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The "Splicing Impact" container track contains tracks showing the predicted or validated effect of variants
close to splice sites.
AbSplice
AbSplice is a method that predicts aberrant splicing across human tissues, as described in Wagner,
Çelik et al., 2023. This track displays precomputed AbSplice scores for all possible
single-nucleotide variants genome-wide. The scores represent the probability that a given variant
causes aberrant splicing in a given tissue.
AbSplice scores
can be computed from VCF files and are based on quantitative tissue-specific splice site annotations
(SpliceMaps).
While SpliceMaps can be generated for any tissue of interest from a cohort of RNA-seq samples, this
track includes 49 tissues available from the
Genotype-Tissue
Expression (GTEx) dataset.
SpliceAI Variants
SpliceAI is an open-source deep
learning splicing prediction algorithm that can predict splicing alterations caused by DNA variations.
To score variants, the spliceAI algorithm is run on the genome sequence itself and scores each
nucleotide for the probability that it is a donor or acceptor site, on both the
forward and the reverse strand. Then variants are added to the sequence and the new sequence is
scored. Variants may activate nearby cryptic splice sites, leading to abnormal transcript isoforms.
SpliceAI was developed at Illumina; a
lookup tool
is provided by the Broad institute.
SpliceAI Wildtype
This SpliceAI "Wildtype" container track shows the scores for the genome sequence itself,
without variants, from predicted splice donor (5' intron boundaries) and splice acceptor
(3' intron boundaries) sites. Predictions are strand-specific, with separate subtracks for the
plus and minus strands. These tracks are useful in combination with the variants track for
evaluating new transcript models. They can be used to assess potential exon boundaries or
possible splice acceptor sites.
Why are some variants not scored by SpliceAI?
SpliceAI only annotates variants within genes defined by the gene
annotation file. Additionally, SpliceAI does not annotate variants if they are close to chromosome
ends (5kb on either side), deletions of length greater than twice the input parameter -D, or
inconsistent with the reference fasta file.
What are the differences between masked and unmasked tracks?
The unmasked tracks include splicing changes corresponding to strengthening annotated splice sites
and weakening unannotated splice sites, which are typically much less pathogenic than weakening
annotated splice sites and strengthening unannotated splice sites. The delta scores of such splicing
changes are set to 0 in the masked files. We recommend using the unmasked tracks for alternative
splicing analysis and masked tracks for variant interpretation.
SpliceVarDB
SpliceVarDB is an online database consolidating over 50,000 variants assayed
for their effects on splicing in over 8,000 human genes. The authors evaluated
over 500 published data sources and established a spliceogenicity scale to
standardize, harmonize, and consolidate variant validation data generated by a
range of experimental protocols. Genes and variant locations were obtained using
GENCODE v44. Splice regions were calculated as specific distances from the closest
canonical exon, including 5' and 3' untranslated regions (UTRs). The
database is available at
splicevardb.org.
To view the full description, click here.
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