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-a-import/processed/ukb-a-328/ukb-a-328.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-a-import/processed/ukb-a-328/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Sun Feb 16 01:57:48 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-a-import/processed/ukb-a-328/ukb-a-328.vcf.gz ...
Read summary statistics for 10877936 SNPs.
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, 1281483 SNPs remain.
After merging with regression SNP LD, 1281483 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0963 (0.0102)
Lambda GC: 1.1315
Mean Chi^2: 1.1528
Intercept: 1.0054 (0.0066)
Ratio: 0.0352 (0.0435)
Analysis finished at Sun Feb 16 01:59:33 2020
Total time elapsed: 1.0m:45.66sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9533,
"inflation_factor": 1.0809,
"mean_EFFECT": 5.1915e-06,
"n": 78291,
"n_snps": 10877936,
"n_clumped_hits": 3,
"n_p_sig": 796,
"n_mono": 0,
"n_ns": 0,
"n_mac": 0,
"is_snpid_unique": true,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 356865,
"n_est": 78135.9275,
"ratio_se_n": 0.999,
"mean_diff": 3.354e-06,
"ratio_diff": 1.3289,
"sd_y_est1": 0.863,
"sd_y_est2": 0.8621,
"r2_sum1": 0.0049,
"r2_sum2": 0.0066,
"r2_sum3": 0.0066,
"r2_sum4": 0.0067,
"ldsc_nsnp_merge_refpanel_ld": 1281483,
"ldsc_nsnp_merge_regression_ld": 1281483,
"ldsc_observed_scale_h2_beta": 0.0963,
"ldsc_observed_scale_h2_se": 0.0102,
"ldsc_intercept_beta": 1.0054,
"ldsc_intercept_se": 0.0066,
"ldsc_lambda_gc": 1.1315,
"ldsc_mean_chisq": 1.1528,
"ldsc_ratio": 0.0353
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | FALSE |
| is_snpid_non_unique | FALSE |
| 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 |
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 | 58 | 0 | 10877936 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.598638e+00 | 5.745666e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▃▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.911383e+07 | 5.624931e+07 | 8.28000e+02 | 3.287294e+07 | 6.988889e+07 | 1.148258e+08 | 2.492251e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.200000e-06 | 2.609440e-02 | -3.82324e-01 | -7.277600e-03 | 2.920000e-05 | 7.335200e-03 | 3.311410e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.880360e-02 | 1.783510e-02 | 4.30580e-03 | 5.324400e-03 | 1.022300e-02 | 2.733110e-02 | 1.015730e-01 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.873371e-01 | 2.918657e-01 | 0.00000e+00 | 2.313540e-01 | 4.831556e-01 | 7.402612e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.873350e-01 | 2.918669e-01 | 0.00000e+00 | 2.313509e-01 | 4.831537e-01 | 7.402609e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.820865e-01 | 2.503832e-01 | 1.00090e-03 | 6.878700e-03 | 5.191440e-02 | 2.739880e-01 | 9.989990e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 356865 | 0.9671937 | NA | NA | NA | NA | NA | 1.877709e-01 | 2.439191e-01 | 0.00000e+00 | 5.191700e-03 | 7.468050e-02 | 2.873400e-01 | 1.000000e+00 | ▇▂▁▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.829100e+04 | 0.000000e+00 | 7.82910e+04 | 7.829100e+04 | 7.829100e+04 | 7.829100e+04 | 7.829100e+04 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 693731 | rs12238997 | A | G | 0.0046257 | 0.0072134 | 0.5213519 | 0.5213504 | 0.1169260 | 0.1417730 | 78291 |
