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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-22607_1/ukb-d-22607_1.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-22607_1/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 16:36:59 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22607_1/ukb-d-22607_1.vcf.gz ...
Read summary statistics for 13566906 SNPs.
Dropped 12682 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: 0.0466 (0.0059)
Lambda GC: 1.0844
Mean Chi^2: 1.0865
Intercept: 1.0043 (0.0068)
Ratio: 0.0499 (0.0791)
Analysis finished at Mon Nov 25 16:39:17 2019
Total time elapsed: 2.0m:17.93s
{
"af_correlation": 0.9521,
"inflation_factor": 1.0521,
"mean_EFFECT": 0.0001,
"n": 90145,
"n_snps": 13566906,
"n_clumped_hits": 1,
"n_p_sig": 36,
"n_mono": 0,
"n_ns": 1251222,
"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": 563168,
"n_est": 90469.0032,
"ratio_se_n": 1.0018,
"mean_diff": 0.0001,
"ratio_diff": 82.2084,
"sd_y_est1": 0.4996,
"sd_y_est2": 0.5005,
"r2_sum1": 0.0001,
"r2_sum2": 0.0004,
"r2_sum3": 0.0004,
"r2_sum4": 0.0004,
"ldsc_nsnp_merge_refpanel_ld": 1283504,
"ldsc_nsnp_merge_regression_ld": 1283504,
"ldsc_observed_scale_h2_beta": 0.0466,
"ldsc_observed_scale_h2_se": 0.0059,
"ldsc_intercept_beta": 1.0043,
"ldsc_intercept_se": 0.0068,
"ldsc_lambda_gc": 1.0844,
"ldsc_mean_chisq": 1.0865,
"ldsc_ratio": 0.0497
}
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 | FALSE |
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 | 13554888 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 57046 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33331 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.051311e+00 | 6.184953e+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 | 7.902483e+07 | 5.591673e+07 | 3.02000e+02 | 3.292761e+07 | 7.013477e+07 | 1.148626e+08 | 2.492309e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 6.620000e-05 | 1.373090e-02 | -1.62547e-01 | -3.690200e-03 | 2.670000e-05 | 3.777000e-03 | 1.627730e-01 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.847300e-03 | 9.489900e-03 | 1.94110e-03 | 2.813400e-03 | 5.175100e-03 | 1.413970e-02 | 4.773580e-02 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.918584e-01 | 2.909521e-01 | 0.00000e+00 | 2.374029e-01 | 4.890475e-01 | 7.440412e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.918566e-01 | 2.909531e-01 | 0.00000e+00 | 2.373996e-01 | 4.890460e-01 | 7.440412e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.910656e-01 | 2.544726e-01 | 1.00000e-03 | 7.499100e-03 | 6.029750e-02 | 2.957600e-01 | 9.990000e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 563168 | 0.9584896 | NA | NA | NA | NA | NA | 1.965220e-01 | 2.471439e-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 | 9.014500e+04 | 0.000000e+00 | 9.01450e+04 | 9.014500e+04 | 9.014500e+04 | 9.014500e+04 | 9.014500e+04 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | 0.0026658 | 0.0041108 | 0.5166709 | 0.5166691 | 0.1113110 | 0.1894970 | 90145 |
1 | 693731 | rs12238997 | A | G | 0.0035140 | 0.0038928 | 0.3666942 | 0.3666900 | 0.1162900 | 0.1417730 | 90145 |
1 | 707522 | rs371890604 | G | C | 0.0009390 | 0.0043748 | 0.8300440 | 0.8300429 | 0.0977515 | 0.1293930 | 90145 |
1 | 717587 | rs144155419 | G | A | -0.0077200 | 0.0104408 | 0.4596603 | 0.4596582 | 0.0157464 | 0.0045926 | 90145 |
1 | 723329 | rs189787166 | A | T | 0.0216604 | 0.0306324 | 0.4795015 | 0.4794997 | 0.0017529 | 0.0003994 | 90145 |
1 | 730087 | rs148120343 | T | C | 0.0026534 | 0.0053990 | 0.6231075 | 0.6231067 | 0.0568458 | 0.0127796 | 90145 |
1 | 731718 | rs142557973 | T | C | 0.0011840 | 0.0036943 | 0.7485848 | 0.7485839 | 0.1221550 | 0.1543530 | 90145 |
1 | 732032 | rs61770163 | A | C | 0.0016729 | 0.0039395 | 0.6710904 | 0.6710892 | 0.1218610 | 0.1555510 | 90145 |
