Summary
Summary {data-width=650}
Manhattan plot
manhattan_plot
QQ plot
qq_plot
AF plot
af_plot
P-Z plot
pz_plot
beta_std plot
beta_std_plot
Metadata
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}
LDSC
*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call:
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30760_raw/ukb-d-30760_raw.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30760_raw/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Mon Nov 25 14:53:38 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30760_raw/ukb-d-30760_raw.vcf.gz ...
Read summary statistics for 13585297 SNPs.
Dropped 12712 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2536 (0.0488)
Lambda GC: 1.6862
Mean Chi^2: 2.5432
Intercept: 1.1384 (0.0187)
Ratio: 0.0897 (0.0121)
Analysis finished at Mon Nov 25 14:55:55 2019
Total time elapsed: 2.0m:16.2sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9521,
"inflation_factor": 1.4117,
"mean_EFFECT": 3.3547e-06,
"n": 315133,
"n_snps": 13585297,
"n_clumped_hits": 267,
"n_p_sig": 52598,
"n_mono": 0,
"n_ns": 1251737,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 568995,
"n_est": 316366.4335,
"ratio_se_n": 1.002,
"mean_diff": 4.9263e-06,
"ratio_diff": 3.7456,
"sd_y_est1": 0.3489,
"sd_y_est2": 0.3496,
"r2_sum1": 0.0136,
"r2_sum2": 0.1114,
"r2_sum3": 0.111,
"r2_sum4": 0.1107,
"ldsc_nsnp_merge_refpanel_ld": 1283502,
"ldsc_nsnp_merge_regression_ld": 1283502,
"ldsc_observed_scale_h2_beta": 0.2536,
"ldsc_observed_scale_h2_se": 0.0488,
"ldsc_intercept_beta": 1.1384,
"ldsc_intercept_se": 0.0187,
"ldsc_lambda_gc": 1.6862,
"ldsc_mean_chisq": 2.5432,
"ldsc_ratio": 0.0897
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | TRUE |
| n | FALSE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | TRUE |
| n_p_sig | TRUE |
| miss_EFFECT | FALSE |
| miss_SE | FALSE |
| miss_PVAL | FALSE |
| ldsc_ratio | FALSE |
| ldsc_intercept_beta | FALSE |
| n_clumped_hits | FALSE |
| r2_sum1 | FALSE |
| r2_sum2 | FALSE |
| r2_sum3 | FALSE |
| r2_sum4 | FALSE |
Definitions
General metrics
af_correlation: Correlation coefficient betweenAFandAF_reference.inflation_factor(lambda): Genomic inflation factor.mean_EFFECT: Mean ofEFFECTsize.n: Maximum value of reported sample size across all SNPs, \(n\).n_clumped_hits: Number of clumped hits.n_snps: Number of SNPsn_p_sig: Number of SNPs with pvalue below5e-8.n_mono: Number of monomorphic (MAF == 1orMAF == 0) SNPs.n_ns: Number of SNPs with nonsense values:- alleles other than
A, C, G or T. - P-values
< 0or> 1. - negative or infinite standard errors (
<= 0or= Infinity). - infinite beta estimates or allele frequencies
< 0or> 1.
- alleles other than
n_mac: Number of cases whereMAC(\(2 \times N \times MAF\)) is less than6.is_snpid_unique:trueif the combination ofIDREFALTis unique and therefore no duplication in snpid.n_miss_<*>: Number ofNAobservations for<*>column.
se_n metrics
n_est: Estimated sample size value, \(\widehat{n}\).ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expectratio_se_nto be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.- \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
- \({z}_j = \frac{\beta_j}{{se}_j}\),
- and \(\beta_j\) is the reported effect size.
ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean ofdiffand the mean ofdiff2(expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.- \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
- \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.- \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
- \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
- and \({se}_j\) is the reported standard error.
sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.- \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
- \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),
r2 metrics
Sum of variance explained, calculated from the clumped top hits sample.
r2_sum<*>:r2statistics under various assumptions1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).
