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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-22660_105/ukb-d-22660_105.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-22660_105/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 14:52:11 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22660_105/ukb-d-22660_105.vcf.gz ...
Read summary statistics for 13560221 SNPs.
Dropped 12671 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: 0.0153 (0.0068)
Lambda GC: 1.0217
Mean Chi^2: 1.0236
Intercept: 1.0032 (0.0061)
Ratio: 0.1354 (0.2587)
Analysis finished at Mon Nov 25 14:54:29 2019
Total time elapsed: 2.0m:18.2s
{
"af_correlation": 0.9521,
"inflation_factor": 1.0052,
"mean_EFFECT": 0,
"n": 67655,
"n_snps": 13560221,
"n_clumped_hits": 1,
"n_p_sig": 2,
"n_mono": 0,
"n_ns": 1250997,
"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": 561552,
"n_est": 67875.8311,
"ratio_se_n": 1.0016,
"mean_diff": 0,
"ratio_diff": 353.8635,
"sd_y_est1": 0.3879,
"sd_y_est2": 0.3885,
"r2_sum1": 0.0001,
"r2_sum2": 0.0005,
"r2_sum3": 0.0005,
"r2_sum4": 0.0005,
"ldsc_nsnp_merge_refpanel_ld": 1283503,
"ldsc_nsnp_merge_regression_ld": 1283503,
"ldsc_observed_scale_h2_beta": 0.0153,
"ldsc_observed_scale_h2_se": 0.0068,
"ldsc_intercept_beta": 1.0032,
"ldsc_intercept_se": 0.0061,
"ldsc_lambda_gc": 1.0217,
"ldsc_mean_chisq": 1.0236,
"ldsc_ratio": 0.1356
}
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 | 13548214 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 57036 | 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 | 9.051468e+00 | 6.185045e+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 | 7.902618e+07 | 5.591720e+07 | 3.02000e+02 | 3.292798e+07 | 7.013588e+07 | 1.148646e+08 | 2.492309e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.610000e-05 | 1.220540e-02 | -1.63966e-01 | -3.254200e-03 | -1.340000e-05 | 3.258400e-03 | 1.532230e-01 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.814800e-03 | 8.492000e-03 | 1.75790e-03 | 2.520700e-03 | 4.633200e-03 | 1.265380e-02 | 4.347500e-02 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.988585e-01 | 2.891642e-01 | 0.00000e+00 | 2.477981e-01 | 4.988925e-01 | 7.492401e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.988562e-01 | 2.891656e-01 | 0.00000e+00 | 2.477937e-01 | 4.988902e-01 | 7.492392e-01 | 9.999999e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.911551e-01 | 2.544950e-01 | 1.00000e-03 | 7.523000e-03 | 6.040290e-02 | 2.959440e-01 | 9.990000e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 561552 | 0.9585883 | NA | NA | NA | NA | NA | 1.965910e-01 | 2.471619e-01 | 0.00000e+00 | 5.790700e-03 | 8.466450e-02 | 3.086090e-01 | 1.000000e+00 | ▇▂▁▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 6.765500e+04 | 0.000000e+00 | 6.76550e+04 | 6.765500e+04 | 6.765500e+04 | 6.765500e+04 | 6.765500e+04 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | -0.0055314 | 0.0036821 | 0.1330430 | 0.1330378 | 0.1113330 | 0.1894970 | 67655 |
1 | 693731 | rs12238997 | A | G | -0.0004489 | 0.0034882 | 0.8975991 | 0.8975990 | 0.1164250 | 0.1417730 | 67655 |
1 | 707522 | rs371890604 | G | C | 0.0030670 | 0.0039218 | 0.4341902 | 0.4341879 | 0.0978617 | 0.1293930 | 67655 |
1 | 717587 | rs144155419 | G | A | -0.0125702 | 0.0093386 | 0.1782900 | 0.1782858 | 0.0157910 | 0.0045926 | 67655 |
1 | 723329 | rs189787166 | A | T | 0.0182969 | 0.0267895 | 0.4946170 | 0.4946146 | 0.0018352 | 0.0003994 | 67655 |
1 | 730087 | rs148120343 | T | C | 0.0018491 | 0.0048379 | 0.7023070 | 0.7023064 | 0.0569430 | 0.0127796 | 67655 |
1 | 731718 | rs142557973 | T | C | 0.0001845 | 0.0033105 | 0.9555519 | 0.9555522 | 0.1223980 | 0.1543530 | 67655 |
1 | 732032 | rs61770163 | A | C | 0.0013699 | 0.0035307 | 0.6980266 | 0.6980251 | 0.1220450 | 0.1555510 | 67655 |
