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}
*********************************************************************
* 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-4946/ukb-d-4946.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-4946/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 17:20:57 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-4946/ukb-d-4946.vcf.gz ...
Read summary statistics for 13567694 SNPs.
Dropped 12693 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, 1283503 SNPs remain.
After merging with regression SNP LD, 1283503 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0027 (0.0043)
Lambda GC: 1.0047
Mean Chi^2: 1.0035
Intercept: 1.0097 (0.0064)
Ratio: 2.7707 (1.8194)
Analysis finished at Mon Nov 25 17:23:14 2019
Total time elapsed: 2.0m:17.34s
{
"af_correlation": 0.9521,
"inflation_factor": 1.0117,
"mean_EFFECT": -3.6807e-06,
"n": 116869,
"n_snps": 13567694,
"n_clumped_hits": 0,
"n_p_sig": 53,
"n_mono": 0,
"n_ns": 1251202,
"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": 563212,
"n_est": 117338.7748,
"ratio_se_n": 1.002,
"mean_diff": -0,
"ratio_diff": 212.9497,
"sd_y_est1": 0.0901,
"sd_y_est2": 0.0903,
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1283503,
"ldsc_nsnp_merge_regression_ld": 1283503,
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": 1.0097,
"ldsc_intercept_se": 0.0064,
"ldsc_lambda_gc": 1.0047,
"ldsc_mean_chisq": 1.0035,
"ldsc_ratio": 2.7714
}
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 | FALSE |
n_p_sig | FALSE |
miss_EFFECT | FALSE |
miss_SE | FALSE |
miss_PVAL | FALSE |
ldsc_ratio | TRUE |
ldsc_intercept_beta | FALSE |
n_clumped_hits | FALSE |
r2_sum1 | FALSE |
r2_sum2 | FALSE |
r2_sum3 | FALSE |
r2_sum4 | FALSE |
General metrics
af_correlation
: Correlation coefficient between AF
and AF_reference
.inflation_factor
(lambda
): Genomic inflation factor.mean_EFFECT
: Mean of EFFECT
size.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 below 5e-8
.n_mono
: Number of monomorphic (MAF == 1
or MAF == 0
) SNPs.n_ns
: Number of SNPs with nonsense values:
A, C, G or T
.< 0
or > 1
.<= 0
or = Infinity
).< 0
or > 1
.n_mac
: Number of cases where MAC
(\(2 \times N \times MAF\)) is less than 6
.is_snpid_unique
: true
if the combination of ID
REF
ALT
is unique and therefore no duplication in snpid.n_miss_<*>
: Number of NA
observations 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 expect ratio_se_n
to 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.
ratio_diff
: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff
and the mean of diff2
(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.
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.
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.
r2 metrics
Sum of variance explained, calculated from the clumped top hits sample.
r2_sum<*>
: r2
statistics under various assumptions
1
: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).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
: NOT is_snpid_unique
.mean_EFFECT_nonfinite
: mean(EFFECT)
is NA
, NaN
, or Inf
.mean_EFFECT_05
: abs(mean(EFFECT))
> 0.5.mean_EFFECT_01
: abs(mean(EFFECT))
> 0.1.mean_chisq
: ldsc_mean_chisq
> 1.3 or ldsc_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<*>
> 0.5Plots
