+This track shows the AlphaGenome Variant Impact (AVI) score, a prediction from Google DeepMind +of how likely a given substitution is to be disease causing. Scores are provided for every +possible single-base substitution at every position in the genome, about 8.8 billion in total. +Unlike predictors that only cover protein-coding changes, the AVI score is defined genome wide, +so it also scores variants in introns and in intergenic regulatory regions. +
+ ++Because there are three possible substitutions at each position, the scores are split across +four separate graphs, one for each alternate allele. The graph labelled "Mutation: A" shows the +score for changing the reference base to an A, and so on. At any given position only three of +the four graphs carry a real prediction; the fourth is the one matching the reference base, +where no substitution exists, and it is shown as zero. +
++The source data gives two numbers per variant, a raw model score and a PHRED-scaled version of +it. This track displays the PHRED-scaled score, which is easier to compare across variants: it +is a rank in which 10 corresponds to the top 10 percent of the most impactful substitutions in +the genome, 20 to the top 1 percent, and 30 to the top 0.1 percent. Higher values therefore +indicate a variant predicted to be more damaging. Most positions score low, with a genome-wide +median near 1.6, so the default view is scaled to 0 to 30 rather than to the observed maximum +of about 89. +
++Individual scores are only shown when the view is zoomed in far enough. At wider zoom levels the +graph shows the range of scores in each screen pixel rather than a single value. +
+ ++The AVI score comes from a machine learning model that combines several kinds of evidence about +a variant: AlphaGenome regulatory predictions, AlphaMissense pathogenicity scores for changes +that fall in coding sequence, measures of evolutionary sequence conservation, and further +functional annotations. Google DeepMind precomputed the score for all single-base substitutions +in GRCh38 and released it as a tab-separated, tabix-indexed table of chromosome, position, +reference allele, alternate allele, raw score and PHRED score. Note that the score has not yet +been described in a peer-reviewed publication. +
++The scores can be downloaded from the +AlphaGenome +Atlas. At UCSC the table was split into one wig file per alternate allele and each was +converted to bigWig. The PHRED column was copied through as text, so the values shown are +exactly those in the source file. The commands are documented in the +makeDoc, and the conversion program is in the +kent source tree. +
+ ++Google DeepMind's terms do not allow UCSC to redistribute this dataset, so it is not available +from the Table Browser, the Data Integrator, the Genome Browser API or our download server. The +full set of precomputed scores can be obtained directly from the +AlphaGenome +Atlas, which provides the same tab-separated, tabix-indexed file that this track was built +from. Scores for individual variants can also be read off the track in the browser by zooming in +until single bases are visible. +
++Use of the AlphaGenome Services and their output is subject to the +AlphaGenome +Services Additional Terms of Service. In summary, the Services are available only to +individuals and to non-commercial organizations such as universities, non-profit research +institutes, educational bodies and government bodies, or for journalism, and their output may not +be used for clinical purposes or relied on for medical advice. +
+ ++Thanks to Dhavanthi Hariharan, Francesca Pietra, Tom Ward and Elisa Wong at Google DeepMind for +providing this dataset and for their help with the track description. +