<p>You need to run a SNP finding pipeline, filter for SNPs in those genes and then run a SNP annotation pipeline. (You could annotate before you filter but it will take longer).</p>

<p>SNP finding usually has three steps, 1) read alignment to reference, 2) SNP calling and 3) SNP filtering (by quality).</p>

<p>You then bring in gene annotation data to filter SNPs to just those genes.</p>

<p>You then run SNP annotation using tools like VEP, SIFT, PolyPhen, etc.</p>

<p>People use tools like GATK to do this.</p>

<p>Hopefully that's enough information to get you started.</p>

CC BY-SA 4.0
2020-01-13T14:02:56.187Z
2020-01-13T14:02:56.187Z
Dan Bolser
<p>Is there any user friendly way to find rare mutations in the individual human whole genome sequencing raw data? (from Dante, 30x coverage).</p>

<p>To be more specific, I want to find mutations from this paper:</p>

<p><a href="https://docs.google.com/document/d/1EkRMuD6J0-zyMY3MegKhz7Th0hzhzVXg6DWg2Hm6l2Y/edit?usp=sharing" rel="nofollow noreferrer">https://docs.google.com/document/d/1EkRMuD6J0-zyMY3MegKhz7Th0hzhzVXg6DWg2Hm6l2Y/edit?usp=sharing</a>
(it's very short, less than one page).</p>

<p>But I'm confused. In their paper they just talk about genes (RAD21, B3GAT2, SMC3, SCN11A , SCN5A, SCN9A, SCN10A, SCN11A, TRPA1), but not mutations? Can we find that diseased-mutations which they talking about in genes, which their list? Or is there not enough data in the paper/study for this?</p>

<p>And if there is not enough data, which data I need to request from authors?</p>

<p>Or those genes have kind a "gold standard sequences" and if that sequence different from standard - there is "diseased" gene?
(I have only very basic genetics and bioinformatics knowledges)</p>

CC BY-SA 4.0
2020-01-08T10:08:14.840Z
@ATpoint do you have a script set up to systematically find when users cross-post to BioStar or Reddit? (Just wondering how common this trend is)
Matteo Ferla
CC BY-SA 4.0
2020-01-08T12:49:25.863Z
That isn't a paper, it's just an abstract. You can read the actual paper here: https://doi.org/10.1016/S0016-5085(17)30765-5 but it isn't available for free. Presumably, the paper will give the actual variants found.
terdon
<gene><ngs><genome><sequence-analysis>
Any user friendly way to find rare mutations in whole genome raw?
# Any user friendly way to find rare mutations in whole genome raw?

(Asked by: username_0 on 2020-01-07)

Is there any user friendly way to find rare mutations in the individual human whole genome sequencing raw data? (from Dante, 30x coverage).

To be more specific, I want to find mutations from this paper:

<https://docs.google.com/document/d/1EkRMuD6J0-zyMY3MegKhz7Th0hzhzVXg6DWg2Hm6l2Y/edit?usp=sharing>
(it's very short, less than one page).

But I'm confused. In their paper they just talk about genes (RAD21, B3GAT2, SMC3, SCN11A , SCN5A, SCN9A, SCN10A, SCN11A, TRPA1), but not mutations? Can we find that diseased-mutations which they talking about in genes, which their list? Or is there not enough data in the paper/study for this?

And if there is not enough data, which data I need to request from authors?

Or those genes have kind a "gold standard sequences" and if that sequence different from standard - there is "diseased" gene?
(I have only very basic genetics and bioinformatics knowledges)

**Tags:** gene, ngs, genome, sequence-analysis
> **Comments:**
> **username_1**: @ATpoint do you have a script set up to systematically find when users cross-post to BioStar or Reddit? (Just wondering how common this trend is)  
> **username_2**: That isn't a paper, it's just an abstract. You can read the actual paper here: https://doi.org/10.1016/S0016-5085(17)30765-5 but it isn't available for free. Presumably, the paper will give the actual variants found.  

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## 1 answers

### Answer by username_3 on 2020-01-13. Score: 1

You need to run a SNP finding pipeline, filter for SNPs in those genes and then run a SNP annotation pipeline. (You could annotate before you filter but it will take longer).

SNP finding usually has three steps, 1) read alignment to reference, 2) SNP calling and 3) SNP filtering (by quality).

You then bring in gene annotation data to filter SNPs to just those genes.

You then run SNP annotation using tools like VEP, SIFT, PolyPhen, etc.

People use tools like GATK to do this.

Hopefully that's enough information to get you started.


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