<p>I have data that looks like this: 3 column SNPs their gene based on Annovar and a p-value for every SNP. What I would like is to aggregate the p values for every gene.</p>
<pre><code>snps &lt;- data.frame(
  snp_id = c(&quot;rs1&quot;, &quot;rs2&quot;, &quot;rs3&quot;, &quot;rs4&quot;, &quot;rs5&quot;, &quot;rs6&quot;, &quot;rs7&quot;, &quot;rs8&quot;),
  Gene.refGene_ANNOVAR = c(&quot;gene1&quot;, &quot;gene1&quot;, &quot;gene1&quot;, &quot;gene1&quot;, &quot;gene2&quot;, &quot;gene2&quot;, &quot;gene2&quot;, &quot;gene2&quot;),
  p.value = c(0.7703884, 0.9648540, 0.9648540, 0.9648540, 0.54, 0.03, 0.03, 0.8)
)
</code></pre>
<p>above an example of the data .
I read about the SKAT method -&gt; <a href="https://www.hsph.harvard.edu/skat/" rel="nofollow noreferrer">https://www.hsph.harvard.edu/skat/</a><br />
and figured it might do the work .
I read about the package here:<a href="https://rdrr.io/cran/SKAT/man/SKAT.html" rel="nofollow noreferrer">https://rdrr.io/cran/SKAT/man/SKAT.html</a>
tried to implement it on my data , but got lost as how to perform it correctly:</p>
<pre><code>gene_pvals &lt;- aggregate(p.value ~ Gene.refGene_ANNOVAR, data = df, FUN = function(x) SKAT::SKAT_Null(x)$p.value)
</code></pre>
<p>I would be happy if you could share your knowledge in this situation.I don't have information about the correlations between the SNPs but I know that they are correlated, do I have enough data to complete the SKAT method?
also for every SNP i have data on how many patients had the hetro/homozygous encoding(0,1,2).</p>

CC BY-SA 4.0
2023-03-24T15:48:41.500Z
cross posted: https://www.biostars.org/p/9558525
Pierre
CC BY-SA 4.0
2023-04-01T10:32:40.907Z
Unfortunately i didn't recive any  helpful reply in BIOSTARS would be happy for help here
liza
<r><gene><snp><p-values>
SKAT method in R
# SKAT method in R

(Asked by: username_0 on 2023-03-24)

I have data that looks like this: 3 column SNPs their gene based on Annovar and a p-value for every SNP. What I would like is to aggregate the p values for every gene.
snps <- data.frame(
  snp_id = c("rs1", "rs2", "rs3", "rs4", "rs5", "rs6", "rs7", "rs8"),
  Gene.refGene_ANNOVAR = c("gene1", "gene1", "gene1", "gene1", "gene2", "gene2", "gene2", "gene2"),
  p.value = c(0.7703884, 0.9648540, 0.9648540, 0.9648540, 0.54, 0.03, 0.03, 0.8)
)

above an example of the data .
I read about the SKAT method -> https://www.hsph.harvard.edu/skat/
and figured it might do the work .
I read about the package here:https://rdrr.io/cran/SKAT/man/SKAT.html
tried to implement it on my data , but got lost as how to perform it correctly:
gene_pvals <- aggregate(p.value ~ Gene.refGene_ANNOVAR, data = df, FUN = function(x) SKAT::SKAT_Null(x)$p.value)

I would be happy if you could share your knowledge in this situation.I don't have information about the correlations between the SNPs but I know that they are correlated, do I have enough data to complete the SKAT method?
also for every SNP i have data on how many patients had the hetro/homozygous encoding(0,1,2).

**Tags:** r, gene, snp, p-values
> **Comments:**
> **username_1**: cross posted: https://www.biostars.org/p/9558525  
> **username_0**: Unfortunately i didn't recive any  helpful reply in BIOSTARS would be happy for help here  

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## 0 answers