1 | 734349 | rs141242758 | T | C | 0.0012153 | 0.0036972 | 0.7423693 | 0.7423674 | 0.1213840 | 0.1525560 | 90145 |
1 | 740284 | rs61770167 | C | T | -0.0034243 | 0.0169369 | 0.8397749 | 0.8397752 | 0.0057634 | 0.0023962 | 90145 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0023582 | 0.0043188 | 0.5850446 | 0.5850430 | 0.0553120 | 0.0309934 | 90145 |
23 | 154923374 | rs111332691 | T | A | 0.0045979 | 0.0047003 | 0.3279676 | 0.3279654 | 0.0448888 | 0.0116556 | 90145 |
23 | 154925045 | rs509981 | C | T | -0.0017436 | 0.0022649 | 0.4413986 | 0.4413958 | 0.2445900 | 0.3634440 | 90145 |
23 | 154925895 | rs538470 | C | T | -0.0015016 | 0.0023155 | 0.5166733 | 0.5166705 | 0.2410980 | 0.3634440 | 90145 |
23 | 154927581 | rs644138 | G | A | -0.0009795 | 0.0021305 | 0.6456795 | 0.6456798 | 0.3003080 | 0.4635760 | 90145 |
23 | 154929412 | rs557132 | C | T | -0.0018191 | 0.0022656 | 0.4220141 | 0.4220117 | 0.2444460 | 0.3568210 | 90145 |
23 | 154929637 | rs35185538 | CT | C | -0.0019511 | 0.0023658 | 0.4095520 | 0.4095511 | 0.2288140 | 0.3011920 | 90145 |
23 | 154929952 | rs4012982 | CAA | C | -0.0022591 | 0.0023846 | 0.3434488 | 0.3434460 | 0.2383540 | 0.3165560 | 90145 |
23 | 154930230 | rs781880 | A | G | -0.0018389 | 0.0022648 | 0.4168348 | 0.4168327 | 0.2449110 | 0.3618540 | 90145 |
23 | 154930487 | rs781879 | T | A | -0.0070286 | 0.0076820 | 0.3602260 | 0.3602232 | 0.0196680 | 0.1263580 | 90145 |
1 692794 rs530212009 CA C . PASS AF=0.111311 ES:SE:LP:AF:SS:ID 0.00266578:0.00411076:0.286786:0.111311:90145:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.11629 ES:SE:LP:AF:SS:ID 0.00351395:0.00389275:0.435696:0.11629:90145:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0977515 ES:SE:LP:AF:SS:ID 0.000939038:0.00437481:0.0808989:0.0977515:90145:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0157464 ES:SE:LP:AF:SS:ID -0.00772003:0.0104408:0.337563:0.0157464:90145:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00175286 ES:SE:LP:AF:SS:ID 0.0216604:0.0306324:0.31921:0.00175286:90145:rs189787166
1 730087 rs148120343 T C . PASS AF=0.0568458 ES:SE:LP:AF:SS:ID 0.00265336:0.00539902:0.205437:0.0568458:90145:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122155 ES:SE:LP:AF:SS:ID 0.00118404:0.00369427:0.125759:0.122155:90145:rs58276399
1 732032 rs61770163 A C . PASS AF=0.121861 ES:SE:LP:AF:SS:ID 0.00167294:0.00393954:0.173219:0.121861:90145:rs61770163
1 734349 rs141242758 T C . PASS AF=0.121384 ES:SE:LP:AF:SS:ID 0.00121533:0.00369716:0.12938:0.121384:90145:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00576344 ES:SE:LP:AF:SS:ID -0.00342432:0.0169369:0.0758371:0.00576344:90145:rs61770167
1 742813 rs112573343 C T . PASS AF=0.00181816 ES:SE:LP:AF:SS:ID -0.0337165:0.0324798:0.523985:0.00181816:90145:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.869117 ES:SE:LP:AF:SS:ID -0.00152738:0.0036372:0.170994:0.869117:90145:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00159834 ES:SE:LP:AF:SS:ID 0.0267542:0.0321471:0.39225:0.00159834:90145:rs190826124
1 751343 rs28544273 T A . PASS AF=0.123502 ES:SE:LP:AF:SS:ID 0.00131863:0.00360586:0.145939:0.123502:90145:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.143012 ES:SE:LP:AF:SS:ID 0.0033802:0.00356954:0.463867:0.143012:90145:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123637 ES:SE:LP:AF:SS:ID 0.00115397:0.00360064:0.125751:0.123637:90145:rs28527770
1 753405 rs3115860 C A . PASS AF=0.870111 ES:SE:LP:AF:SS:ID -0.00055318:0.0035084:0.0581334:0.870111:90145:rs3115860
1 753425 rs3131970 T C . PASS AF=0.874755 ES:SE:LP:AF:SS:ID -0.000419569:0.00356542:0.0427165:0.874755:90145:rs3131970