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 | 13555665 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 57053 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33328 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.051369e+00 | 6.184959e+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 | 7.902512e+07 | 5.591687e+07 | 3.02000e+02 | 3.292864e+07 | 7.013814e+07 | 1.148574e+08 | 2.492309e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -3.700000e-06 | 2.168900e-03 | -3.73049e-02 | -5.441000e-04 | 1.980000e-05 | 6.054000e-04 | 2.777270e-02 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.560100e-03 | 1.503400e-03 | 3.06100e-04 | 4.456000e-04 | 8.197000e-04 | 2.240200e-03 | 7.658800e-03 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.993216e-01 | 2.878092e-01 | 0.00000e+00 | 2.510169e-01 | 4.975033e-01 | 7.483504e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.993203e-01 | 2.878100e-01 | 0.00000e+00 | 2.510152e-01 | 4.975016e-01 | 7.483496e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.910597e-01 | 2.544605e-01 | 1.00000e-03 | 7.506700e-03 | 6.031390e-02 | 2.958250e-01 | 9.990000e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 563212 | 0.9584887 | NA | NA | NA | NA | NA | 1.965112e-01 | 2.471407e-01 | 0.00000e+00 | 5.790700e-03 | 8.446490e-02 | 3.085060e-01 | 1.000000e+00 | ▇▂▁▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.168690e+05 | 0.000000e+00 | 1.16869e+05 | 1.168690e+05 | 1.168690e+05 | 1.168690e+05 | 1.168690e+05 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | 0.0000050 | 0.0006517 | 0.9939220 | 0.9939220 | 0.1115770 | 0.1894970 | 116869 |
1 | 693731 | rs12238997 | A | G | -0.0000166 | 0.0006163 | 0.9785230 | 0.9785231 | 0.1168970 | 0.1417730 | 116869 |
1 | 707522 | rs371890604 | G | C | 0.0002295 | 0.0006916 | 0.7400635 | 0.7400638 | 0.0982501 | 0.1293930 | 116869 |
1 | 717587 | rs144155419 | G | A | -0.0018246 | 0.0016596 | 0.2716008 | 0.2716005 | 0.0157095 | 0.0045926 | 116869 |
1 | 723329 | rs189787166 | A | T | -0.0015435 | 0.0049351 | 0.7544614 | 0.7544619 | 0.0016867 | 0.0003994 | 116869 |
1 | 730087 | rs148120343 | T | C | 0.0010259 | 0.0008594 | 0.2325691 | 0.2325675 | 0.0568845 | 0.0127796 | 116869 |
1 | 731718 | rs142557973 | T | C | -0.0000320 | 0.0005851 | 0.9563950 | 0.9563949 | 0.1227320 | 0.1543530 | 116869 |
1 | 732032 | rs61770163 | A | C | -0.0001109 | 0.0006234 | 0.8588450 | 0.8588450 | 0.1222520 | 0.1555510 | 116869 |
1 | 734349 | rs141242758 | T | C | 0.0000194 | 0.0005855 | 0.9735250 | 0.9735249 | 0.1219430 | 0.1525560 | 116869 |
1 | 740284 | rs61770167 | C | T | -0.0031279 | 0.0026160 | 0.2318291 | 0.2318264 | 0.0060264 | 0.0023962 | 116869 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | -0.0004021 | 0.0006824 | 0.5557136 | 0.5557118 | 0.0550798 | 0.0309934 | 116869 |
23 | 154923374 | rs111332691 | T | A | -0.0005319 | 0.0007467 | 0.4762906 | 0.4762889 | 0.0441092 | 0.0116556 | 116869 |
23 | 154925045 | rs509981 | C | T | -0.0002727 | 0.0003581 | 0.4464183 | 0.4464162 | 0.2437800 | 0.3634440 | 116869 |
23 | 154925895 | rs538470 | C | T | -0.0002347 | 0.0003662 | 0.5214600 | 0.5214594 | 0.2402700 | 0.3634440 | 116869 |
23 | 154927581 | rs644138 | G | A | -0.0003892 | 0.0003368 | 0.2477958 | 0.2477926 | 0.2992680 | 0.4635760 | 116869 |
23 | 154929412 | rs557132 | C | T | -0.0002780 | 0.0003583 | 0.4378224 | 0.4378209 | 0.2436020 | 0.3568210 | 116869 |
