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-2395_1/ukb-d-2395_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-2395_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 16:58:59 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-2395_1/ukb-d-2395_1.vcf.gz ...
Read summary statistics for 13577603 SNPs.
Dropped 12699 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, 1283500 SNPs remain.
After merging with regression SNP LD, 1283500 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1852 (0.0172)
Lambda GC: 1.2805
Mean Chi^2: 1.7499
Intercept: 1.1226 (0.0136)
Ratio: 0.1635 (0.0182)
Analysis finished at Mon Nov 25 17:01:20 2019
Total time elapsed: 2.0m:20.72sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9521,
"inflation_factor": 1.1811,
"mean_EFFECT": -2.8413e-06,
"n": 165649,
"n_snps": 13577603,
"n_clumped_hits": 201,
"n_p_sig": 34771,
"n_mono": 0,
"n_ns": 1251513,
"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": 567212,
"n_est": 167798.3794,
"ratio_se_n": 1.0065,
"mean_diff": -4.6851e-06,
"ratio_diff": 3.2425,
"sd_y_est1": 0.4642,
"sd_y_est2": 0.4672,
"r2_sum1": 0.0234,
"r2_sum2": 0.1085,
"r2_sum3": 0.1071,
"r2_sum4": 0.107,
"ldsc_nsnp_merge_refpanel_ld": 1283500,
"ldsc_nsnp_merge_regression_ld": 1283500,
"ldsc_observed_scale_h2_beta": 0.1852,
"ldsc_observed_scale_h2_se": 0.0172,
"ldsc_intercept_beta": 1.1226,
"ldsc_intercept_se": 0.0136,
"ldsc_lambda_gc": 1.2805,
"ldsc_mean_chisq": 1.7499,
"ldsc_ratio": 0.1635
}
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 | 13565568 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 57071 | 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 | 9.050671e+00 | 6.184566e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | <U+2587><U+2585><U+2585><U+2582><U+2582> |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.902693e+07 | 5.591532e+07 | 3.02000e+02 | 3.292852e+07 | 7.014227e+07 | 1.148620e+08 | 2.492309e+08 | <U+2587><U+2586><U+2585><U+2582><U+2581> |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -2.800000e-06 | 9.835200e-03 | -2.14888e-01 | -2.799700e-03 | -3.900000e-06 | 2.770000e-03 | 1.572090e-01 | <U+2581><U+2581><U+2587><U+2581><U+2581> |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 6.768800e-03 | 6.538000e-03 | 1.14100e-03 | 1.933000e-03 | 3.551900e-03 | 9.703400e-03 | 3.320290e-02 | <U+2587><U+2582><U+2581><U+2581><U+2581> |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.715750e-01 | 2.981373e-01 | 0.00000e+00 | 2.063051e-01 | 4.635430e-01 | 7.301852e-01 | 1.000000e+00 | <U+2587><U+2586><U+2586><U+2586><U+2586> |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.715740e-01 | 2.981378e-01 | 0.00000e+00 | 2.063029e-01 | 4.635421e-01 | 7.301847e-01 | 9.999999e-01 | <U+2587><U+2586><U+2586><U+2586><U+2586> |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.909192e-01 | 2.544310e-01 | 1.00000e-03 | 7.459700e-03 | 6.017310e-02 | 2.955560e-01 | 9.990000e-01 | <U+2587><U+2582><U+2581><U+2581><U+2581> |
