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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"gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_20090_371.vcf.gz --id UKB-b:9025 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20090_371.txt.gz --cohort_cases 5250 --cohort_controls 59699 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
"file_date": "2019-09-13T11:44:04.282988",
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"bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-9025/ukb-b-9025.vcf.gz; Date=Sun May 10 02:08:29 2020"
}
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/public/UKB-b-9025/UKB-b-9025_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9025/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/
Beginning analysis at Thu Oct 17 14:42:09 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9025/UKB-b-9025_data.vcf.gz ...
Read summary statistics for 4981765 SNPs.
Dropped 1415 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1113145 SNPs remain.
After merging with regression SNP LD, 1113145 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0062 (0.008)
Lambda GC: 1.0123
Mean Chi^2: 1.0185
Intercept: 1.01 (0.0078)
Ratio: 0.5413 (0.4202)
Analysis finished at Thu Oct 17 14:43:09 2019
Total time elapsed: 59.56sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9061,
"inflation_factor": 1,
"mean_EFFECT": -1.3561e-06,
"n": "-Inf",
"n_snps": 9851866,
"n_clumped_hits": 0,
"n_p_sig": 0,
"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": 42487,
"n_est": "NA",
"ratio_se_n": "NA",
"mean_diff": "NaN",
"ratio_diff": "NaN",
"sd_y_est1": "NaN",
"sd_y_est2": "NA",
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1113145,
"ldsc_nsnp_merge_regression_ld": 1113145,
"ldsc_observed_scale_h2_beta": 0.0062,
"ldsc_observed_scale_h2_se": 0.008,
"ldsc_intercept_beta": 1.01,
"ldsc_intercept_se": 0.0078,
"ldsc_lambda_gc": 1.0123,
"ldsc_mean_chisq": 1.0185,
"ldsc_ratio": 0.5405
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | TRUE |
| 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 | TRUE |
| 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 | logical.mean | logical.count | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 0 | 1.0000000 | 3 | 58 | 0 | 4980360 | 0 | NA | NA | 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 | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 4981765 | 0.0000000 | NA | NA | NA | NA | NA | NaN | : | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.667795e+00 | 5.766273e+00 | 1.0000000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.858099e+07 | 5.664692e+07 | 828.0000000 | 3.189132e+07 | 6.896864e+07 | 1.146212e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.400000e-06 | 2.017200e-03 | -0.0133431 | -1.279900e-03 | -1.000000e-06 | 1.282100e-03 | 1.388630e-02 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.948600e-03 | 4.314000e-04 | 0.0014605 | 1.582700e-03 | 1.795000e-03 | 2.225400e-03 | 5.561100e-03 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.970382e-01 | 2.894752e-01 | 0.0000001 | 2.500000e-01 | 5.000000e-01 | 7.499995e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.970402e-01 | 2.894493e-01 | 0.0000001 | 2.461218e-01 | 4.967755e-01 | 7.473500e-01 | 9.999999e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.525439e-01 | 2.379501e-01 | 0.0666670 | 1.475030e-01 | 2.873950e-01 | 5.189610e-01 | 9.333330e-01 | ▇▅▃▂▂ |
