2/ If you are working with human 🧑🤝🧑 variation data, genome-wide variant deleteriousness rankings from the CADD algorithm are available as well as pathogenicity predictions from SIFT, Polyphen-2, REVEL, MutationAssessor and MetaLR for missense variants.
3/ You can see all this data in the ‘Variant Table’ page in the gene tab
👉 https://t.co/vZAsntjEXYensembl.org/Homo_sapiens/G…
4/ or the ‘Genes and Regulation’ page when exploring a single variant in the variant tab
👉
https://t.co/rvA0FRoVY1ensembl.org/Homo_sapiens/V…
5/ SIFT predictions are also available for cat, chicken, cow, dog, goat, horse, mouse, pig, rat, sheep, zebrafish and a number of plant species 🐈⬛🐔🐄🐎🐕🐐🐭🐷🐀🐑🐟🌱
6/ You can also visualise missense variants mapped onto the #protein structure in the Transcript tab. Just click on ‘PDB 3D protein model’ in the menu on the left hand side of the page to see if a @PDBeurope structure is available.
@PDBeurope 7/ If not, you can view the predicted protein structures from #AlphaFoldDB for human, mouse and zebrafish by clicking on ‘AlphaFold predicted model’ in the menu on the left hand side of the page.
8/ Missense variants are mapped onto the protein and can be colour coordinated according to whether the SIFT or PolyPhen-2 score predicts a tolerated or deleterious effect
9/ All of this is great if you are looking at previously identified variants already in the Ensembl database, but if you have your own set of variants, you can also retreive pathogenicity predictions using the Variant Effect Predictor (VEP) tool:
2/ The #BioMart tool is what you’re going to need for this task. You can find it in the blue header from the @ensembl homepage: ensembl.org/biomart/martvi…
3/ First, you’ll need to select your database type and species of interest using the drop-down menus. In this case, we want to select ‘Ensembl Genes 111’ and the ‘Human genes’ dataset.
2/ Gene-level tissue-specific expression patterns from @ExpressionAtlas are displayed in the Gene tab. Just search for your gene of interest, click through to the gene tab and then click on ‘Gene Expression’ in the left-hand menu. Let’s use SERPINA3 as an example:
@ExpressionAtlas 3/ On this page, you can view baseline expression results as a heatmap with all tissues studied (columns) in different experiments (rows) in which the gene is expressed above the default minimum expression level.
2/ To start, look for the #canonical tag in the flags column of the transcript table. The canonical transcript is based on conservation, expression, concordance with @appris_cnio and @uniprot, length, clinically important variants and completeness.
3/ Many Ensembl #canonical transcripts will also be the #MANESelect, which is our collaboration with @NCBI. These transcripts match perfectly with RefSeq transcripts, so are the best to report variant location.
2/ If you need the sequence of a single #gene, you can search for the gene symbol or ID from Ensembl homepage and click on ‘Sequence’ in the menu on the left
3/ From this page, you can download the sequence of the gene by clicking on the blue ‘Download Sequence’ button just above the sequence display.
1/ It’s another Thursday, and that means it’s time for another #tweetorial! Today, we want to show you how you can view RefSeq #annotations on Ensembl 🥳
2/ While Ensembl gene models are annotated directly on the reference genome, #RefSeq are annotated on mRNA sequences. In other words: genome browsers will have different annotation methods, so you might be interested in comparing these annotations side-by-side 📖🤔
3/ 👂🏽You say you want to make direct comparisons of annotations between @NCBI’s RefSeq and Ensembl? Now is your time to try it out on Ensembl! 🏃🏽
2/ The Variant Effect Predictor (VEP) is what you’re going to need for this task. You can find it in the blue header from the @ensembl homepage: ensembl.org/info/docs/tool…
3/ Click the ‘Launch VEP’ button to open the VEP web tool and enter your input data using instructions in the documentation:
👉ensembl.org/info/docs/tool…