1 753541 rs2073813 G A . PASS AF=0.129319 ES:SE:LP:AF:SS:ID 0.00101045:0.00351936:0.111244:0.129319:90145:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0358644 ES:SE:LP:AF:SS:ID 0.0137067:0.00642231:1.48378:0.0358644:90145:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869758 ES:SE:LP:AF:SS:ID -0.00058691:0.00350547:0.0619639:0.869758:90145:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869836 ES:SE:LP:AF:SS:ID -0.000479192:0.00350702:0.0499678:0.869836:90145:rs3131968
1 754334 rs3131967 T C . PASS AF=0.869754 ES:SE:LP:AF:SS:ID -0.000577793:0.00350532:0.0609422:0.869754:90145:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00532358 ES:SE:LP:AF:SS:ID 0.0323348:0.0174825:1.19124:0.00532358:90145:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00528889 ES:SE:LP:AF:SS:ID 0.0324885:0.0175259:1.19532:0.00528889:90145:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00566273 ES:SE:LP:AF:SS:ID -0.0171758:0.0172464:0.495802:0.00566273:90145:rs184270342
1 755890 rs3115858 A T . PASS AF=0.869737 ES:SE:LP:AF:SS:ID -0.000812371:0.00349811:0.0881188:0.869737:90145:rs3115858
1 756434 rs61768170 G C . PASS AF=0.126726 ES:SE:LP:AF:SS:ID 0.00136654:0.00357075:0.1537:0.126726:90145:rs61768170
1 756604 rs3131962 A G . PASS AF=0.869261 ES:SE:LP:AF:SS:ID -0.00123959:0.00348899:0.141237:0.869261:90145:rs3131962
1 757640 rs3115853 G A . PASS AF=0.86865 ES:SE:LP:AF:SS:ID -0.000667148:0.00348675:0.0714705:0.86865:90145:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869414 ES:SE:LP:AF:SS:ID -0.000899525:0.00349218:0.0986888:0.869414:90145:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869419 ES:SE:LP:AF:SS:ID -0.000893619:0.00349242:0.0979704:0.869419:90145:rs4951862
1 758144 rs3131956 A G . PASS AF=0.869421 ES:SE:LP:AF:SS:ID -0.00089542:0.00349244:0.0981865:0.869421:90145:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869904 ES:SE:LP:AF:SS:ID -0.000601731:0.00350182:0.063703:0.869904:90145:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0990489 ES:SE:LP:AF:SS:ID -5.29959e-05:0.00407458:0.00453022:0.0990489:90145:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00650816 ES:SE:LP:AF:SS:ID -0.0249916:0.0157013:0.952885:0.00650816:90145:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.873894 ES:SE:LP:AF:SS:ID -0.000484473:0.00355375:0.049848:0.873894:90145:rs3115851
1 761732 rs2286139 C T . PASS AF=0.863267 ES:SE:LP:AF:SS:ID -0.0011191:0.00348585:0.125994:0.863267:90145:rs2286139
1 761752 rs1057213 C T . PASS AF=0.868697 ES:SE:LP:AF:SS:ID -0.00106472:0.00352042:0.117865:0.868697:90145:rs1057213
1 762273 rs3115849 G A . PASS AF=0.865579 ES:SE:LP:AF:SS:ID -0.000612563:0.00352102:0.0645497:0.865579:90145:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0993705 ES:SE:LP:AF:SS:ID 0.000392339:0.00421421:0.0334711:0.0993705:90145:rs12095200
1 762589 rs3115848 G C . PASS AF=0.870867 ES:SE:LP:AF:SS:ID -0.000706679:0.00356126:0.0743244:0.870867:90145:rs3115848
1 762592 rs3131950 C G . PASS AF=0.870867 ES:SE:LP:AF:SS:ID -0.000707251:0.00356126:0.0743894:0.870867:90145:rs3131950
1 762601 rs3131949 T C . PASS AF=0.870864 ES:SE:LP:AF:SS:ID -0.00070659:0.00356127:0.0743141:0.870864:90145:rs3131949
1 762632 rs3131948 T A . PASS AF=0.87123 ES:SE:LP:AF:SS:ID -0.00101039:0.00356297:0.109728:0.87123:90145:rs3131948
1 764191 rs7515915 T G . PASS AF=0.126315 ES:SE:LP:AF:SS:ID 0.000980789:0.00356682:0.106052:0.126315:90145:rs7515915
1 766007 rs61768174 A C . PASS AF=0.105889 ES:SE:LP:AF:SS:ID 0.00107627:0.0038768:0.107179:0.105889:90145:rs61768174
1 766105 rs2519015 T A . PASS AF=0.854607 ES:SE:LP:AF:SS:ID -0.000757987:0.00348462:0.0820741:0.854607:90145:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00166577 ES:SE:LP:AF:SS:ID 0.016151:0.0307262:0.222474:0.00166577:90145:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.839373 ES:SE:LP:AF:SS:ID -0.00307101:0.00344265:0.429026:0.839373:90145:rs376645387