LDSC metrics
Metrics from LD regression
ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.ldsc_observed_scale_h2_{beta,se}Coefficient value and SE for total observed scale h2.ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.ldsc_lambda_gc: Lambda GC statistics.ldsc_mean_chisq: Mean \(\chi^2\) statistics.ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).
Flags
When a metric needs attention, the flag should return TRUE.
af_correlation:abs(af_correlation)< 0.7.inflation_factor:inflation_factor> 1.2.n:n(max reported sample size) < 10000.is_snpid_non_unique: NOTis_snpid_unique.mean_EFFECT_nonfinite:mean(EFFECT)isNA,NaN, orInf.mean_EFFECT_05:abs(mean(EFFECT))> 0.5.mean_EFFECT_01:abs(mean(EFFECT))> 0.1.mean_chisq:ldsc_mean_chisq> 1.3 orldsc_mean_chisq< 0.7.n_p_sig:n_p_sig> 1000.miss_<*>:n_miss_<*>/n_snps> 0.01.ldsc_ratio:ldsc_ratio> 0.5ldsc_intercept_beta:ldsc_intercept_beta> 1.5n_clumped_hits:n_clumped_hits> 1000r2_sum<*>:r2_sum<*>> 0.5
Plots
- Manhattan plot
- Red line: \(-log_{10}^{5 \times 10^{-8}}\)
- Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
- QQ plot
- AF plot
- P-Z plot
- beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)
Diagnostics
Details
Summary stats
| skim_type | skim_variable | n_missing | complete_rate | character.min | character.max | character.empty | character.n_unique | character.whitespace | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 0 | 1.0000000 | 3 | 94 | 0 | 13573249 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 57080 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33335 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.051264e+00 | 6.184949e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.902526e+07 | 5.591521e+07 | 3.02000e+02 | 3.293044e+07 | 7.013885e+07 | 1.148599e+08 | 2.492309e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.400000e-06 | 5.510500e-03 | -1.64900e-01 | -1.709400e-03 | 9.600000e-06 | 1.703700e-03 | 3.737500e-01 | ▁▇▁▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.692400e-03 | 3.561700e-03 | 7.21700e-04 | 1.051500e-03 | 1.937300e-03 | 5.306100e-03 | 1.795900e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.428064e-01 | 3.046711e-01 | 0.00000e+00 | 1.639400e-01 | 4.229003e-01 | 7.066803e-01 | 1.000000e+00 | ▇▆▅▅▅ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.428058e-01 | 3.046713e-01 | 0.00000e+00 | 1.639362e-01 | 4.229013e-01 | 7.066824e-01 | 9.999999e-01 | ▇▆▅▅▅ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.908198e-01 | 2.544077e-01 | 1.00000e-03 | 7.434100e-03 | 6.004500e-02 | 2.953300e-01 | 9.990000e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 568995 | 0.9581169 | NA | NA | NA | NA | NA | 1.963465e-01 | 2.471051e-01 | 0.00000e+00 | 5.591000e-03 | 8.426520e-02 | 3.081070e-01 | 1.000000e+00 | ▇▂▁▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.151330e+05 | 0.000000e+00 | 3.15133e+05 | 3.151330e+05 | 3.151330e+05 | 3.151330e+05 | 3.151330e+05 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 692794 | rs530212009 | CA | C | 0.0015669 | 0.0015393 | 0.3087003 | 0.3087111 | 0.1105400 | 0.1894970 | 315133 |
