8
votes
Accepted
Is there any difference between SNPs 'AG' and 'GA' in association analyses?
Could you please show us the context in which this appears, as you seem to be interpreting this differently to Devon.
If it's appearing as you say, GA and AG, then Devon is right, this usually means ...
- 1,749
8
votes
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Where can I find a database that has phenotype information together with associated SNPs?
International Mouse Phenotyping Consortium is building a database of phenotypes and knock-outs of mouse. I believe that this database will be fairly complete (20000 knock-outs), but these are knock-...
- 5,497
6
votes
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How to deal with correlated SNPs in GWAS?
What you are attempting to do is known as LD-pruning.
As @Emily_Ensembl said, it is not customary to do this for standard association tests: it is possible that one of the SNPs you remove is causal, ...
- 463
5
votes
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What does PCA mean on GWAS
From my memory of what a statistician told me, a PCA aims to determine independent linear combinations of variables (i.e. genotypes) that account for the most variation in the dataset. With 10 million ...
- 13.5k
5
votes
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What does liability mean in GWAS heritability?
When you use linear mixed models to estimate heritability you assume that the underlying trait is normally distributed which is called a disease liability scale.
For continuous traits this is not a ...
- 393
5
votes
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PLINK clump behavior on missing SNPs?
Most likely, the GWASs that generated your summary statistics used other imputation panels than 1000G, like HRC. Clearly, PLINK can't estimate the LD for SNPs that aren't found in the reference, and ...
- 463
4
votes
Is there any difference between SNPs 'AG' and 'GA' in association analyses?
Is "user5054" the same as "user5504"? No? Exactly. Not only does order matter, it's incredibly vitally important. AG and GA are ...
- 19.5k
4
votes
Where can I find a database that has phenotype information together with associated SNPs?
A few days ago, I was trying to find some GWAS datasets to download. I hope this site for 3000 rice will help: http://snp-seek.irri.org/. You can click Genotype in the index page for "Query for SNPs ...
- 325
3
votes
how do I convert a vcf file for a GWAS study (using R package vcfR)
If you want to do GWAS or mendelian randomisation, you can do it with Plink (v2) which should be faster than R.
- 203
3
votes
PLINK clump behavior on missing SNPs?
You can use imputation for guessing at what the missing SNPs might be based on known LD patterns in populations. This procedure will give you an idea of whether the recombinational history of genomic ...
- 13.5k
3
votes
Is there any difference between SNPs 'AG' and 'GA' in association analyses?
Most association analyses are carried out at a single SNP level, so AG and GA are likely to indicate a heterozygous genotype at a particular location. However, the precise notation matters.
As @...
- 13.5k
3
votes
Filtering imputed GWAS SNPs based on a MAF difference of 10%
I cannot think of any principled rationale for choosing this filtering strategy.
However, I am going to take a guess that this filtering strategy is supposed to filter out SNPs for which imputation ...
- 2,216
3
votes
Accepted
GWAS, MWAS, EWAS: what are the (in)dependent variables?
To answer the first part of your question, the dependent and independent variable of X-WAS is kind of arbitrary and dependent on the question you asked. But it gradually becomes a convention in the ...
- 857
3
votes
Accepted
Odds ratio and enrichment of SNPs in gene regions?
The first approach only address the question of how likely are you to end up with the observed over-representation given the MAF distribution.
My suggestion is to use the second approach, but I am not ...
- 1,678
3
votes
How to z-transform Fst and -log(p) values for genome wide selection scan?
The standard score can be estimated by using the sample mean and sample standard deviation as estimates of the population values. Just as you wrote it in the question.
The z-score is given by
$ z = \...
- 750
2
votes
How to filter info score post-imputation?
In simple GWAS setups, each SNP is analyzed independently. In those cases you can filter out SNPs with poor INFO scores at any point.
For analyses that combine information across SNPs (for example ...
- 2,216
2
votes
Accepted
Assuming that we have the following SNP and phenotype data, is the SNP significantly associated with the phenotype?
Your approach is correct - it's not the only one permitted under their conditions, but it would be the standard way given only that information.
F-test compares a "full model" (predicting the ...
- 463
2
votes
What are the differences between GWAS and QTL mapping?
Most papers that I've looked at distinguish between looking for genotype/trait associations in mapping populations created by experimental crosses (QTL mapping) and looking for genotype/trait ...
- 1,816
2
votes
Accepted
Adjusting phenotypes by regressing out covariates
Instead of the "observed phenotype", it's asking for a "corrected phenotype", which is the residuals from pheno ~ covariates. In R, one would get that as follows:
<...
- 19.5k
2
votes
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Parallel in PLINK for linear association for SNP effects
Try the latest plink 2.0 alpha build for this. It’s an incomplete program, but its implementation of —linear is far better than v1.9’s.
2
votes
Accepted
Odds ratio calculations in GWAS paper
Those odds ratio aren't calculated from the raw allele frequencies. They're calculated from coefficients estimated from complex linear models with a bunch of covariates that are run on subsets of the ...
- 1,816
2
votes
significant SNPs to annotated candidate genes
You can use BEDOPS' closest-features tool. You only need to have the SNPs coordinates in .bed format and a .bed file with gene locations. BEDOPS will look for the closest genes upstream and downstream ...
- 1,022
2
votes
Accepted
Pandas automatically rounds GWAS P-value
The solution you likely want is here,
pd.set_eng_float_format(accuracy=x, use_eng_prefix=True)
x = whatever is required
The function set_eng_float_format has ...
M__♦
- 11.3k
2
votes
What does PCA mean on GWAS
PCA = principle component analysis and a multivariate statistic, today it is trendily retermed "unsupervised learning" and here is likely being deployed for individuals within your data set. It works ...
M__♦
- 11.3k
2
votes
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PLINK - Transposed BED file?
Yes, this exists, and can be efficiently generated by plink 2.0's --export ind-major-bed command. (The third byte is 0 instead of 1, and the specification is ...
2
votes
Is there a way to do GWAS on phenotype data that is not normally distributed?
Yes, that can be done.
A common approach for these types of analysis is to carry out a transformation on the data first in order for it to have a normal distribution (the most general approach called ...
- 13.5k
2
votes
Accepted
What is the state of the art for GWAS in terms of the statistical algorithm for either Case/control and Quantitative traits?
I've got the answer to my question at https://www.biostars.org/p/410466/ by chrchang522
"The main regression executed by Plink was introduced by EIGENSTRAT in ~2006; see https://www.nature.com/...
- 207
2
votes
Interpreting GWAS results with different settings
Based on the QQ plots, filter out variants with p > 0.01, then display the beta statistic (or whatever other statistic you're using to demonstrate association). If you want to incorporate the p-...
- 13.5k
2
votes
How do I lift GWAS results to hg38?
Yes. LiftOver tools, if they work on VCF data (some only take BED as input) work on GWAS summary statistics. You could use
https://pypi.org/project/liftover/, for example.
- 364
2
votes
Making PLINK compatible files from VCF file without phenotype information
You can use --pheno to specify a phenotype file you want to use, the 1st and 2nd columns being FID and IID. These are just used on the fly and cannot be written to ...
- 857
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