How to find rs number of SNP when UCSC data base position known in reverse strand sequence

Question

[Nawaj Shaikh]

I have screened a human gene to find out its association with infection. For the same i have used UCSC data base as reference sequence. I have noted some intronic and exon base SNPs. To identify its rs number i used Predict SNP online tool but it gives following massage (The user's given refererence alleles of more than 50% input variants do not match the reference alleles of selected genome assembly (GRCh37/hg19 and GRCh38/hg38 supported). Please make sure that you selected correct genome assembly.) When i am choosing GRCh38/hg38 this option for genome assembly, same massage coming. Please anybody tell me How to find rs number of SNP when UCSC data base position known in reverse strand sequence? Is there another online tool use to identify rs number when reference sequence is reveres strand? or any other .... Please....

[finswimmer]

Hello,

how does your input looks like? How should your expected output look like?

fin swimmer

[Nawaj Shaikh]

I just need rs number in out put.

[finswimmer]

And your input? Please post an exact example.

[Nawaj Shaikh]

For example, I have screened a gene TLR9 for polymorphism and i found variation (G to T) at chromosome position chr3: 52222681 (UCSC data base) (rev), Hence i have to search what is rs number allotted for the same position. which online tools i can use to identify the same? Kindly guide me on same. Thanking you,

Answer 1

[ATpoint]

The user's given refererence alleles of more than 50% input variants do not match the reference alleles of selected genome assembly.

This sounds like a typical 1-based/0-based coordinate error. Check if the online tool expects 0-based (BED-like) coordinates or 1-based (genome browser) coordinates. Which tool did you use for variant calling?

If you called SNVs they are probably in VCF format? If so, you can use the Ensemble Variant Effect Predictor with the --check-existing option. It will give you dbSNP IDs in case of overlaps with your data and optionally a plethora of other annotations, such as allele frequencies in the 1000 Genomes project, polyphen scores etc.