| 1 | 693731 | rs12238997 | A | G | 0.0016203 | 0.0014541 | 0.2651698 | 0.2651516 | 0.1158500 | 0.1417730 | 315133 |
| 1 | 707522 | rs371890604 | G | C | 0.0016986 | 0.0016362 | 0.2991899 | 0.2992062 | 0.0972120 | 0.1293930 | 315133 |
| 1 | 717587 | rs144155419 | G | A | 0.0047342 | 0.0038959 | 0.2242999 | 0.2242994 | 0.0157110 | 0.0045926 | 315133 |
| 1 | 723329 | rs189787166 | A | T | 0.0020644 | 0.0115090 | 0.8576500 | 0.8576451 | 0.0017335 | 0.0003994 | 315133 |
| 1 | 730087 | rs148120343 | T | C | 0.0036084 | 0.0020257 | 0.0748652 | 0.0748618 | 0.0564740 | 0.0127796 | 315133 |
| 1 | 731718 | rs142557973 | T | C | 0.0013135 | 0.0013794 | 0.3409699 | 0.3409826 | 0.1217300 | 0.1543530 | 315133 |
| 1 | 732032 | rs61770163 | A | C | 0.0015257 | 0.0014720 | 0.2999701 | 0.2999778 | 0.1210900 | 0.1555510 | 315133 |
| 1 | 734349 | rs141242758 | T | C | 0.0013361 | 0.0013801 | 0.3329799 | 0.3329853 | 0.1209500 | 0.1525560 | 315133 |
| 1 | 740284 | rs61770167 | C | T | -0.0006696 | 0.0063274 | 0.9157101 | 0.9157146 | 0.0057544 | 0.0023962 | 315133 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154923311 | rs141127553 | C | T | 0.0008356 | 0.0015929 | 0.5998905 | 0.5998942 | 0.056084 | 0.0309934 | 315133 |
| 23 | 154923374 | rs111332691 | T | A | 0.0001139 | 0.0017430 | 0.9478801 | 0.9478839 | 0.045008 | 0.0116556 | 315133 |
| 23 | 154925045 | rs509981 | C | T | 0.0045587 | 0.0008414 | 0.0000001 | 0.0000001 | 0.245770 | 0.3634440 | 315133 |
| 23 | 154925895 | rs538470 | C | T | 0.0044807 | 0.0008607 | 0.0000002 | 0.0000002 | 0.242060 | 0.3634440 | 315133 |
| 23 | 154927581 | rs644138 | G | A | 0.0042377 | 0.0007914 | 0.0000001 | 0.0000001 | 0.302240 | 0.4635760 | 315133 |
| 23 | 154929412 | rs557132 | C | T | 0.0045569 | 0.0008416 | 0.0000001 | 0.0000001 | 0.245620 | 0.3568210 | 315133 |
| 23 | 154929637 | rs35185538 | CT | C | 0.0050777 | 0.0008782 | 0.0000000 | 0.0000000 | 0.230010 | 0.3011920 | 315133 |
| 23 | 154929952 | rs4012982 | CAA | C | 0.0046083 | 0.0008851 | 0.0000002 | 0.0000002 | 0.239560 | 0.3165560 | 315133 |
| 23 | 154930230 | rs781880 | A | G | 0.0045175 | 0.0008415 | 0.0000001 | 0.0000001 | 0.246000 | 0.3618540 | 315133 |
| 23 | 154930487 | rs781879 | T | A | 0.0023424 | 0.0028927 | 0.4180796 | 0.4180767 | 0.019473 | 0.1263580 | 315133 |
bcf preview
1 692794 rs530212009 CA C . PASS AF=0.11054 ES:SE:LP:AF:SS:ID 0.0015669:0.0015393:0.510463:0.11054:315133:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.11585 ES:SE:LP:AF:SS:ID 0.0016203:0.0014541:0.576476:0.11585:315133:rs12238997