| numeric | AF_reference | 42487 | 0.9914715 | NA | NA | NA | NA | NA | NA | NA | 3.458490e-01 | 2.348223e-01 | 0.0000000 | 1.519570e-01 | 2.895370e-01 | 5.081870e-01 | 1.000000e+00 | ▇▇▅▃▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 49298 | rs200943160 | T | C | 0.0010830 | 0.0026916 | 0.6899999 | 0.6874186 | 0.623812 | 0.7821490 | NA |
| 1 | 54676 | rs2462492 | C | T | 0.0024641 | 0.0026838 | 0.3599996 | 0.3585404 | 0.399144 | NA | NA |
| 1 | 86028 | rs114608975 | T | C | -0.0029381 | 0.0042722 | 0.4899999 | 0.4916258 | 0.103536 | 0.0277556 | NA |
| 1 | 91536 | rs6702460 | G | T | 0.0005562 | 0.0026397 | 0.8300000 | 0.8331048 | 0.455916 | 0.4207270 | NA |
| 1 | 234313 | rs8179466 | C | T | -0.0022494 | 0.0052204 | 0.6700003 | 0.6665427 | 0.074455 | NA | NA |
| 1 | 534192 | rs6680723 | C | T | -0.0033078 | 0.0030065 | 0.2700001 | 0.2712363 | 0.242057 | NA | NA |
| 1 | 546697 | rs12025928 | A | G | -0.0066866 | 0.0037304 | 0.0729995 | 0.0730586 | 0.912862 | NA | NA |
| 1 | 693731 | rs12238997 | A | G | 0.0017965 | 0.0025069 | 0.4700002 | 0.4736115 | 0.117313 | 0.1417730 | NA |
| 1 | 705882 | rs72631875 | G | A | -0.0023397 | 0.0036541 | 0.5199996 | 0.5219747 | 0.067698 | 0.0315495 | NA |
| 1 | 706368 | rs55727773 | A | G | 0.0000773 | 0.0018608 | 0.9699999 | 0.9668601 | 0.513304 | 0.2751600 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51213613 | rs34726907 | C | T | 0.0012834 | 0.0023211 | 0.5800000 | 0.5803052 | 0.126422 | 0.1727240 | NA |
| 22 | 51216564 | rs9616970 | T | C | 0.0009730 | 0.0023120 | 0.6700003 | 0.6738568 | 0.126887 | 0.1563500 | NA |
| 22 | 51217954 | rs9616974 | G | A | -0.0000919 | 0.0029446 | 0.9800000 | 0.9751022 | 0.071487 | 0.0621006 | NA |
| 22 | 51218224 | rs9616975 | C | A | -0.0001055 | 0.0029460 | 0.9699999 | 0.9714437 | 0.071497 | 0.0619010 | NA |
| 22 | 51218377 | rs2519461 | G | C | -0.0002604 | 0.0029422 | 0.9299999 | 0.9294647 | 0.071792 | 0.0826677 | NA |
| 22 | 51219006 | rs28729663 | G | A | 0.0005345 | 0.0022634 | 0.8100000 | 0.8133266 | 0.136315 | 0.2052720 | NA |
| 22 | 51219387 | rs9616832 | T | C | 0.0000863 | 0.0029500 | 0.9800000 | 0.9766572 | 0.071797 | 0.0654952 | NA |
| 22 | 51221731 | rs115055839 | T | C | -0.0000679 | 0.0029507 | 0.9800000 | 0.9816448 | 0.071348 | 0.0625000 | NA |
| 22 | 51229805 | rs9616985 | T | C | -0.0002440 | 0.0029598 | 0.9299999 | 0.9342914 | 0.071253 | 0.0730831 | NA |
| 22 | 51237063 | rs3896457 | T | C | -0.0004535 | 0.0017868 | 0.8000000 | 0.7996302 | 0.298393 | 0.2050720 | NA |
bcf preview
1 49298 rs10399793 T C . PASS AF=0.623812 ES:SE:LP:AF:ID 0.00108301:0.00269164:0.161151:0.623812:rs10399793
1 54676 rs2462492 C T . PASS AF=0.399144 ES:SE:LP:AF:ID 0.00246414:0.00268381:0.443698:0.399144:rs2462492
1 86028 rs114608975 T C . PASS AF=0.103536 ES:SE:LP:AF:ID -0.0029381:0.0042722:0.309804:0.103536:rs114608975