| 1 | 717587 | rs144155419 | G | A | 0.0111403 | 0.0192058 | 0.5618844 | 0.5618818 | 0.0143862 | 0.0045926 | 78291 |
| 1 | 730087 | rs148120343 | T | C | -0.0023942 | 0.0101141 | 0.8128739 | 0.8128740 | 0.0554733 | 0.0127796 | 78291 |
| 1 | 731718 | rs142557973 | T | C | 0.0033955 | 0.0068303 | 0.6191074 | 0.6191069 | 0.1216580 | 0.1543530 | 78291 |
| 1 | 734349 | rs141242758 | T | C | 0.0032951 | 0.0068357 | 0.6297744 | 0.6297740 | 0.1215130 | 0.1525560 | 78291 |
| 1 | 740284 | rs61770167 | C | T | -0.0136474 | 0.0305476 | 0.6550523 | 0.6550494 | 0.0058556 | 0.0023962 | 78291 |
| 1 | 742813 | rs112573343 | C | T | -0.0276303 | 0.0594323 | 0.6420014 | 0.6420004 | 0.0015525 | 0.1030350 | 78291 |
| 1 | 753405 | rs3115860 | C | A | -0.0028071 | 0.0064910 | 0.6654064 | 0.6654062 | 0.8706760 | 0.7517970 | 78291 |
| 1 | 753541 | rs2073813 | G | A | 0.0029477 | 0.0065058 | 0.6504891 | 0.6504880 | 0.1288330 | 0.3019170 | 78291 |
| 1 | 754182 | rs3131969 | A | G | -0.0026647 | 0.0064830 | 0.6810500 | 0.6810492 | 0.8703180 | 0.6785140 | 78291 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51219387 | rs9616832 | T | C | -0.0038618 | 0.0083628 | 0.6442345 | 0.6442334 | 0.0729806 | 0.0654952 | 78291 |
| 22 | 51219704 | rs147475742 | G | A | -0.0179232 | 0.0112350 | 0.1106481 | 0.1106451 | 0.0418225 | 0.0473243 | 78291 |
| 22 | 51219766 | rs182321900 | C | T | -0.2046130 | 0.0608221 | 0.0007683 | 0.0007679 | 0.0014546 | NA | 78291 |
| 22 | 51220088 | rs566371895 | G | A | -0.0459691 | 0.0390695 | 0.2393602 | 0.2393560 | 0.0039843 | 0.0003994 | 78291 |
| 22 | 51220146 | rs868950473 | C | T | -0.2164280 | 0.0604731 | 0.0003452 | 0.0003450 | 0.0015139 | NA | 78291 |
| 22 | 51221731 | rs115055839 | T | C | -0.0044444 | 0.0083680 | 0.5953358 | 0.5953345 | 0.0728101 | 0.0625000 | 78291 |
| 22 | 51223637 | rs375798137 | G | A | -0.0112326 | 0.0098768 | 0.2554289 | 0.2554245 | 0.0540289 | 0.0788738 | 78291 |
| 22 | 51226692 | rs150189434 | G | A | -0.1992080 | 0.0626387 | 0.0014719 | 0.0014714 | 0.0013983 | 0.0155751 | 78291 |
| 22 | 51229805 | rs9616985 | T | C | -0.0050786 | 0.0083970 | 0.5453082 | 0.5453062 | 0.0727671 | 0.0730831 | 78291 |
| 22 | 51237063 | rs3896457 | T | C | -0.0039383 | 0.0051166 | 0.4414739 | 0.4414723 | 0.2968410 | 0.2050720 | 78291 |
bcf preview
1 693731 rs12238997 A G . PASS AF=0.116926 ES:SE:LP:AF:SS:ID 0.00462567:0.00721335:0.282869:0.116926:78291:rs12238997
