Our FAQ page shows the description of the file format and how you may use iPGS coefficients in your research.
Population | Model | Metric | Predictive Performance | 95% CI | P-value |
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Population | Model | Metric | Predictive Performance | 95% CI | P-value |
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white British | Covariate-only model | R2 | 0.064 | [0.060, 0.068] | <1.0x10-300 |
white British | Genotype-only model | R2 | 0.086 | [0.082, 0.090] | <1.0x10-300 |
white British | Full model (covariates and genotypes) | R2 | 0.149 | [0.144, 0.154] | <1.0x10-300 |
Non-British white | Covariate-only model | R2 | 0.041 | [0.027, 0.055] | 1.4x10-27 |
Non-British white | Genotype-only model | R2 | 0.082 | [0.063, 0.101] | 1.4x10-54 |
Non-British white | Full model (covariates and genotypes) | R2 | 0.124 | [0.101, 0.146] | 1.7x10-83 |
South Asian | Covariate-only model | R2 | 0.150 | [0.116, 0.183] | 4.0x10-53 |
South Asian | Genotype-only model | R2 | 0.074 | [0.048, 0.099] | 4.9x10-26 |
South Asian | Full model (covariates and genotypes) | R2 | 0.198 | [0.162, 0.234] | 1.0x10-71 |
African | Covariate-only model | R2 | 0.190 | [0.151, 0.230] | 2.6x10-55 |
African | Genotype-only model | R2 | 0.008 | [-0.002, 0.019] | 1.6x10-03 |
African | Full model (covariates and genotypes) | R2 | 0.134 | [0.098, 0.170] | 2.7x10-38 |
Others | Covariate-only model | R2 | 0.078 | [0.066, 0.089] | 1.6x10-139 |
Others | Genotype-only model | R2 | 0.080 | [0.068, 0.091] | 2.1x10-143 |
Others | Full model (covariates and genotypes) | R2 | 0.146 | [0.131, 0.160] | 4.6x10-270 |
The predictive performance (R2), its 95% confidence interval (CI), and statistical significance (P-value) are shown for each population in UK Biobank in the held-out test set. The "model" column indicates whether the predictive performance is from the covariate-terms alone (covariate-only model), PGS terms alone (Genotype-only model), or the full model containing both PGS and covariate terms. We used the following sets of covariates in our analysis: age, sex, age2, age*sex, Townsend deprivation index, and genotype PCs (PC1-PC18). Please refer to our publication for a more detailed description of the methods.
We show the coefficients (BETA) of PGS models. Our iPGS model selected 29790 variants with non-zero coefficients. The genetic variants with the large absolute values of coefficients are annotated in the plot. There is no guarantee that our iPGS model selects causal variants. We use the GRCh37/hg19 reference genome.
CHROM | POS | Variant | Variant ID | Effect allele | Consequence | Gene symbol | Beta |
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CHROM | POS | Variant | Variant ID | Effect allele | Consequence | Gene symbol | Beta |
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16 | 53800954 | 16:53800954:T:C | rs1421085 | C | Intronic | FTO | 0.038 |
2 | 417167 | 2:417167:T:C | rs62106258 | C | Others | AC105393.2 | -0.032 |
18 | 58039276 | 18:58039276:C:T | rs2229616 | T | PAVs | MC4R | -0.028 |
1 | 177889480 | 1:177889480:A:G | rs543874 | G | Others | SEC16B | 0.021 |
19 | 46181392 | 19:46181392:G:C | rs1800437 | C | PAVs | GIPR | -0.019 |