1 707522 rs371890604 G C . PASS AF=0.097212 ES:SE:LP:AF:SS:ID 0.0016986:0.0016362:0.524053:0.097212:315133:rs371890604
1 717587 rs144155419 G A . PASS AF=0.015711 ES:SE:LP:AF:SS:ID 0.0047342:0.0038959:0.649171:0.015711:315133:rs144155419
1 723329 rs189787166 A T . PASS AF=0.0017335 ES:SE:LP:AF:SS:ID 0.0020644:0.011509:0.0666899:0.0017335:315133:rs189787166
1 730087 rs148120343 T C . PASS AF=0.056474 ES:SE:LP:AF:SS:ID 0.0036084:0.0020257:1.12572:0.056474:315133:rs148120343
1 731718 rs58276399 T C . PASS AF=0.12173 ES:SE:LP:AF:SS:ID 0.0013135:0.0013794:0.467284:0.12173:315133:rs58276399
1 732032 rs61770163 A C . PASS AF=0.12109 ES:SE:LP:AF:SS:ID 0.0015257:0.001472:0.522922:0.12109:315133:rs61770163
1 734349 rs141242758 T C . PASS AF=0.12095 ES:SE:LP:AF:SS:ID 0.0013361:0.0013801:0.477582:0.12095:315133:rs141242758
1 740284 rs61770167 C T . PASS AF=0.0057544 ES:SE:LP:AF:SS:ID -0.00066965:0.0063274:0.038242:0.0057544:315133:rs61770167
1 742813 rs112573343 C T . PASS AF=0.0018569 ES:SE:LP:AF:SS:ID 0.016557:0.012009:0.774742:0.0018569:315133:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.86974 ES:SE:LP:AF:SS:ID -0.001015:0.0013605:0.341359:0.86974:315133:rs529266287
1 750230 rs190826124 G C . PASS AF=0.0015184 ES:SE:LP:AF:SS:ID -0.014991:0.012366:0.647046:0.0015184:315133:rs190826124
1 751343 rs28544273 T A . PASS AF=0.12292 ES:SE:LP:AF:SS:ID 0.0010872:0.0013475:0.376989:0.12292:315133:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.14273 ES:SE:LP:AF:SS:ID 0.00074632:0.0013317:0.240196:0.14273:315133:rs200141114
1 751756 rs28527770 T C . PASS AF=0.12304 ES:SE:LP:AF:SS:ID 0.0010476:0.0013456:0.360245:0.12304:315133:rs28527770
1 753405 rs3115860 C A . PASS AF=0.87096 ES:SE:LP:AF:SS:ID -0.0013668:0.0013116:0.526703:0.87096:315133:rs3115860
1 753425 rs3131970 T C . PASS AF=0.87548 ES:SE:LP:AF:SS:ID -0.0011052:0.001333:0.390331:0.87548:315133:rs3131970
1 753541 rs2073813 G A . PASS AF=0.12859 ES:SE:LP:AF:SS:ID 0.0011901:0.0013148:0.437243:0.12859:315133:rs2073813
1 754105 rs12184325 C T . PASS AF=0.036316 ES:SE:LP:AF:SS:ID -0.0013757:0.0023862:0.248521:0.036316:315133:rs12184325
1 754182 rs3131969 A G . PASS AF=0.87054 ES:SE:LP:AF:SS:ID -0.0013973:0.0013102:0.5433:0.87054:315133:rs3131969
1 754192 rs3131968 A G . PASS AF=0.87066 ES:SE:LP:AF:SS:ID -0.0015001:0.0013109:0.597807:0.87066:315133:rs3131968
1 754334 rs3131967 T C . PASS AF=0.87054 ES:SE:LP:AF:SS:ID -0.0013982:0.0013102:0.543816:0.87054:315133:rs3131967
1 754433 rs150578204 G A . PASS AF=0.0050347 ES:SE:LP:AF:SS:ID -0.00041236:0.0067234:0.0217784:0.0050347:315133:rs150578204
1 754458 rs142682604 G T . PASS AF=0.0050013 ES:SE:LP:AF:SS:ID -0.00017181:0.0067416:0.00892019:0.0050013:315133:rs142682604
1 755435 rs184270342 T G . PASS AF=0.0055145 ES:SE:LP:AF:SS:ID -0.0016382:0.0065546:0.0954792:0.0055145:315133:rs184270342
