Annotating your own variation data with the Ensembl Variant Effect Predictor VEP
ฝัง
- เผยแพร่เมื่อ 23 ส.ค. 2024
- The Ensembl VEP is a powerful tool that allows you to input a list of genetic variants and determines which genes are affected and how. In this webinar, you’ll learn how to use the online VEP tool, which is suitable for analysing short lists of genetic variants, and the offline tool, which allows you to annotate whole genome variant calls.
Who is this course for?
This webinar is suitable to any clinical or research scientists who are interested in exploring genetic variants and their effect. In this webinar we will use examples from human clinical data but the VEP tool is available for other species too.
The webinar was recorded on 03 March 2021.
The slides can be downloaded from On-demand training - www.ebi.ac.uk/...
See the EMBL-EBI training pages for a list of upcoming webinars - www.ebi.ac.uk/...
Thanks for sharing this webinar. It would be really useful to integrate this with the R package ensemblVEP, and/or some Python equivalent.
Thanks for sharing. I am Computer Science background, am doing PhD title on "An automated decision-making system to identify T2DM (type - II diabetes Miletus ) based on DNA sequences". i got data from which i have to figure it out diabetic variant from genomic dataset and i am stuck with it. i will be extremely glad if you can provides me some help in my research. Can you please drop some thing to contact you.
Perhaps a naive question but why is there such a focus on SNPs in genomics/bioinformatics? The "SN" meaning "single nucleotide", but aren't there many contiguous genomic variations that involve *multiple nucleotides* in a given stretch of DNA? Why don't they call it (or focus on) something like "contiguous nucleotide polymorphisms"?
In Ensembl, we have different types of variants for several species:
single nucleotide polymorphisms (SNPs)
short nucleotide insertions and/or deletions
longer variants classified as structural variants (including CNVs)
SNPs are the most common form of variation in the genome and they are extensively used to study genetic differences between individuals and populations.
For example, for human, most of the variation data is imported from Single Nucleotide Polymorphism database (dbSNP) which is a public-domain archive for a broad collection of simple genetic polymorphisms. This collection of polymorphisms includes single-base nucleotide substitutions, small-scale multi-base deletions or insertions (also called deletion insertion polymorphisms or DIPs), and retroposable element insertions and microsatellite repeat variations (also called short tandem repeats or STRs).
@@EnsemblHelpdesk I see, so I understand from this that the primary focus on "SNPs" is simply because they are the most common (and probably least complex) type of variant. Other types of variants exist but are presumably more complicated to include in any analysis of genetic variation between individuals/populations so (some/many) researchers just focus their analyses on SNPs.(?)
Very informative - thank you. I have had success the conda package for VEP:
conda create -n VEP109
conda activate VEP109
conda install ensembl-vep=109.3 (latest at time of installation)
conda install perl-compress-raw-zlib=2.202
An additional step was required (suggested during installation of the above) to install cache data. Here I installed human GCRh38:
vep_install -a cf -s homo_sapiens -y GRCh38 -c ~/.conda/envs/VEP109/ ~/.conda/envs/VEP109/GRCh38/ --CONVERT --PLUGINS all