18 | 57852587 | 18:57852587:T:C | rs476828 | C | Others | 0.018 | |
11 | 27679916 | 11:27679916:C:T | rs6265 | T | PAVs | BDNF | -0.015 |
4 | 45179883 | 4:45179883:C:T | rs12641981 | T | Others | 0.013 | |
3 | 12393125 | 3:12393125:C:G | rs1801282 | G | PAVs | PPARG | 0.012 |
11 | 117076972 | 11:117076972:C:A | rs45574931 | A | PAVs | PCSK7 | -0.012 |
16 | 19944363 | 16:19944363:A:G | rs11639988 | G | Others | -0.012 | |
19 | 47569003 | 19:47569003:G:A | rs3810291 | A | UTR | ZC3H4 | 0.012 |
2 | 25141538 | 2:25141538:A:G | rs11676272 | G | PAVs | ADCY3 | 0.011 |
2 | 635721 | 2:635721:T:C | rs6755502 | C | Others | 0.011 | |
4 | 25408838 | 4:25408838:G:A | rs34811474 | A | PAVs | ANAPC4 | -0.011 |
3 | 49924940 | 3:49924940:T:C | rs1062633 | C | PAVs | MST1R | 0.011 |
12 | 50247468 | 12:50247468:G:A | rs7138803 | A | Others | 0.010 | |
3 | 141326602 | 3:141326602:T:C | rs295322 | C | PAVs | RASA2 | 0.010 |
6 | 40371918 | 6:40371918:C:T | rs1579557 | T | Intronic | LRFN2 | 0.010 |
3 | 185822353 | 3:185822353:T:G | rs10513801 | G | Intronic | ETV5 | -0.010 |
12 | 123087442 | 12:123087442:A:G | rs7307735 | G | PAVs | KNTC1 | 0.010 |
17 | 65838743 | 17:65838743:T:G | rs8074078 | G | Intronic | BPTF | 0.010 |
16 | 53756885 | 16:53756885:A:G | rs76488452 | G | Intronic | FTO | 0.010 |
6 | 31595882 | 6:31595882:C:A | rs1046080 | A | PAVs | PRRC2A | 0.009 |
14 | 29685328 | 14:29685328:G:A | rs974471 | A | Others | 0.009 | |
15 | 92571283 | 15:92571283:G:T | rs12101386 | T | Intronic | SLCO3A1 | -0.009 |
16 | 4013467 | 16:4013467:C:T | rs2531995 | T | UTR | ADCY9 | 0.009 |
8 | 73439070 | 8:73439070:A:G | rs1431659 | G | Others | -0.009 | |
6 | 13189275 | 6:13189275:T:C | rs9367368 | C | Intronic | PHACTR1 | -0.009 |
12 | 124413491 | 12:124413491:G:A | rs9971695 | A | UTR | DNAH10OS | 0.009 |
16 | 20370810 | 16:20370810:C:T | rs9652588 | T | PAVs | PDILT | -0.009 |
1 | 78623626 | 1:78623626:C:T | rs17391694 | T | Others | 0.009 | |
3 | 51755065 | 3:51755065:T:C | rs4687770 | C | Others | GRM2 | -0.009 |
6 | 34827085 | 6:34827085:A:T | rs9469913 | T | PAVs | UHRF1BP1 | 0.009 |
19 | 18820308 | 19:18820308:C:A | rs757318 | A | Intronic | CRTC1 | -0.009 |
5 | 75003678 | 5:75003678:T:C | rs2307111 | C | PAVs | POC5 | -0.009 |
12 | 117160976 | 12:117160976:T:C | rs10507274 | C | PAVs | C12orf49 | -0.009 |
18 | 21120444 | 18:21120444:T:C | rs1805082 | C | PAVs | NPC1 | -0.009 |
4 | 103188709 | 4:103188709:C:T | rs13107325 | T | PAVs | SLC39A8 | 0.009 |
6 | 50865820 | 6:50865820:C:T | rs943005 | T | Others | RP4-753D5.3 | 0.008 |
10 | 21830104 | 10:21830104:A:G | rs11012732 | G | Intronic | MLLT10 | 0.008 |
1 | 1546304 | 1:1546304:C:T | rs11492279 | T | Others | MIB2 | -0.008 |
2 | 622827 | 2:622827:T:C | rs2867125 | C | Others | 0.008 | |
4 | 102709308 | 4:102709308:T:C | rs11097755 | C | Intronic | BANK1 | 0.008 |
5 | 145895394 | 5:145895394:G:A | rs114285050 | A | PTVs | GPR151 | -0.008 |
8 | 138215228 | 8:138215228:G:A | rs16906845 | A | Others | -0.008 | |
8 | 77228222 | 8:77228222:A:G | rs1405348 | G | Others | 0.008 | |
18 | 42606091 | 18:42606091:C:T | rs9967367 | T | Intronic | SETBP1 | -0.008 |
1 | 201869257 | 1:201869257:G:A | rs2820312 | A | PAVs | LMOD1 | 0.008 |
17 | 47123423 | 17:47123423:T:C | rs4643373 | C | Intronic | IGF2BP1 | -0.008 |