| numeric | AF_reference | 567212 | 0.9582244 | NA | NA | NA | NA | NA | 1.964225e-01 | 2.471215e-01 | 0.00000e+00 | 5.591000e-03 | 8.426520e-02 | 3.083070e-01 | 1.000000e+00 | <U+2587><U+2582><U+2581><U+2581><U+2581> |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.656490e+05 | 0.000000e+00 | 1.65649e+05 | 1.656490e+05 | 1.656490e+05 | 1.656490e+05 | 1.656490e+05 | <U+2581><U+2581><U+2587><U+2581><U+2581> |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 692794 | rs530212009 | CA | C | -0.0019366 | 0.0028466 | 0.4963123 | 0.4963105 | 0.1102210 | 0.1894970 | 165649 |
| 1 | 693731 | rs12238997 | A | G | 0.0016236 | 0.0026875 | 0.5457566 | 0.5457551 | 0.1153190 | 0.1417730 | 165649 |
| 1 | 707522 | rs371890604 | G | C | 0.0012530 | 0.0030262 | 0.6788440 | 0.6788441 | 0.0967014 | 0.1293930 | 165649 |
| 1 | 717587 | rs144155419 | G | A | -0.0023697 | 0.0072065 | 0.7422907 | 0.7422901 | 0.0156702 | 0.0045926 | 165649 |
| 1 | 723329 | rs189787166 | A | T | 0.0102796 | 0.0211817 | 0.6274585 | 0.6274595 | 0.0017431 | 0.0003994 | 165649 |
| 1 | 730087 | rs148120343 | T | C | -0.0023448 | 0.0037375 | 0.5304165 | 0.5304146 | 0.0563052 | 0.0127796 | 165649 |
| 1 | 731718 | rs142557973 | T | C | 0.0014596 | 0.0025493 | 0.5669399 | 0.5669389 | 0.1211840 | 0.1543530 | 165649 |
| 1 | 732032 | rs61770163 | A | C | 0.0010585 | 0.0027208 | 0.6972331 | 0.6972336 | 0.1206570 | 0.1555510 | 165649 |
| 1 | 734349 | rs141242758 | T | C | 0.0013146 | 0.0025506 | 0.6062615 | 0.6062597 | 0.1204330 | 0.1525560 | 165649 |
| 1 | 740284 | rs61770167 | C | T | 0.0140315 | 0.0117781 | 0.2335269 | 0.2335275 | 0.0056920 | 0.0023962 | 165649 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154923311 | rs141127553 | C | T | 0.0016141 | 0.0025180 | 0.5214984 | 0.5214982 | 0.0556296 | 0.0309934 | 165649 |
| 23 | 154923374 | rs111332691 | T | A | -0.0039318 | 0.0027692 | 0.1556471 | 0.1556467 | 0.0444253 | 0.0116556 | 165649 |
| 23 | 154925045 | rs509981 | C | T | -0.0004423 | 0.0013281 | 0.7390963 | 0.7390968 | 0.2453180 | 0.3634440 | 165649 |
| 23 | 154925895 | rs538470 | C | T | -0.0007246 | 0.0013578 | 0.5935824 | 0.5935822 | 0.2417900 | 0.3634440 | 165649 |
| 23 | 154927581 | rs644138 | G | A | 0.0000236 | 0.0012488 | 0.9849360 | 0.9849360 | 0.3012970 | 0.4635760 | 165649 |
| 23 | 154929412 | rs557132 | C | T | -0.0004267 | 0.0013285 | 0.7480472 | 0.7480472 | 0.2451720 | 0.3568210 | 165649 |
| 23 | 154929637 | rs35185538 | CT | C | -0.0005970 | 0.0013859 | 0.6666057 | 0.6666048 | 0.2295060 | 0.3011920 | 165649 |
| 23 | 154929952 | rs4012982 | CAA | C | -0.0000770 | 0.0013954 | 0.9559890 | 0.9559890 | 0.2396450 | 0.3165560 | 165649 |
| 23 | 154930230 | rs781880 | A | G | -0.0004457 | 0.0013279 | 0.7371163 | 0.7371156 | 0.2457100 | 0.3618540 | 165649 |
| 23 | 154930487 | rs781879 | T | A | -0.0025680 | 0.0045650 | 0.5737464 | 0.5737459 | 0.0194938 | 0.1263580 | 165649 |
bcf preview
