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-1747_2/ukb-d-1747_2.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-1747_2/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 17:06:41 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1747_2/ukb-d-1747_2.vcf.gz ...
Read summary statistics for 13586530 SNPs.
Dropped 12711 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1543 (0.1371)
Lambda GC: 1.0496
Mean Chi^2: 2.1614
Intercept: 1.0019 (0.0102)
Ratio: 0.0016 (0.0088)
Analysis finished at Mon Nov 25 17:08:59 2019
Total time elapsed: 2.0m:18.25sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9521,
"inflation_factor": 1.0266,
"mean_EFFECT": -4.0578e-06,
"n": 360270,
"n_snps": 13586530,
"n_clumped_hits": 28,
"n_p_sig": 13349,
"n_mono": 0,
"n_ns": 1251807,
"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": 569284,
"n_est": 361642.8888,
"ratio_se_n": 1.0019,
"mean_diff": -0,
"ratio_diff": 18.4753,
"sd_y_est1": 0.2102,
"sd_y_est2": 0.2106,
"r2_sum1": 0.0012,
"r2_sum2": 0.0268,
"r2_sum3": 0.0267,
"r2_sum4": 0.026,
"ldsc_nsnp_merge_refpanel_ld": 1283504,
"ldsc_nsnp_merge_regression_ld": 1283504,
"ldsc_observed_scale_h2_beta": 0.1543,
"ldsc_observed_scale_h2_se": 0.1371,
"ldsc_intercept_beta": 1.0019,
"ldsc_intercept_se": 0.0102,
"ldsc_lambda_gc": 1.0496,
"ldsc_mean_chisq": 2.1614,
"ldsc_ratio": 0.0016
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| 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 | 13574483 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 57082 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33336 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.051332e+00 | 6.184976e+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 | 7.902492e+07 | 5.591479e+07 | 3.02000e+02 | 3.293086e+07 | 7.013828e+07 | 1.148589e+08 | 2.492309e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -4.100000e-06 | 3.047400e-03 | -1.37443e-01 | -7.887000e-04 | -7.400000e-06 | 7.650000e-04 | 2.402350e-01 | ▁▇▁▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.081000e-03 | 2.007400e-03 | 4.07200e-04 | 5.924000e-04 | 1.091800e-03 | 2.990600e-03 | 1.009730e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.955055e-01 | 2.906828e-01 | 0.00000e+00 | 2.425912e-01 | 4.943574e-01 | 7.475874e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.955050e-01 | 2.906830e-01 | 0.00000e+00 | 2.425903e-01 | 4.943561e-01 | 7.475880e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.908023e-01 | 2.544021e-01 | 1.00000e-03 | 7.429300e-03 | 6.003020e-02 | 2.953080e-01 | 9.989990e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 569284 | 0.9580994 | NA | NA | NA | NA | NA | 1.963336e-01 | 2.471006e-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 | 3.602700e+05 | 0.000000e+00 | 3.60270e+05 | 3.602700e+05 | 3.602700e+05 | 3.602700e+05 | 3.602700e+05 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 692794 | rs530212009 | CA | C | 0.0013070 | 0.0008672 | 0.1317501 | 0.1317495 | 0.1106500 | 0.1894970 | 360270 |
| 1 | 693731 | rs12238997 | A | G | 0.0003813 | 0.0008194 | 0.6417059 | 0.6417063 | 0.1158380 | 0.1417730 | 360270 |
| 1 | 707522 | rs371890604 | G | C | -0.0000470 | 0.0009213 | 0.9593260 | 0.9593264 | 0.0972910 | 0.1293930 | 360270 |
| 1 | 717587 | rs144155419 | G | A | 0.0045506 | 0.0021972 | 0.0383522 | 0.0383516 | 0.0157019 | 0.0045926 | 360270 |
| 1 | 723329 | rs189787166 | A | T | -0.0086182 | 0.0064920 | 0.1843440 | 0.1843437 | 0.0017308 | 0.0003994 | 360270 |
| 1 | 730087 | rs148120343 | T | C | 0.0018431 | 0.0011417 | 0.1064371 | 0.1064373 | 0.0564472 | 0.0127796 | 360270 |
| 1 | 731718 | rs142557973 | T | C | 0.0004225 | 0.0007771 | 0.5867012 | 0.5867004 | 0.1217410 | 0.1543530 | 360270 |
| 1 | 732032 | rs61770163 | A | C | 0.0002912 | 0.0008290 | 0.7254158 | 0.7254146 | 0.1211730 | 0.1555510 | 360270 |