4 | 100239319 | 4:100239319:T:C | rs1229984 | C | PAVs | ADH1B | 0.008 |
19 | 19789528 | 19:19789528:A:G | rs2304130 | G | PAVs | ZNF101 | -0.008 |
X | 117904229 | X:117904229:T:C | rs2248846 | C | PTVs | IL13RA1 | 0.008 |
1 | 98348885 | 1:98348885:G:A | rs1801265 | A | PAVs | DPYD | -0.008 |
14 | 103246470 | 14:103246470:A:G | rs3803286 | G | Intronic | TRAF3 | -0.008 |
2 | 236817629 | 2:236817629:C:T | rs4663215 | T | Intronic | AGAP1 | -0.008 |
5 | 95728898 | 5:95728898:C:G | rs6235 | G | PAVs | PCSK1 | 0.008 |
7 | 76608143 | 7:76608143:C:T | rs2245368 | T | Others | DTX2P1 | -0.008 |
14 | 79942647 | 14:79942647:G:A | rs7156625 | A | Intronic | NRXN3 | 0.008 |
19 | 4061190 | 19:4061190:C:T | rs10414261 | T | Intronic | ZBTB7A | -0.008 |
13 | 40759773 | 13:40759773:T:C | rs10507483 | C | Intronic | LINC00332 | 0.008 |
17 | 46252346 | 17:46252346:T:C | rs208015 | C | Intronic | SKAP1 | -0.008 |
1 | 110210780 | 1:110210780:C:G | rs530021 | G | PAVs | GSTM2 | -0.008 |
10 | 73964243 | 10:73964243:G:C | rs11000217 | C | PTVs | ASCC1 | 0.008 |
6 | 50820940 | 6:50820940:T:C | rs2635727 | C | Others | RPS17P5 | 0.008 |
2 | 142293511 | 2:142293511:A:G | rs13008033 | G | Intronic | LRP1B | -0.008 |
1 | 190303149 | 1:190303149:C:T | rs648091 | T | Intronic | RP11-547I7.1, BRINP3 | -0.008 |
6 | 34824636 | 6:34824636:A:G | rs11755393 | G | PAVs | UHRF1BP1 | 0.007 |
10 | 99772404 | 10:99772404:G:A | rs563296 | A | Intronic | CRTAC1 | 0.007 |
15 | 75130093 | 15:75130093:T:C | rs12898397 | C | PAVs | ULK3 | 0.007 |
16 | 31088625 | 16:31088625:A:G | rs749670 | G | PAVs | ZNF646 | -0.007 |
10 | 61831984 | 10:61831984:G:T | rs11599164 | T | PAVs | ANK3 | 0.007 |
18 | 57839769 | 18:57839769:C:A | rs571312 | A | Others | 0.007 | |
20 | 15819495 | 20:15819495:A:G | rs8123881 | G | Intronic | MACROD2 | 0.007 |
1 | 32165495 | 1:32165495:G:T | rs2228552 | T | PAVs | COL16A1 | 0.007 |
20 | 54153759 | 20:54153759:A:G | rs2244665 | G | Others | 0.007 | |
17 | 1824305 | 17:1824305:C:A | rs4790292 | A | Others | -0.007 | |
7 | 77423560 | 7:77423560:ATCCAGACTGGAATG:A | rs866484129 | A | PTVs | TMEM60 | 0.007 |
21 | 32638550 | 21:32638550:C:T | rs2070418 | T | PAVs | TIAM1 | -0.007 |
19 | 19413092 | 19:19413092:C:T | rs17751061 | T | PAVs | SUGP1 | -0.007 |
1 | 201934578 | 1:201934578:G:A | rs4648 | A | PAVs | TIMM17A | 0.007 |
16 | 2821525 | 16:2821525:G:A | rs4036 | A | PAVs | TCEB2 | 0.007 |
16 | 54299503 | 16:54299503:C:T | rs10521300 | T | Intronic | RP11-324D17.1 | 0.007 |
3 | 183976103 | 3:183976103:C:T | rs11546878 | T | PAVs | ECE2 | -0.007 |
2 | 162904013 | 2:162904013:T:C | rs116302758 | C | PTVs | DPP4 | -0.007 |
16 | 24793741 | 16:24793741:C:T | rs2343606 | T | Intronic | TNRC6A | -0.007 |
17 | 78611724 | 17:78611724:A:G | rs12939549 | G | Intronic | RPTOR | -0.007 |
6 | 43757082 | 6:43757082:T:A | rs4711750 | A | Others | VEGFA | -0.007 |
6 | 48415152 | 6:48415152:G:A | rs9395354 | A | Others | 0.007 | |
10 | 76854564 | 10:76854564:C:T | rs3088142 | T | PAVs | DUSP13 | 0.007 |
16 | 71264561 | 16:71264561:A:G | rs3743953 | G | PTVs | HYDIN | -0.007 |
14 | 25930988 | 14:25930988:C:A | rs8015400 | A | Others | 0.006 | |
6 | 153381622 | 6:153381622:A:C | rs2185027 | C | Intronic | RGS17 | 0.006 |
