Question: Random SNPs simulation?
gravatar for thomasbersez
4 months ago by
France INRA
thomasbersez20 wrote:

Hi everyone,

For an allele mining project I need to generate in silico NGS data. I have chosen to use Grinder to do so. I would like to add randomly generated SNPs to my reference genome, is any software available to do that ?

Thanks for help!

snp • 269 views
ADD COMMENTlink modified 4 days ago by meenatibiswalcynixit0 • written 4 months ago by thomasbersez20
gravatar for jean.elbers
4 months ago by
jean.elbers1.1k wrote:

You could try from BBTools/BBMap. can also produce a VCF file of the SNPs added. You can also generate random Illumina reads with the BBTool

ADD COMMENTlink modified 4 months ago • written 4 months ago by jean.elbers1.1k
gravatar for Corentin
4 months ago by
Corentin290 wrote:

Hi, you can also try Simulome, it is quite customisable.

ADD COMMENTlink written 4 months ago by Corentin290
gravatar for rainadawan
4 months ago by
rainadawan10 wrote:

To evaluate statistical methods for genome-wide genetic analyses, one needs to be able to simulate realistic genotypes. We here describe a method, applicable to a broad range of association study designs, that can simulate autosome-wide single-nucleotide polymorphism data with realistic linkage disequilibrium and with spiked in, user-specified, single or multi-SNP causal effects.

ADD COMMENTlink written 4 months ago by rainadawan10
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5 weeks ago by
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gravatar for meenatibiswalcynixit
4 days ago by
meenatibiswalcynixit0 wrote:

FASTmrEMMA is a new algorithm that can approximate the estimation of QTN variance (see Materials and Methods). Thus, we need to know whether this approximation has a significant effect on the estimate of QTN variance. Tableau To answer this question, four flowering time traits in Arabidopsis [29] were analyzed by FASTmrEMMA and an exact method implemented by PROC MIXED in SAS. The estimates for QTN variance are listed in Figure 1 and Table S1. As a result, the relative error between the two methods ranged from 0.0 to 24.09%, and the average was 1.60%, indicating no effect on the QTN variance estimate using FASTmrEMMA under the conditions of this simulation. Android

When the SNP effect is viewed as random, three variance components will be estimated. Generally, the polygenic variance is larger than zero while variance components for most SNPs are zero because these markers are not associated with the trait of interest. In other words, as in most mixed model approaches, variance components in FASTmrEMMA are also estimated under the assumption that one variance component is zero.

ADD COMMENTlink written 4 days ago by meenatibiswalcynixit0
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