1 | 734349 | rs141242758 | T | C | 0.0003026 | 0.0033130 | 0.9272320 | 0.9272321 | 0.1216050 | 0.1525560 | 67655 |
1 | 740284 | rs61770167 | C | T | -0.0001038 | 0.0153081 | 0.9945920 | 0.9945917 | 0.0056852 | 0.0023962 | 67655 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0026897 | 0.0039489 | 0.4958005 | 0.4957974 | 0.0547784 | 0.0309934 | 67655 |
23 | 154923374 | rs111332691 | T | A | -0.0027186 | 0.0042971 | 0.5269629 | 0.5269610 | 0.0442687 | 0.0116556 | 67655 |
23 | 154925045 | rs509981 | C | T | 0.0006095 | 0.0020513 | 0.7663656 | 0.7663645 | 0.2448950 | 0.3634440 | 67655 |
23 | 154925895 | rs538470 | C | T | 0.0009773 | 0.0020976 | 0.6412804 | 0.6412786 | 0.2412550 | 0.3634440 | 67655 |
23 | 154927581 | rs644138 | G | A | 0.0011819 | 0.0019322 | 0.5407369 | 0.5407338 | 0.3000720 | 0.4635760 | 67655 |
23 | 154929412 | rs557132 | C | T | 0.0006538 | 0.0020520 | 0.7500272 | 0.7500271 | 0.2447530 | 0.3568210 | 67655 |
23 | 154929637 | rs35185538 | CT | C | 0.0012504 | 0.0021435 | 0.5596416 | 0.5596381 | 0.2291340 | 0.3011920 | 67655 |
23 | 154929952 | rs4012982 | CAA | C | 0.0003505 | 0.0021600 | 0.8710849 | 0.8710844 | 0.2385660 | 0.3165560 | 67655 |
23 | 154930230 | rs781880 | A | G | 0.0007587 | 0.0020515 | 0.7115083 | 0.7115079 | 0.2451600 | 0.3618540 | 67655 |
23 | 154930487 | rs781879 | T | A | -0.0076814 | 0.0070216 | 0.2739713 | 0.2739673 | 0.0193551 | 0.1263580 | 67655 |
1 692794 rs530212009 CA C . PASS AF=0.111333 ES:SE:LP:AF:SS:ID -0.00553136:0.0036821:0.876008:0.111333:67655:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.116425 ES:SE:LP:AF:SS:ID -0.000448914:0.0034882:0.0469176:0.116425:67655:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0978617 ES:SE:LP:AF:SS:ID 0.00306701:0.00392178:0.36232:0.0978617:67655:rs371890604
1 717587 rs144155419 G A . PASS AF=0.015791 ES:SE:LP:AF:SS:ID -0.0125702:0.00933857:0.748873:0.015791:67655:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00183518 ES:SE:LP:AF:SS:ID 0.0182969:0.0267895:0.305731:0.00183518:67655:rs189787166
1 730087 rs148120343 T C . PASS AF=0.056943 ES:SE:LP:AF:SS:ID 0.0018491:0.00483793:0.153473:0.056943:67655:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122398 ES:SE:LP:AF:SS:ID 0.000184515:0.00331052:0.0197457:0.122398:67655:rs58276399
1 732032 rs61770163 A C . PASS AF=0.122045 ES:SE:LP:AF:SS:ID 0.00136988:0.00353073:0.156128:0.122045:67655:rs61770163
1 734349 rs141242758 T C . PASS AF=0.121605 ES:SE:LP:AF:SS:ID 0.00030257:0.00331301:0.0328116:0.121605:67655:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00568516 ES:SE:LP:AF:SS:ID -0.000103763:0.0153081:0.00235504:0.00568516:67655:rs61770167
1 742813 rs112573343 C T . PASS AF=0.00185636 ES:SE:LP:AF:SS:ID 0.0268929:0.0287546:0.456354:0.00185636:67655:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.86888 ES:SE:LP:AF:SS:ID 0.00121599:0.00325784:0.149377:0.86888:67655:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00154315 ES:SE:LP:AF:SS:ID 0.0222487:0.0295351:0.345559:0.00154315:67655:rs190826124
1 751343 rs28544273 T A . PASS AF=0.123646 ES:SE:LP:AF:SS:ID -0.0012088:0.00323121:0.149765:0.123646:67655:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.143073 ES:SE:LP:AF:SS:ID -0.00149349:0.00319805:0.19348:0.143073:67655:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123779 ES:SE:LP:AF:SS:ID -0.00115699:0.00322649:0.142727:0.123779:67655:rs28527770
1 753405 rs3115860 C A . PASS AF=0.869863 ES:SE:LP:AF:SS:ID 0.00113387:0.00314343:0.143684:0.869863:67655:rs3115860
1 753425 rs3131970 T C . PASS AF=0.874632 ES:SE:LP:AF:SS:ID 0.000735492:0.00319582:0.0872563:0.874632:67655:rs3131970
