>&gt; head(out)
        Responders1 Nonresponders1 Responders2 Nonresponders2
A[C&gt;A]A       11744          13546        2897           3655
A[C&gt;A]C        5144           7172        2295           2163
A[C&gt;A]G         939           1257         290            279
A[C&gt;A]T        6065           7997        2078           2088
C[C&gt;A]A        8969          11155        2055           2582
C[C&gt;A]C        4050           6657        1367           1173
&gt;

 &gt; dim(mut)
[1] 96  4
&gt; 
</code></pre>
<p><em>Note: A[C&gt;A]A - Single nucleotide base substitution</em></p>
<p>I want to look if mutational substitutions are different between samples</p>
<p>I have tried</p>
<pre><code>wilcox.test(mut<span class="math-container">$Responders2,mut$</span>Nonresponders2)

t.test(mut<span class="math-container">$Responders2,mut$</span>Nonresponders2)

var.test(mut<span class="math-container">$Responders2,mut$</span>Nonresponders2)
fisher.test(mut<span class="math-container">$Responders2,mut$</span>Nonresponders2,simulate.p.value=TRUE)

kruskal.test(mut<span class="math-container">$Responders2,mut$</span>Nonresponders2)
</code></pre>
<p>To find a difference but I think you may know a better test to find any difference here</p>
<p>This is base shift (mutation, substitution across genome of each patient). I guess mutations happen randomly but I don't know if mutational caller algorithm also pick them by randomness. I expect the shift of A (Adenine) to C (Cytosine) in a group of these patients be higher than the other group. This higher rate likely should be due to some background than randomness picked by algorithm. So I think null hypothesis is that rate of base shifting is not the same in both group. I also don't expect a normalised distribution of base shifting rather a poison distribution.</p>
<p>Can you help please?</p>
<p>Thanks</p>

<r><wgs><mutations>
Finding difference between groups
# Finding difference between groups

(Asked by: username_0 on 2020-03-21)

I have mutational catalogues of 4 samples like below
> head(out)
        Responders1 Nonresponders1 Responders2 Nonresponders2
A[C>A]A       11744          13546        2897           3655
A[C>A]C        5144           7172        2295           2163
A[C>A]G         939           1257         290            279
A[C>A]T        6065           7997        2078           2088
C[C>A]A        8969          11155        2055           2582
C[C>A]C        4050           6657        1367           1173
>

 > dim(mut)
[1] 96  4
> 

Note: A[C>A]A - Single nucleotide base substitution
I want to look if mutational substitutions are different between samples
I have tried
wilcox.test(mut$Responders2,mut$Nonresponders2)

t.test(mut$Responders2,mut$Nonresponders2)

var.test(mut$Responders2,mut$Nonresponders2)
fisher.test(mut$Responders2,mut$Nonresponders2,simulate.p.value=TRUE)

kruskal.test(mut$Responders2,mut$Nonresponders2)

To find a difference but I think you may know a better test to find any difference here
This is base shift (mutation, substitution across genome of each patient). I guess mutations happen randomly but I don't know if mutational caller algorithm also pick them by randomness. I expect the shift of A (Adenine) to C (Cytosine) in a group of these patients be higher than the other group. This higher rate likely should be due to some background than randomness picked by algorithm. So I think null hypothesis is that rate of base shifting is not the same in both group. I also don't expect a normalised distribution of base shifting rather a poison distribution.
Can you help please?
Thanks

**Tags:** r, wgs, mutations

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## 1 answers

### Answer by username_1 on 2021-07-14. Score: 1

*Answer from @fabio-marroni, converted from comment:*

You might try to use [mutationalPatterns](https://bioconductor.org/packages/release/bioc/vignettes/MutationalPatterns/inst/doc/Introduction_to_MutationalPatterns.pdf) and see if the responders cluster together and separated from nonresponders.


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