13 | 58631525 | 13:58631525:A:G | rs9569808 | G | Others | -0.006 | |
1 | 194961172 | 1:194961172:A:G | rs7349184 | G | Others | -0.006 | |
13 | 53484591 | 13:53484591:G:A | rs4884286 | A | Others | -0.006 | |
7 | 2801803 | 7:2801803:C:T | rs798489 | T | PTVs | GNA12 | -0.006 |
15 | 68082816 | 15:68082816:G:A | rs2241420 | A | Intronic | MAP2K5 | -0.006 |
3 | 12426936 | 3:12426936:G:T | rs10510419 | T | Intronic | PPARG | -0.006 |
7 | 113503703 | 7:113503703:G:A | rs10247621 | A | Others | -0.006 |
There is no guarantee that our iPGS model selects causal variants. We show the top 100 variants with the largest effect size (BETA). To see 29790 variants included in our iPGS model, please download the iPGS coefficients by clicking the download button. We use the GRCh37/hg19 reference genome.
There are several ways to use the resource in your research. First, you may use our iPGS coefficients and compute individual-level polygenic scores for your cohort. Second, you may also investigate the genetic variants with non-zero coefficients and their annotated genes to learn more about biology by taking advantage of the sparsity of our iPGS models. For your convenience, here we suggest several resources as an example of follow-up analysis. We do not intend to cover all the relevant follow-up analyses.
By clicking the download button above, you may download the iPGS coefficients. Our FAQ page shows the description of file format and how you may use iPGS coefficients in your research.
HaploReg is a tool for exploring annotations of the non-coding genome at variants on haplotype blocks. The button above submits the top 100 genetic variants with the largest absolute value of coefficients as a query to HaploReg using the default parameters in HaploReg v4.2 (LD threshold r2 >= 1, ChromHMM 15-state model, SiPhy-omega, and GENCODE genes). HaploReg's ability to browse haplotypes is useful here as there is no guarantee that our iPGS model selects causal variants. The 'top 100 variant' cutoff is an arbitrary threshold; we aim to demonstrate how one may investigate the selected variants. Please check Ward and Kellis. Nucleic Acids Res. 2012 and Ward and Kellis. Nucleic Acids Res. 2016 for more information on HaploReg.
GREAT: Genomic Regions Enrichment of Annotations Tool evaluates enrichment of pathway and ontology terms. The ability of GREAT to map non-coding genetic variants to their downstream target genes would be suitable for investigating pathway and ontology enrichment of genetic variants selected in our sparse iPGS model. The button above submits the top 1000 genetic variants with the largest absolute value of coefficients as a query to GREAT using the default parameters in GREAT v4.0.4. The 'top 1000 variant' cutoff is an arbitrary threshold; we aim to demonstrate how one may investigate the selected variants. Please check McLean et al. Nat Biotechnol. 2010 and Tanigawa*, Dyer*, and Bejerano. PLoS Comput Biol. 2022 for more information on GREAT.
For anthropometric traits, it may be relevant to investigate the single-cell expression profiling data in adipose-muscle tissues. Please check Single Cell Metab Browser from Yang*, Vamvini*, Nigro* et al. Cell Metab. 2022 as an example of such resources.