| 1 | 734349 | rs141242758 | T | C | 0.0003755 | 0.0007775 | 0.6291483 | 0.6291474 | 0.1209690 | 0.1525560 | 360270 |
| 1 | 740284 | rs61770167 | C | T | -0.0024307 | 0.0035556 | 0.4942083 | 0.4942078 | 0.0057907 | 0.0023962 | 360270 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154923311 | rs141127553 | C | T | 0.0006370 | 0.0008982 | 0.4782500 | 0.4782502 | 0.0561460 | 0.0309934 | 360270 |
| 23 | 154923374 | rs111332691 | T | A | -0.0016842 | 0.0009870 | 0.0879346 | 0.0879330 | 0.0447845 | 0.0116556 | 360270 |
| 23 | 154925045 | rs509981 | C | T | -0.0002639 | 0.0004749 | 0.5783637 | 0.5783623 | 0.2456300 | 0.3634440 | 360270 |
| 23 | 154925895 | rs538470 | C | T | -0.0002917 | 0.0004857 | 0.5481419 | 0.5481424 | 0.2419380 | 0.3634440 | 360270 |
| 23 | 154927581 | rs644138 | G | A | -0.0000951 | 0.0004466 | 0.8314331 | 0.8314327 | 0.3021610 | 0.4635760 | 360270 |
| 23 | 154929412 | rs557132 | C | T | -0.0002629 | 0.0004750 | 0.5798905 | 0.5798887 | 0.2454820 | 0.3568210 | 360270 |
| 23 | 154929637 | rs35185538 | CT | C | -0.0006072 | 0.0004957 | 0.2206358 | 0.2206351 | 0.2297100 | 0.3011920 | 360270 |
| 23 | 154929952 | rs4012982 | CAA | C | -0.0001625 | 0.0004996 | 0.7449910 | 0.7449918 | 0.2394580 | 0.3165560 | 360270 |
| 23 | 154930230 | rs781880 | A | G | -0.0002574 | 0.0004749 | 0.5877843 | 0.5877833 | 0.2458930 | 0.3618540 | 360270 |
| 23 | 154930487 | rs781879 | T | A | 0.0001475 | 0.0016285 | 0.9278419 | 0.9278423 | 0.0195732 | 0.1263580 | 360270 |
bcf preview
1 692794 rs530212009 CA C . PASS AF=0.11065 ES:SE:LP:AF:SS:ID 0.00130702:0.000867162:0.880249:0.11065:360270:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.115838 ES:SE:LP:AF:SS:ID 0.000381274:0.00081939:0.192664:0.115838:360270:rs12238997
1 707522 rs371890604 G C . PASS AF=0.097291 ES:SE:LP:AF:SS:ID -4.69842e-05:0.000921278:0.0180338:0.097291:360270:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0157019 ES:SE:LP:AF:SS:ID 0.00455059:0.00219721:1.41621:0.0157019:360270:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00173076 ES:SE:LP:AF:SS:ID -0.00861819:0.00649205:0.734371:0.00173076:360270:rs189787166
1 730087 rs148120343 T C . PASS AF=0.0564472 ES:SE:LP:AF:SS:ID 0.00184313:0.00114167:0.972907:0.0564472:360270:rs148120343
1 731718 rs58276399 T C . PASS AF=0.121741 ES:SE:LP:AF:SS:ID 0.000422456:0.000777111:0.231583:0.121741:360270:rs58276399
1 732032 rs61770163 A C . PASS AF=0.121173 ES:SE:LP:AF:SS:ID 0.000291158:0.000828963:0.139413:0.121173:360270:rs61770163
1 734349 rs141242758 T C . PASS AF=0.120969 ES:SE:LP:AF:SS:ID 0.000375489:0.000777527:0.201247:0.120969:360270:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00579066 ES:SE:LP:AF:SS:ID -0.0024307:0.00355557:0.30609:0.00579066:360270:rs61770167
1 742813 rs112573343 C T . PASS AF=0.00187672 ES:SE:LP:AF:SS:ID -0.00105324:0.00672112:0.0577558:0.00187672:360270:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.869737 ES:SE:LP:AF:SS:ID -0.000169844:0.000766517:0.0837345:0.869737:360270:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00153102 ES:SE:LP:AF:SS:ID 0.00475321:0.00693777:0.306917:0.00153102:360270:rs190826124
1 751343 rs28544273 T A . PASS AF=0.122922 ES:SE:LP:AF:SS:ID 0.000244846:0.000759144:0.126649:0.122922:360270:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.142717 ES:SE:LP:AF:SS:ID 0.000761991:0.000750362:0.508822:0.142717:360270:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123037 ES:SE:LP:AF:SS:ID 0.000244024:0.000758088:0.12637:0.123037:360270:rs28527770
1 753405 rs3115860 C A . PASS AF=0.87088 ES:SE:LP:AF:SS:ID -0.00030724:0.00073873:0.169102:0.87088:360270:rs3115860
1 753425 rs3131970 T C . PASS AF=0.875466 ES:SE:LP:AF:SS:ID -0.000256925:0.000750987:0.135333:0.875466:360270:rs3131970