1 717587 rs144155419 G A . PASS AF=0.0143862 ES:SE:LP:AF:SS:ID 0.0111403:0.0192058:0.250353:0.0143862:78291:rs144155419
1 730087 rs148120343 T C . PASS AF=0.0554733 ES:SE:LP:AF:SS:ID -0.00239421:0.0101141:0.0899768:0.0554733:78291:rs148120343
1 731718 rs58276399 T C . PASS AF=0.121658 ES:SE:LP:AF:SS:ID 0.00339546:0.00683031:0.208234:0.121658:78291:rs58276399
1 734349 rs141242758 T C . PASS AF=0.121513 ES:SE:LP:AF:SS:ID 0.0032951:0.00683567:0.200815:0.121513:78291:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00585559 ES:SE:LP:AF:SS:ID -0.0136474:0.0305476:0.183724:0.00585559:78291:rs61770167
1 742813 rs112573343 C T . PASS AF=0.0015525 ES:SE:LP:AF:SS:ID -0.0276303:0.0594323:0.192464:0.0015525:78291:rs112573343
1 753405 rs3115860 C A . PASS AF=0.870676 ES:SE:LP:AF:SS:ID -0.00280711:0.00649101:0.176913:0.870676:78291:rs3115860
1 753541 rs2073813 G A . PASS AF=0.128833 ES:SE:LP:AF:SS:ID 0.00294769:0.00650583:0.18676:0.128833:78291:rs2073813
1 754182 rs3131969 A G . PASS AF=0.870318 ES:SE:LP:AF:SS:ID -0.00266474:0.00648305:0.166821:0.870318:78291:rs3131969
1 754192 rs3131968 A G . PASS AF=0.870409 ES:SE:LP:AF:SS:ID -0.00269906:0.00648614:0.169207:0.870409:78291:rs3131968
1 754334 rs3131967 T C . PASS AF=0.870037 ES:SE:LP:AF:SS:ID -0.00264608:0.00648305:0.165476:0.870037:78291:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00465304 ES:SE:LP:AF:SS:ID 0.0473669:0.0334331:0.805333:0.00465304:78291:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00464711 ES:SE:LP:AF:SS:ID 0.0457683:0.0335245:0.763997:0.00464711:78291:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00590897 ES:SE:LP:AF:SS:ID -0.00421508:0.0326676:0.0470454:0.00590897:78291:rs184270342
1 755890 rs3115858 A T . PASS AF=0.870329 ES:SE:LP:AF:SS:ID -0.00250135:0.00647239:0.155427:0.870329:78291:rs3115858
1 756604 rs3131962 A G . PASS AF=0.87002 ES:SE:LP:AF:SS:ID -0.00258052:0.00645412:0.161601:0.87002:78291:rs3131962
1 757640 rs3115853 G A . PASS AF=0.869421 ES:SE:LP:AF:SS:ID -0.00235747:0.00645067:0.145835:0.869421:78291:rs3115853
1 757734 rs4951929 C T . PASS AF=0.870219 ES:SE:LP:AF:SS:ID -0.0024391:0.00646121:0.151316:0.870219:78291:rs4951929
1 757936 rs4951862 C A . PASS AF=0.870219 ES:SE:LP:AF:SS:ID -0.00241519:0.00646169:0.149614:0.870219:78291:rs4951862
1 758144 rs3131956 A G . PASS AF=0.870222 ES:SE:LP:AF:SS:ID -0.0024735:0.00646187:0.153736:0.870222:78291:rs3131956
1 758626 rs3131954 C T . PASS AF=0.870396 ES:SE:LP:AF:SS:ID -0.00267752:0.00647969:0.167843:0.870396:78291:rs3131954
1 761732 rs2286139 C T . PASS AF=0.867743 ES:SE:LP:AF:SS:ID -0.00183257:0.00645256:0.109911:0.867743:78291:rs2286139
1 766007 rs61768174 A C . PASS AF=0.106958 ES:SE:LP:AF:SS:ID -0.000373505:0.00718392:0.018392:0.106958:78291:rs61768174
1 768253 rs2977608 A C . PASS AF=0.763932 ES:SE:LP:AF:SS:ID -0.00160318:0.00511419:0.122675:0.763932:78291:rs2977608
1 768448 rs12562034 G A . PASS AF=0.105257 ES:SE:LP:AF:SS:ID 5.05082e-05:0.0070269:0.00249785:0.105257:78291:rs12562034