1 755890 rs3115858 A T . PASS AF=0.87064 ES:SE:LP:AF:SS:ID -0.0014386:0.001308:0.566406:0.87064:315133:rs3115858
1 756434 rs61768170 G C . PASS AF=0.12593 ES:SE:LP:AF:SS:ID 0.0013481:0.0013344:0.505317:0.12593:315133:rs61768170
1 756604 rs3131962 A G . PASS AF=0.87021 ES:SE:LP:AF:SS:ID -0.0015704:0.0013049:0.640582:0.87021:315133:rs3131962
1 757640 rs3115853 G A . PASS AF=0.86948 ES:SE:LP:AF:SS:ID -0.0013681:0.0013037:0.531667:0.86948:315133:rs3115853
1 757734 rs4951929 C T . PASS AF=0.87035 ES:SE:LP:AF:SS:ID -0.0015066:0.001306:0.604394:0.87035:315133:rs4951929
1 757936 rs4951862 C A . PASS AF=0.87036 ES:SE:LP:AF:SS:ID -0.0015121:0.0013061:0.607391:0.87036:315133:rs4951862
1 758144 rs3131956 A G . PASS AF=0.87037 ES:SE:LP:AF:SS:ID -0.0015197:0.0013061:0.611544:0.87037:315133:rs3131956
1 758626 rs3131954 C T . PASS AF=0.87081 ES:SE:LP:AF:SS:ID -0.0014718:0.0013094:0.583343:0.87081:315133:rs3131954
1 759293 rs10157329 T A . PASS AF=0.098804 ES:SE:LP:AF:SS:ID 0.0011295:0.0015218:0.339191:0.098804:315133:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.006394 ES:SE:LP:AF:SS:ID -0.0031425:0.0059243:0.224892:0.006394:315133:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.87466 ES:SE:LP:AF:SS:ID -0.0015003:0.0013286:0.587053:0.87466:315133:rs3115851
1 761732 rs2286139 C T . PASS AF=0.86409 ES:SE:LP:AF:SS:ID -0.0013304:0.0013033:0.512395:0.86409:315133:rs2286139
1 761752 rs1057213 C T . PASS AF=0.86948 ES:SE:LP:AF:SS:ID -0.0015298:0.0013157:0.61094:0.86948:315133:rs1057213
1 762273 rs3115849 G A . PASS AF=0.86643 ES:SE:LP:AF:SS:ID -0.0013698:0.0013159:0.525915:0.86643:315133:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0988 ES:SE:LP:AF:SS:ID 0.00086077:0.0015748:0.233104:0.0988:315133:rs12095200
1 762589 rs3115848 G C . PASS AF=0.87159 ES:SE:LP:AF:SS:ID -0.0015522:0.0013308:0.613555:0.87159:315133:rs3115848
1 762592 rs3131950 C G . PASS AF=0.87159 ES:SE:LP:AF:SS:ID -0.0015523:0.0013308:0.613608:0.87159:315133:rs3131950
1 762601 rs3131949 T C . PASS AF=0.87159 ES:SE:LP:AF:SS:ID -0.0015572:0.0013309:0.616221:0.87159:315133:rs3131949
1 762632 rs3131948 T A . PASS AF=0.87195 ES:SE:LP:AF:SS:ID -0.0015497:0.0013316:0.611739:0.87195:315133:rs3131948
1 764191 rs7515915 T G . PASS AF=0.12555 ES:SE:LP:AF:SS:ID 0.0013076:0.0013326:0.486183:0.12555:315133:rs7515915
1 766007 rs61768174 A C . PASS AF=0.10538 ES:SE:LP:AF:SS:ID 0.0015298:0.0014515:0.534766:0.10538:315133:rs61768174
1 766105 rs2519015 T A . PASS AF=0.85542 ES:SE:LP:AF:SS:ID -0.001988:0.0013027:0.896196:0.85542:315133:rs2519015
1 767393 rs538667473 A C . PASS AF=0.0016515 ES:SE:LP:AF:SS:ID 0.0030976:0.011541:0.103264:0.0016515:315133:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.83823 ES:SE:LP:AF:SS:ID 0.0012242:0.0012815:0.469263:0.83823:315133:rs376645387