1 753541 rs2073813 G A . PASS AF=0.128643 ES:SE:LP:AF:SS:ID 0.000284366:0.000740572:0.154287:0.128643:360270:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0363464 ES:SE:LP:AF:SS:ID 0.00133011:0.00134386:0.491759:0.0363464:360270:rs12184325
1 754182 rs3131969 A G . PASS AF=0.870474 ES:SE:LP:AF:SS:ID -0.000327112:0.000737963:0.182055:0.870474:360270:rs3131969
1 754192 rs3131968 A G . PASS AF=0.870579 ES:SE:LP:AF:SS:ID -0.000303869:0.0007383:0.167077:0.870579:360270:rs3131968
1 754334 rs3131967 T C . PASS AF=0.870471 ES:SE:LP:AF:SS:ID -0.00033887:0.000737935:0.189713:0.870471:360270:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00505041 ES:SE:LP:AF:SS:ID -0.00489152:0.00378585:0.706991:0.00505041:360270:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00501736 ES:SE:LP:AF:SS:ID -0.00482249:0.00379597:0.690508:0.00501736:360270:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00558719 ES:SE:LP:AF:SS:ID -0.00135911:0.00366886:0.148099:0.00558719:360270:rs184270342
1 755890 rs3115858 A T . PASS AF=0.870552 ES:SE:LP:AF:SS:ID -0.000290026:0.000736632:0.158773:0.870552:360270:rs3115858
1 756434 rs61768170 G C . PASS AF=0.125993 ES:SE:LP:AF:SS:ID 0.000239567:0.000751638:0.124977:0.125993:360270:rs61768170
1 756604 rs3131962 A G . PASS AF=0.870117 ES:SE:LP:AF:SS:ID -0.000312212:0.00073486:0.173317:0.870117:360270:rs3131962
1 757640 rs3115853 G A . PASS AF=0.869406 ES:SE:LP:AF:SS:ID -0.000408034:0.000734192:0.23779:0.869406:360270:rs3115853
1 757734 rs4951929 C T . PASS AF=0.870272 ES:SE:LP:AF:SS:ID -0.000326817:0.000735494:0.182573:0.870272:360270:rs4951929
1 757936 rs4951862 C A . PASS AF=0.870278 ES:SE:LP:AF:SS:ID -0.000327015:0.000735546:0.182687:0.870278:360270:rs4951862
1 758144 rs3131956 A G . PASS AF=0.870287 ES:SE:LP:AF:SS:ID -0.000330625:0.000735569:0.185031:0.870287:360270:rs3131956
1 758626 rs3131954 C T . PASS AF=0.870728 ES:SE:LP:AF:SS:ID -0.000290099:0.000737441:0.158619:0.870728:360270:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0988323 ES:SE:LP:AF:SS:ID -0.000124595:0.000857011:0.0533473:0.0988323:360270:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00647755 ES:SE:LP:AF:SS:ID -0.00304648:0.00331444:0.446098:0.00647755:360270:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.874628 ES:SE:LP:AF:SS:ID -0.000228379:0.000748443:0.119037:0.874628:360270:rs3115851
1 761732 rs2286139 C T . PASS AF=0.864021 ES:SE:LP:AF:SS:ID -0.00037748:0.000733953:0.216786:0.864021:360270:rs2286139
1 761752 rs1057213 C T . PASS AF=0.869415 ES:SE:LP:AF:SS:ID -0.000319884:0.000741077:0.176527:0.869415:360270:rs1057213
1 762273 rs3115849 G A . PASS AF=0.866359 ES:SE:LP:AF:SS:ID -0.000272441:0.000741223:0.146786:0.866359:360270:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0987912 ES:SE:LP:AF:SS:ID 0.000640202:0.000887382:0.327318:0.0987912:360270:rs12095200
1 762589 rs3115848 G C . PASS AF=0.871548 ES:SE:LP:AF:SS:ID -0.000252464:0.000749679:0.132948:0.871548:360270:rs3115848
1 762592 rs3131950 C G . PASS AF=0.871548 ES:SE:LP:AF:SS:ID -0.000252492:0.000749679:0.132965:0.871548:360270:rs3131950
1 762601 rs3131949 T C . PASS AF=0.871547 ES:SE:LP:AF:SS:ID -0.000253331:0.000749693:0.133459:0.871547:360270:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871922 ES:SE:LP:AF:SS:ID -0.000248813:0.000750122:0.130698:0.871922:360270:rs3131948
1 764191 rs7515915 T G . PASS AF=0.12557 ES:SE:LP:AF:SS:ID 0.000259037:0.000750702:0.136647:0.12557:360270:rs7515915
1 766007 rs61768174 A C . PASS AF=0.105413 ES:SE:LP:AF:SS:ID 5.3827e-06:0.000817309:0.00228824:0.105413:360270:rs61768174
1 766105 rs2519015 T A . PASS AF=0.855359 ES:SE:LP:AF:SS:ID -0.000551719:0.000733667:0.344814:0.855359:360270:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00165156 ES:SE:LP:AF:SS:ID -0.00724827:0.00650606:0.576353:0.00165156:360270:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.838382 ES:SE:LP:AF:SS:ID -0.00141905:0.000722944:1.30398:0.838382:360270:rs376645387