1 753541 rs2073813 G A . PASS AF=0.129534 ES:SE:LP:AF:SS:ID -0.00135651:0.00315287:0.175862:0.129534:67655:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0358436 ES:SE:LP:AF:SS:ID -0.00237286:0.00575522:0.167413:0.0358436:67655:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869516 ES:SE:LP:AF:SS:ID 0.00117982:0.00314064:0.150477:0.869516:67655:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869601 ES:SE:LP:AF:SS:ID 0.00110106:0.00314224:0.139042:0.869601:67655:rs3131968
1 754334 rs3131967 T C . PASS AF=0.86951 ES:SE:LP:AF:SS:ID 0.00117358:0.00314049:0.149578:0.86951:67655:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00535705 ES:SE:LP:AF:SS:ID 0.000880985:0.0156432:0.0199562:0.00535705:67655:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00532268 ES:SE:LP:AF:SS:ID 0.000113579:0.0156827:0.00251663:0.00532268:67655:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00587606 ES:SE:LP:AF:SS:ID -0.000849079:0.0151092:0.0199121:0.00587606:67655:rs184270342
1 755890 rs3115858 A T . PASS AF=0.869521 ES:SE:LP:AF:SS:ID 0.000856342:0.00313451:0.105295:0.869521:67655:rs3115858
1 756434 rs61768170 G C . PASS AF=0.126879 ES:SE:LP:AF:SS:ID -0.00123138:0.00319939:0.154699:0.126879:67655:rs61768170
1 756604 rs3131962 A G . PASS AF=0.869086 ES:SE:LP:AF:SS:ID 0.000797182:0.00312656:0.0975908:0.869086:67655:rs3131962
1 757640 rs3115853 G A . PASS AF=0.86843 ES:SE:LP:AF:SS:ID 0.00067475:0.00312326:0.081468:0.86843:67655:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869213 ES:SE:LP:AF:SS:ID 0.000892129:0.00312911:0.110383:0.869213:67655:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869219 ES:SE:LP:AF:SS:ID 0.000888932:0.00312932:0.109936:0.869219:67655:rs4951862
1 758144 rs3131956 A G . PASS AF=0.869221 ES:SE:LP:AF:SS:ID 0.000893224:0.00312934:0.110523:0.869221:67655:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869661 ES:SE:LP:AF:SS:ID 0.000757389:0.00313748:0.0919194:0.869661:67655:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0991549 ES:SE:LP:AF:SS:ID 0.00252048:0.00365251:0.309668:0.0991549:67655:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00672466 ES:SE:LP:AF:SS:ID 0.000279525:0.013775:0.00708877:0.00672466:67655:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.873693 ES:SE:LP:AF:SS:ID 0.00115636:0.00318374:0.144815:0.873693:67655:rs3115851
1 761732 rs2286139 C T . PASS AF=0.86311 ES:SE:LP:AF:SS:ID 0.00129343:0.00312265:0.168307:0.86311:67655:rs2286139
1 761752 rs1057213 C T . PASS AF=0.868459 ES:SE:LP:AF:SS:ID 0.00160088:0.0031542:0.213407:0.868459:67655:rs1057213
1 762273 rs3115849 G A . PASS AF=0.865449 ES:SE:LP:AF:SS:ID 0.00190546:0.00315441:0.262963:0.865449:67655:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0996966 ES:SE:LP:AF:SS:ID -0.000457682:0.00377179:0.0441108:0.0996966:67655:rs12095200
1 762589 rs3115848 G C . PASS AF=0.870704 ES:SE:LP:AF:SS:ID 0.00154277:0.00319048:0.201553:0.870704:67655:rs3115848
1 762592 rs3131950 C G . PASS AF=0.870704 ES:SE:LP:AF:SS:ID 0.00154237:0.00319048:0.201492:0.870704:67655:rs3131950
1 762601 rs3131949 T C . PASS AF=0.870702 ES:SE:LP:AF:SS:ID 0.0015424:0.00319049:0.201496:0.870702:67655:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871042 ES:SE:LP:AF:SS:ID 0.00134328:0.00319201:0.171414:0.871042:67655:rs3131948
1 764191 rs7515915 T G . PASS AF=0.126524 ES:SE:LP:AF:SS:ID -0.00113876:0.00319523:0.141735:0.126524:67655:rs7515915
1 766007 rs61768174 A C . PASS AF=0.105925 ES:SE:LP:AF:SS:ID 8.23118e-05:0.00347736:0.00828008:0.105925:67655:rs61768174
1 766105 rs2519015 T A . PASS AF=0.854403 ES:SE:LP:AF:SS:ID 0.000280332:0.00312127:0.032248:0.854403:67655:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00175177 ES:SE:LP:AF:SS:ID 0.026558:0.0268276:0.491872:0.00175177:67655:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.839355 ES:SE:LP:AF:SS:ID 0.0026932:0.00308298:0.417532:0.839355:67655:rs376645387