1 768819 rs12562811 C T . PASS AF=0.00692766 ES:SE:LP:AF:SS:ID -0.00652686:0.0256252:0.0974793:0.00692766:78291:rs12562811
1 769223 rs60320384 C G . PASS AF=0.128651 ES:SE:LP:AF:SS:ID 0.00230727:0.00649686:0.141169:0.128651:78291:rs60320384
1 769224 rs141644775 G A . PASS AF=0.00143239 ES:SE:LP:AF:SS:ID -0.0731448:0.0616582:0.627991:0.00143239:78291:rs141644775
1 770181 rs146076599 A G . PASS AF=0.00907328 ES:SE:LP:AF:SS:ID -0.00800917:0.0251618:0.124792:0.00907328:78291:rs146076599
1 770377 rs112563271 A T . PASS AF=0.00692321 ES:SE:LP:AF:SS:ID -0.00427008:0.0257212:0.0614072:0.00692321:78291:rs112563271
1 771823 rs2977605 T C . PASS AF=0.869934 ES:SE:LP:AF:SS:ID -0.00148342:0.00646569:0.0869622:0.869934:78291:rs2977605
1 771967 rs59066358 G A . PASS AF=0.128709 ES:SE:LP:AF:SS:ID 0.0019988:0.0064919:0.120236:0.128709:78291:rs59066358
1 772755 rs2905039 A C . PASS AF=0.870112 ES:SE:LP:AF:SS:ID -0.0013764:0.0064666:0.0801654:0.870112:78291:rs2905039
1 774736 rs28830877 A C . PASS AF=0.998797 ES:SE:LP:AF:SS:ID 0.012958:0.0679095:0.0712601:0.998797:78291:rs28830877
1 776556 rs151160018 C T . PASS AF=0.00851871 ES:SE:LP:AF:SS:ID 0.00682351:0.0244301:0.1079:0.00851871:78291:rs151160018
1 777122 rs2980319 A T . PASS AF=0.871122 ES:SE:LP:AF:SS:ID -0.00189769:0.00647881:0.113738:0.871122:78291:rs2980319
1 777232 rs112618790 C T . PASS AF=0.0961319 ES:SE:LP:AF:SS:ID 0.00253875:0.00745312:0.134669:0.0961319:78291:rs112618790
1 778745 rs1055606 A G . PASS AF=0.127871 ES:SE:LP:AF:SS:ID 0.0021658:0.00650103:0.131341:0.127871:78291:rs1055606
1 779322 rs4040617 A G . PASS AF=0.127984 ES:SE:LP:AF:SS:ID 0.0015731:0.00649187:0.0923012:0.127984:78291:rs4040617
1 780785 rs2977612 T A . PASS AF=0.870455 ES:SE:LP:AF:SS:ID -0.00179494:0.00646831:0.107127:0.870455:78291:rs2977612
1 781367 rs149821290 A C . PASS AF=0.00989772 ES:SE:LP:AF:SS:ID 0.0144537:0.0230988:0.274503:0.00989772:78291:rs149821290
1 781845 rs61768199 A G . PASS AF=0.1044 ES:SE:LP:AF:SS:ID -0.000797599:0.00728494:0.0396163:0.1044:78291:rs61768199
1 782721 rs185280546 G A . PASS AF=0.0143713 ES:SE:LP:AF:SS:ID -0.0224683:0.0195755:0.600214:0.0143713:78291:rs185280546
1 782981 rs6594026 C T . PASS AF=0.128338 ES:SE:LP:AF:SS:ID 0.00246937:0.00649619:0.152519:0.128338:78291:rs6594026
1 783193 rs145767270 G C . PASS AF=0.0143639 ES:SE:LP:AF:SS:ID -0.0237656:0.01966:0.644485:0.0143639:78291:rs145767270
1 783194 rs138555831 G T . PASS AF=0.0143713 ES:SE:LP:AF:SS:ID -0.0236862:0.0196578:0.641618:0.0143713:78291:rs138555831
1 783711 rs184266993 G A . PASS AF=0.00541372 ES:SE:LP:AF:SS:ID -0.0139124:0.0321931:0.176767:0.00541372:78291:rs184266993
1 785050 rs2905062 G A . PASS AF=0.87014 ES:SE:LP:AF:SS:ID -0.00212857:0.00646926:0.129516:0.87014:78291:rs2905062
1 785989 rs2980300 T C . PASS AF=0.87009 ES:SE:LP:AF:SS:ID -0.00215866:0.00647397:0.13147:0.87009:78291:rs2980300