23 | 154929637 | rs35185538 | CT | C | -0.0005332 | 0.0003737 | 0.1536399 | 0.1536371 | 0.2275940 | 0.3011920 | 116869 |
23 | 154929952 | rs4012982 | CAA | C | -0.0003054 | 0.0003769 | 0.4178063 | 0.4178052 | 0.2377050 | 0.3165560 | 116869 |
23 | 154930230 | rs781880 | A | G | -0.0002957 | 0.0003582 | 0.4090025 | 0.4090021 | 0.2440820 | 0.3618540 | 116869 |
23 | 154930487 | rs781879 | T | A | 0.0008305 | 0.0012439 | 0.5043604 | 0.5043599 | 0.0190780 | 0.1263580 | 116869 |
1 692794 rs530212009 CA C . PASS AF=0.111577 ES:SE:LP:AF:SS:ID 4.96484e-06:0.000651746:0.0026477:0.111577:116869:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.116897 ES:SE:LP:AF:SS:ID -1.65905e-05:0.000616276:0.00942896:0.116897:116869:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0982501 ES:SE:LP:AF:SS:ID 0.000229458:0.00069162:0.130731:0.0982501:116869:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0157095 ES:SE:LP:AF:SS:ID -0.00182456:0.00165962:0.566069:0.0157095:116869:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00168667 ES:SE:LP:AF:SS:ID -0.0015435:0.00493507:0.122363:0.00168667:116869:rs189787166
1 730087 rs148120343 T C . PASS AF=0.0568845 ES:SE:LP:AF:SS:ID 0.00102594:0.000859411:0.633448:0.0568845:116869:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122732 ES:SE:LP:AF:SS:ID -3.19899e-05:0.000585059:0.0193627:0.122732:116869:rs58276399
1 732032 rs61770163 A C . PASS AF=0.122252 ES:SE:LP:AF:SS:ID -0.000110873:0.000623426:0.0660852:0.122252:116869:rs61770163
1 734349 rs141242758 T C . PASS AF=0.121943 ES:SE:LP:AF:SS:ID 1.943e-05:0.000585457:0.0116529:0.121943:116869:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00602642 ES:SE:LP:AF:SS:ID -0.00312789:0.00261602:0.634832:0.00602642:116869:rs61770167
1 742813 rs112573343 C T . PASS AF=0.00177846 ES:SE:LP:AF:SS:ID -0.00259452:0.00526579:0.206059:0.00177846:116869:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.868711 ES:SE:LP:AF:SS:ID -2.42693e-05:0.000577077:0.0148188:0.868711:116869:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00158247 ES:SE:LP:AF:SS:ID 0.00252278:0.0051241:0.205873:0.00158247:116869:rs190826124
1 751343 rs28544273 T A . PASS AF=0.123857 ES:SE:LP:AF:SS:ID -0.000291011:0.000571652:0.21417:0.123857:116869:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.143426 ES:SE:LP:AF:SS:ID -0.000301815:0.000566206:0.226213:0.143426:116869:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123977 ES:SE:LP:AF:SS:ID -0.000279479:0.00057082:0.204529:0.123977:116869:rs28527770
1 753405 rs3115860 C A . PASS AF=0.869921 ES:SE:LP:AF:SS:ID 4.58697e-05:0.000556033:0.029535:0.869921:116869:rs3115860
1 753425 rs3131970 T C . PASS AF=0.874599 ES:SE:LP:AF:SS:ID 0.000282649:0.000565374:0.209628:0.874599:116869:rs3131970
1 753541 rs2073813 G A . PASS AF=0.129653 ES:SE:LP:AF:SS:ID 2.91979e-07:0.000557267:0.000181573:0.129653:116869:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0366136 ES:SE:LP:AF:SS:ID 0.00133343:0.00100791:0.730837:0.0366136:116869:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869536 ES:SE:LP:AF:SS:ID 3.90955e-05:0.000555493:0.0250777:0.869536:116869:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869655 ES:SE:LP:AF:SS:ID 4.46156e-05:0.000555774:0.0287163:0.869655:116869:rs3131968
