The Genome Aggregation Database (gnomAD) - Predicted Constraint Metrics track set contains metrics of pathogenicity per-gene as predicted for gnomAD v2.1.1 and identifies genes subject to strong selection against various classes of mutation.
This track includes several subtracks of constraint metrics calculated at gene (canonical transcript), transcript and transcript-region level. For more information see the following blog post. The metrics include:
There are three "groups" of tracks in this set:
Clicking the grey box to the left of the track, or right-clicking and choosing the Configure option, brings up the interface for filtering items based on their pLI score, or labeling the items based on their Ensembl identifier and/or Gene Name.
Please see the gnomAD browser help page and FAQ for further explanation of the topics below.
Observed count: The number of unique single-nucleotide variants in each transcript/gene with 123 or fewer alternative alleles (MAF < 0.1%).
Expected count: A depth-corrected probability prediction model that takes into account sequence context, coverage, and methylation was used to predict expected variant counts. For more information please see Lek et al., 2016.
Variants found in exons with a median depth < 1 were removed from both counts.
The O/E constraint score is the ratio of the observed/expected variants in that gene. Each item in this track shows the O/E ratio for three different types of variation: missense, synonymous, and loss-of-function. The O/E ratio is a continuous measurement of how tolerant a gene or transcript is to a certain class of variation. When a gene has a low O/E value, it is under stronger selection for that class of variation than a gene with a higher O/E value. Because Counts depend on gene size and sample size, the precision of the values varies a lot from one gene to the next. Therefore, the 90% confidence interval (CI) is also displayed along with the O/E ratio to better assist interpretation of the scores.
When evaluating how constrained a gene is, it is essential to consider the CI when using O/E. In research and clinical interpretation of Mendelian cases, pLI > 0.9 has been widely used for filtering. Accordingly, the Gnomad team suggests using the upper bound of the O/E confidence interval LOEUF < 0.35 as a threshold if needed.
Please see the Methods section below for more information about how the scores were calculated.
The pLI and Z-scores of the deviation of observed variant counts relative to the expected number are intended to measure how constrained or intolerant a gene or transcript is to a specific type of variation. Genes or transcripts that are particularly depleted of a specific class of variation (as observed in the gnomAD data set) are considered intolerant of that specific type of variation. Z-scores are available for the missense and synonynmous categories and pLI scores are available for the loss-of-function variation.
NOTE: The Regional Constraint track data reflects regions within transcripts that are intolerant of missense variation within the ExAc dataset and was calculated with the method described by Samocha et al., 2017.
Missense and Synonymous: Positive Z-scores indicate more constraint (fewer observed variants than expected), and negative scores indicate less constraint (more observed variants than expected). A greater Z-score indicates more intolerance to the class of variation. Z-scores were generated by a sequence-context-based mutational model that predicted the number of expected rare (< 1% MAF) variants per transcript. The square root of the chi-squared value of the deviation of observed counts from expected counts was multiplied by -1 if the observed count was greater than the expected and vice versa. For the synonymous score, each Z-score was corrected by dividing by the standard deviation of all synonymous Z-scores between -5 and 5. For the missense scores, a mirrored distribution of all Z-scores between -5 and 0 was created, and then all missense Z-scores were corrected by dividing by the standard deviation of the Z-score of the mirror distribution.
Loss-of-function: pLI closer to 1 indicates that the gene or transcript cannot tolerate protein truncating variation (nonsense, splice acceptor and splice donor variation). The gnomAD team recommends transcripts with a pLI >= 0.9 for the set of transcripts extremely intolerant to truncating variants. pLI is based on the idea that transcripts can be classified into three categories:
Please see Samocha et al., 2014 and Lek et al., 2016 for further discussion of these metrics.
Transcripts from GENCODE v19 were filtered according to the following criteria:
Per gene and per transcript data were downloaded from the gnomAD Google Storage bucket:
gs://gnomad-public/release/2.1.1/constraint/gnomad.v2.1.1.lof_metrics.by_gene.txt.bgz gs://gnomad-public/release/2.1.1/constraint/gnomad.v2.1.1.lof_metrics.by_transcript.txt.bgzThese data were then joined to the Gencode v19 set of genes/transcripts available at the UCSC Genome Browser and then transformed into a bigBed 12+5. For the full list of commands used to make this track please see the "gnomAD 2 pLI and other loss-of-function metrics" section of the makedoc.
Supplementary Table 4 from the associated publication was downloaded and joined to the Gencode v19 set of transcripts available at UCSC and then transformed into a bigBed 12+6. For the full list of commands used to make this track please the "gnomAD Missense Constraint Scores" section of the makedoc.
The raw data can be explored interactively with the Table Browser, or
the Data Integrator. For automated access, this track, like all
others, is available via our API. However, for bulk
processing, it is recommended to download the dataset. The genome annotation is stored in a bigBed
file that can be downloaded from the
download server. The exact
filenames can be found in the track configuration file. Annotations can be converted to ASCII text
by our tool bigBedToBed
which can be compiled from the source code or downloaded as
a precompiled binary for your system. Instructions for downloading source code and binaries can be
found here. The tool
can also be used to obtain only features within a given range, for example:
bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg19/gnomAD/pLI/pliByTranscript.bb -chrom=chr6 -start=0 -end=1000000 stdout
Please refer to our mailing list archives for questions and example queries, or our Data Access FAQ for more information.
More information about using and understanding the gnomAD data can be found in the gnomAD FAQ site.
Thanks to the Genome Aggregation Database Consortium for making these data available. The data are released under the ODC Open Database License (ODbL) as described here.
Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, O'Donnell-Luria AH, Ware JS, Hill AJ, Cummings BB et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016 Aug 18;536(7616):285-91. PMID: 27535533; PMC: PMC5018207
Karczewski KJ, Francioli LC, Tiao G, Cummings BB, Alföldi J, Wang Q, Collins RL, Laricchia KM, Ganna A, Birnbaum DP et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature. 2020 May;581(7809):434-443. PMID: 32461654; PMC: PMC7334197
Collins RL, Brand H, Karczewski KJ, Zhao X, Alföldi J, Francioli LC, Khera AV, Lowther C, Gauthier LD, Wang H et al. A structural variation reference for medical and population genetics. Nature. 2020 May;581(7809):444-451. PMID: 32461652; PMC: PMC7334194
Cummings BB, Karczewski KJ, Kosmicki JA, Seaby EG, Watts NA, Singer-Berk M, Mudge JM, Karjalainen J, Satterstrom FK, O'Donnell-Luria AH et al. Transcript expression-aware annotation improves rare variant interpretation. Nature. 2020 May;581(7809):452-458. PMID: 32461655; PMC: PMC7334198