The number of genes and transcripts we have in Ensembl can make your VEP results very big. Filtering your results after running the VEP is the best way to make this more manageable, but you can also reduce the results in your run itself, to only get one result per variant or variant/gene combo.
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Did you know you can upload your own data for display alongside the reference genomes in Ensembl? For some file types, and files larger than 20MB in size you will need to create a URL to attach the data, rather than uploading from your local directory. It’s not difficult to create these URLs, but there are quite a few steps, so read on to find out how!
The VEP can work as an offline or a web tool and it’s also available as REST service. Perfect for integrating into pipelines or displaying data on the web, the REST API VEP endpoints can take input as HGVS, genomic loci or variant identifiers and can interpret common forms of non-standard HGVS. They are all available using both GET and POST protocols, supporting queries on single or multiple variants respectively.
Ever come across a transcript that seems to span multiple genes? These are called ‘readthrough transcripts’, or sometimes ‘conjoined genes’, and they’re more common than you might think. Read on to find out about what they are and what they do, and how we annotate these at Ensembl.
Identifying the causal variants from a GWAS generally involves identifying the haplotype blocks that contain your variant of interest, rather than the variant and the gene it is affecting itself. To find the actual genes involved, you need to consider all variants in LD with your identified associations. Ensembl Post-GWAS analysis pipeline (PostGAP) can provide automatic fine-tuning of your GWAS variants, incorporating regulatory information and population-wide LD calculations, along with your VEP results.
Most of the time when we talk about variant annotation, we talk about the effects of variants on genes, but did you know that the VEP can also tell you how variants affect the genomic features that regulate gene expression, such as promoter and enhancers?
If a variant hits a splice site, you want to know if splicing is going to occur as normal, or if you can expect a different protein isoform. We have a few cool tools with the VEP that will help you to assess that for your own variants.
In this blog we catch up with Ensembl’s 2018 Google Summer of Code (GSoC) students and hear about their now completed projects, and their reflections on the experience. You may have already seen our previous blog post which we published as they were just beginning their projects. Read on to find out how they went, what they learnt and what valuable advice they can pass on to aspiring GSoC students.
A common use case for the VEP is as a first step towards identifying the causal genetic variant of a rare phenotype from whole genome/exome sequencing. The VEP tells you which genes are hit, what effects they have on them, and you have to begin the long laborious process of filtering those down. Things you might consider include allele frequency, association with genes known to be involved in rare disease and whether both genes in a diploid organism are affected. Rather than faffing about doing this manually, you can use the G2P (genotype to phenotype) plugin instead, which was recently published as a preprint.
Rating variants for their potential deleteriousness is vital for solving the link between genotypes and phenotypes. There are many different algorithms for predicting how likely it is that a human variant would affect the function of a protein, and in release 94 of Ensembl, we’ll be making more of these available.