1 692794 rs530212009 CA C . PASS AF=0.110221 ES:SE:LP:AF:SS:ID -0.00193656:0.0028466:0.304245:0.110221:165649:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.115319 ES:SE:LP:AF:SS:ID 0.00162359:0.00268747:0.263001:0.115319:165649:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0967014 ES:SE:LP:AF:SS:ID 0.00125295:0.00302615:0.16823:0.0967014:165649:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0156702 ES:SE:LP:AF:SS:ID -0.00236967:0.00720654:0.129426:0.0156702:165649:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00174314 ES:SE:LP:AF:SS:ID 0.0102796:0.0211817:0.202415:0.00174314:165649:rs189787166
1 730087 rs148120343 T C . PASS AF=0.0563052 ES:SE:LP:AF:SS:ID -0.00234482:0.00373752:0.275383:0.0563052:165649:rs148120343
1 731718 rs58276399 T C . PASS AF=0.121184 ES:SE:LP:AF:SS:ID 0.00145963:0.00254928:0.246463:0.121184:165649:rs58276399
1 732032 rs61770163 A C . PASS AF=0.120657 ES:SE:LP:AF:SS:ID 0.00105854:0.00272078:0.156622:0.120657:165649:rs61770163
1 734349 rs141242758 T C . PASS AF=0.120433 ES:SE:LP:AF:SS:ID 0.00131464:0.00255062:0.21734:0.120433:165649:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00569205 ES:SE:LP:AF:SS:ID 0.0140315:0.0117781:0.631663:0.00569205:165649:rs61770167
1 742813 rs112573343 C T . PASS AF=0.00190824 ES:SE:LP:AF:SS:ID 0.00512094:0.0218626:0.0889463:0.00190824:165649:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.870223 ES:SE:LP:AF:SS:ID -0.000203633:0.00251576:0.0289622:0.870223:165649:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00155958 ES:SE:LP:AF:SS:ID 0.00376838:0.0224568:0.0621132:0.00155958:165649:rs190826124
1 751343 rs28544273 T A . PASS AF=0.122448 ES:SE:LP:AF:SS:ID 0.00122773:0.00249021:0.206211:0.122448:165649:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.142093 ES:SE:LP:AF:SS:ID 0.000844831:0.00246254:0.135759:0.142093:165649:rs200141114
1 751756 rs28527770 T C . PASS AF=0.122568 ES:SE:LP:AF:SS:ID 0.00128025:0.00248668:0.217052:0.122568:165649:rs28527770
1 753405 rs3115860 C A . PASS AF=0.871403 ES:SE:LP:AF:SS:ID -0.00136219:0.00242288:0.241114:0.871403:165649:rs3115860
1 753425 rs3131970 T C . PASS AF=0.875954 ES:SE:LP:AF:SS:ID -0.00181045:0.00246274:0.335117:0.875954:165649:rs3131970
1 753541 rs2073813 G A . PASS AF=0.128126 ES:SE:LP:AF:SS:ID 0.00114179:0.00242882:0.194985:0.128126:165649:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0365441 ES:SE:LP:AF:SS:ID -0.00377564:0.00438516:0.409786:0.0365441:165649:rs12184325
1 754182 rs3131969 A G . PASS AF=0.870999 ES:SE:LP:AF:SS:ID -0.00132694:0.00241996:0.233985:0.870999:165649:rs3131969
1 754192 rs3131968 A G . PASS AF=0.871137 ES:SE:LP:AF:SS:ID -0.00148813:0.00242123:0.268564:0.871137:165649:rs3131968
1 754334 rs3131967 T C . PASS AF=0.870997 ES:SE:LP:AF:SS:ID -0.00133288:0.00241991:0.235246:0.870997:165649:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00504652 ES:SE:LP:AF:SS:ID 0.0033972:0.0123806:0.105806:0.00504652:165649:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00501043 ES:SE:LP:AF:SS:ID 0.00392668:0.0124149:0.123906:0.00501043:165649:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00549874 ES:SE:LP:AF:SS:ID -0.0151147:0.0120981:0.674605:0.00549874:165649:rs184270342