1 754334 rs3131967 T C . PASS AF=0.869535 ES:SE:LP:AF:SS:ID 4.03051e-05:0.000555468:0.0258772:0.869535:116869:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00511216 ES:SE:LP:AF:SS:ID -0.0031474:0.00284115:0.571938:0.00511216:116869:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00507941 ES:SE:LP:AF:SS:ID -0.00320761:0.00284863:0.584758:0.00507941:116869:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00550249 ES:SE:LP:AF:SS:ID -0.000372917:0.00277723:0.0490591:0.00550249:116869:rs184270342
1 755890 rs3115858 A T . PASS AF=0.869651 ES:SE:LP:AF:SS:ID 5.78626e-05:0.000554539:0.0376794:0.869651:116869:rs3115858
1 756434 rs61768170 G C . PASS AF=0.126941 ES:SE:LP:AF:SS:ID -8.56556e-05:0.00056582:0.0556782:0.126941:116869:rs61768170
1 756604 rs3131962 A G . PASS AF=0.869238 ES:SE:LP:AF:SS:ID 4.18869e-05:0.000553266:0.0270334:0.869238:116869:rs3131962
1 757640 rs3115853 G A . PASS AF=0.868444 ES:SE:LP:AF:SS:ID 7.04463e-05:0.000552608:0.0464524:0.868444:116869:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869384 ES:SE:LP:AF:SS:ID 5.02967e-05:0.000553708:0.0326285:0.869384:116869:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869391 ES:SE:LP:AF:SS:ID 5.09218e-05:0.000553747:0.0330463:0.869391:116869:rs4951862
1 758144 rs3131956 A G . PASS AF=0.8694 ES:SE:LP:AF:SS:ID 5.05679e-05:0.000553765:0.0328074:0.8694:116869:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869823 ES:SE:LP:AF:SS:ID 7.55575e-05:0.000555172:0.0497598:0.869823:116869:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0997572 ES:SE:LP:AF:SS:ID 0.000256905:0.000643988:0.161184:0.0997572:116869:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00630607 ES:SE:LP:AF:SS:ID 3.70104e-05:0.00252225:0.00511428:0.00630607:116869:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.873735 ES:SE:LP:AF:SS:ID 0.000266895:0.00056356:0.196683:0.873735:116869:rs3115851
1 761732 rs2286139 C T . PASS AF=0.863118 ES:SE:LP:AF:SS:ID -6.53158e-05:0.000552715:0.0429049:0.863118:116869:rs2286139
1 761752 rs1057213 C T . PASS AF=0.868538 ES:SE:LP:AF:SS:ID 8.24264e-05:0.000557977:0.0542553:0.868538:116869:rs1057213
1 762273 rs3115849 G A . PASS AF=0.865299 ES:SE:LP:AF:SS:ID 0.000273971:0.000557932:0.205237:0.865299:116869:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0994223 ES:SE:LP:AF:SS:ID -0.000795295:0.000668959:0.629859:0.0994223:116869:rs12095200
1 762589 rs3115848 G C . PASS AF=0.870538 ES:SE:LP:AF:SS:ID 0.000352406:0.000564329:0.273826:0.870538:116869:rs3115848
1 762592 rs3131950 C G . PASS AF=0.870538 ES:SE:LP:AF:SS:ID 0.000352401:0.000564329:0.273822:0.870538:116869:rs3131950
1 762601 rs3131949 T C . PASS AF=0.870539 ES:SE:LP:AF:SS:ID 0.000352583:0.000564358:0.273977:0.870539:116869:rs3131949
1 762632 rs3131948 T A . PASS AF=0.870932 ES:SE:LP:AF:SS:ID 0.000339978:0.000564676:0.261913:0.870932:116869:rs3131948
1 764191 rs7515915 T G . PASS AF=0.126524 ES:SE:LP:AF:SS:ID -0.000200357:0.000565073:0.140913:0.126524:116869:rs7515915
1 766007 rs61768174 A C . PASS AF=0.106234 ES:SE:LP:AF:SS:ID 0.000368542:0.000614651:0.260604:0.106234:116869:rs61768174
1 766105 rs2519015 T A . PASS AF=0.854461 ES:SE:LP:AF:SS:ID -6.56444e-05:0.000552675:0.0431341:0.854461:116869:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00158591 ES:SE:LP:AF:SS:ID -0.00193984:0.00497282:0.157096:0.00158591:116869:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.837903 ES:SE:LP:AF:SS:ID -0.000179681:0.000543666:0.130168:0.837903:116869:rs376645387