Joannella Morales, Jane Loveland and Adam Frankish contributed to this post.
Back in October, we introduced you to our new joint initiative with the NCBI — the Matched Annotation from the NCBI and EMBL-EBI (MANE) transcript set. We are now pleased to update you on our progress so far.
The goal of this project is to share annotation and converge on a high-confidence, genome-wide transcript set, with a matched transcript in both RefSeq and Ensembl/GENCODE. We are doing this in two phases. During phase 1, we will release the “MANE Select” transcript set to include one well-supported transcript for every protein-coding locus. We envision the adoption of the MANE Select set as a default set across genomics resources. In phase 2, we intend to release an expanded set (“MANE Plus”) to include additional transcripts per locus that are well-supported or of particular user interest.
As of Ensembl release 96/Ensembl Genomes release 43, we will retire rest.ensemblgenomes.org and invite you to use rest.ensembl.org instead.
In the next release of Ensembl (Ensembl 96) we will remove our ontology database patching scripts from the main Ensembl repository.
There is now a dedicated module using the EBI OLS service to load Ensembl required ontologies. Considering this module is now in charge of loading the required data, the previous databases patches have been moved to the ols-ensembl-loader repository.
If you need to update your system with future patches, please now refer to the ols-ensembl-loader repository sql directory where files are already available.
Please contact the Ensembl Helpdesk if you have any questions or want to find out more about how this might affect your work.
Today we are meeting Guy, who works in the Plants team of Ensembl Genomes. He talks about how he came to Ensembl, his interests and experiences so far.
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.
We are planning to release Ensembl 96 and Ensembl Genomes 43 in late March or beginning of April 2019.
The Ensembl 96 release includes the first pass full annotation of the mouse genome, with the GENCODE M21 gene set.
The Ensembl Genomes 43 release will bring changes to our REST API and FTP server that may affect your pipelines. Specifically, we will merge our Ensembl and Ensembl Genomes REST servers into a single server. We will also change the Ensembl Genomes Comparative Genomics FTP file structure to make it consistent with Ensembl.
We have got lots of new genomes: 19 birds, five reptiles and 12 mammals, which include primates, rodents, American mink, American bison and wild yak.
We also have an exciting first release of Ensembl-RefSeq MANE Select v0.5 transcripts!
Due to a major loss of cooling incident at one of the EMBL-EBI data centres, there was reduced Ensembl functionality between Saturday 2nd February and Wednesday 6th February.
However, as of Wednesday 6th February, all Ensembl and Ensembl Genomes services have now been restored and are working as normal.
If you encounter any further issues, please report them to the Ensembl Helpdesk.
Thank you for your understanding and patience while we worked to fully restore our services.
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.