1 755890 rs3115858 A T . PASS AF=0.871069 ES:SE:LP:AF:SS:ID -0.00136351:0.00241607:0.242212:0.871069:165649:rs3115858
1 756434 rs61768170 G C . PASS AF=0.125451 ES:SE:LP:AF:SS:ID 0.000923268:0.00246565:0.149924:0.125451:165649:rs61768170
1 756604 rs3131962 A G . PASS AF=0.87063 ES:SE:LP:AF:SS:ID -0.00126833:0.00241018:0.222773:0.87063:165649:rs3131962
1 757640 rs3115853 G A . PASS AF=0.869889 ES:SE:LP:AF:SS:ID -0.00117624:0.00240722:0.204047:0.869889:165649:rs3115853
1 757734 rs4951929 C T . PASS AF=0.870787 ES:SE:LP:AF:SS:ID -0.00136809:0.00241231:0.243647:0.870787:165649:rs4951929
1 757936 rs4951862 C A . PASS AF=0.870794 ES:SE:LP:AF:SS:ID -0.00136758:0.00241249:0.243516:0.870794:165649:rs4951862
1 758144 rs3131956 A G . PASS AF=0.870802 ES:SE:LP:AF:SS:ID -0.00134552:0.00241257:0.238793:0.870802:165649:rs3131956
1 758626 rs3131954 C T . PASS AF=0.871255 ES:SE:LP:AF:SS:ID -0.00142409:0.00241881:0.254906:0.871255:165649:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0982061 ES:SE:LP:AF:SS:ID 0.00217136:0.00281478:0.35609:0.0982061:165649:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00635021 ES:SE:LP:AF:SS:ID -0.0110659:0.010969:0.504379:0.00635021:165649:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.875183 ES:SE:LP:AF:SS:ID -0.00157854:0.00245538:0.28375:0.875183:165649:rs3115851
1 761732 rs2286139 C T . PASS AF=0.864437 ES:SE:LP:AF:SS:ID -0.00113593:0.00240595:0.195974:0.864437:165649:rs2286139
1 761752 rs1057213 C T . PASS AF=0.86997 ES:SE:LP:AF:SS:ID -0.00157045:0.00243092:0.285451:0.86997:165649:rs1057213
1 762273 rs3115849 G A . PASS AF=0.866938 ES:SE:LP:AF:SS:ID -0.0014375:0.00243108:0.25624:0.866938:165649:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0981256 ES:SE:LP:AF:SS:ID 0.00201886:0.00291652:0.310866:0.0981256:165649:rs12095200
1 762589 rs3115848 G C . PASS AF=0.872084 ES:SE:LP:AF:SS:ID -0.00193163:0.00245871:0.364429:0.872084:165649:rs3115848
1 762592 rs3131950 C G . PASS AF=0.872084 ES:SE:LP:AF:SS:ID -0.00193112:0.00245871:0.364306:0.872084:165649:rs3131950
1 762601 rs3131949 T C . PASS AF=0.872085 ES:SE:LP:AF:SS:ID -0.00191808:0.0024588:0.361171:0.872085:165649:rs3131949
1 762632 rs3131948 T A . PASS AF=0.872437 ES:SE:LP:AF:SS:ID -0.00169548:0.00246036:0.309141:0.872437:165649:rs3131948
1 764191 rs7515915 T G . PASS AF=0.125007 ES:SE:LP:AF:SS:ID 0.00139241:0.00246293:0.242728:0.125007:165649:rs7515915
1 766007 rs61768174 A C . PASS AF=0.104884 ES:SE:LP:AF:SS:ID 0.00123197:0.00268195:0.189781:0.104884:165649:rs61768174
1 766105 rs2519015 T A . PASS AF=0.856009 ES:SE:LP:AF:SS:ID -0.00277836:0.00240748:0.604709:0.856009:165649:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00166081 ES:SE:LP:AF:SS:ID 0.0146499:0.021229:0.30968:0.00166081:165649:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.838158 ES:SE:LP:AF:SS:ID 0.00205884:0.00236055:0.416678:0.838158:165649:rs376645387