1 91536 rs6702460 G T . PASS AF=0.455916 ES:SE:LP:AF:ID 0.000556243:0.00263971:0.0809219:0.455916:rs6702460
1 234313 rs8179466 C T . PASS AF=0.074455 ES:SE:LP:AF:ID -0.00224945:0.00522038:0.173925:0.074455:rs8179466
1 534192 rs6680723 C T . PASS AF=0.242057 ES:SE:LP:AF:ID -0.0033078:0.00300649:0.568636:0.242057:rs6680723
1 546697 rs12025928 A G . PASS AF=0.912862 ES:SE:LP:AF:ID -0.00668661:0.0037304:1.13668:0.912862:rs12025928
1 693731 rs12238997 A G . PASS AF=0.117313 ES:SE:LP:AF:ID 0.00179649:0.00250691:0.327902:0.117313:rs12238997
1 705882 rs72631875 G A . PASS AF=0.067698 ES:SE:LP:AF:ID -0.00233973:0.00365409:0.283997:0.067698:rs72631875
1 706368 rs12029736 A G . PASS AF=0.513304 ES:SE:LP:AF:ID 7.73101e-05:0.0018608:0.0132283:0.513304:rs12029736
1 722670 rs116030099 T C . PASS AF=0.102736 ES:SE:LP:AF:ID -0.00323549:0.00303659:0.537602:0.102736:rs116030099
1 729679 rs4951859 C G . PASS AF=0.841441 ES:SE:LP:AF:ID 0.00044145:0.00216801:0.0757207:0.841441:rs4951859
1 731718 rs58276399 T C . PASS AF=0.123078 ES:SE:LP:AF:ID 0.000571992:0.00238127:0.091515:0.123078:rs58276399
1 734349 rs141242758 T C . PASS AF=0.12233 ES:SE:LP:AF:ID 0.000702292:0.00238204:0.113509:0.12233:rs141242758
1 736289 rs79010578 T A . PASS AF=0.134139 ES:SE:LP:AF:ID -0.000314924:0.00233836:0.05061:0.134139:rs79010578
1 752566 rs3094315 G A . PASS AF=0.837029 ES:SE:LP:AF:ID -0.000527985:0.00209729:0.09691:0.837029:rs3094315
1 752721 rs3131972 A G . PASS AF=0.836733 ES:SE:LP:AF:ID -0.000359876:0.00209575:0.0655015:0.836733:rs3131972
1 753405 rs3115860 C A . PASS AF=0.868562 ES:SE:LP:AF:ID -0.00130597:0.00225199:0.251812:0.868562:rs3115860
1 753541 rs2073813 G A . PASS AF=0.131004 ES:SE:LP:AF:ID 0.00112495:0.00225777:0.207608:0.131004:rs2073813
1 754182 rs3131969 A G . PASS AF=0.867976 ES:SE:LP:AF:ID -0.00113931:0.00224837:0.21467:0.867976:rs3131969
1 754192 rs3131968 A G . PASS AF=0.86805 ES:SE:LP:AF:ID -0.00118763:0.00224929:0.221849:0.86805:rs3131968
1 754334 rs3131967 T C . PASS AF=0.867987 ES:SE:LP:AF:ID -0.00115538:0.00224831:0.21467:0.867987:rs3131967
1 754503 rs3115859 G A . PASS AF=0.836159 ES:SE:LP:AF:ID -0.000570224:0.00208962:0.107905:0.836159:rs3115859
1 754964 rs3131966 C T . PASS AF=0.836793 ES:SE:LP:AF:ID -0.000507751:0.00209534:0.091515:0.836793:rs3131966
1 755775 rs3131965 A G . PASS AF=0.838109 ES:SE:LP:AF:ID -0.00104661:0.00212484:0.207608:0.838109:rs3131965
1 755890 rs3115858 A T . PASS AF=0.868228 ES:SE:LP:AF:ID -0.00146563:0.00224542:0.29243:0.868228:rs3115858
1 756604 rs3131962 A G . PASS AF=0.867742 ES:SE:LP:AF:ID -0.00153796:0.00223947:0.309804:0.867742:rs3131962
1 757640 rs3115853 G A . PASS AF=0.866644 ES:SE:LP:AF:ID -0.00108457:0.00223537:0.200659:0.866644:rs3115853
1 757734 rs4951929 C T . PASS AF=0.867911 ES:SE:LP:AF:ID -0.00139567:0.00224174:0.275724:0.867911:rs4951929
1 757936 rs4951862 C A . PASS AF=0.867923 ES:SE:LP:AF:ID -0.00139662:0.0022419:0.275724:0.867923:rs4951862
1 758144 rs3131956 A G . PASS AF=0.867932 ES:SE:LP:AF:ID -0.00140527:0.00224198:0.275724:0.867932:rs3131956
1 758626 rs3131954 C T . PASS AF=0.868398 ES:SE:LP:AF:ID -0.00141295:0.00224788:0.275724:0.868398:rs3131954
1 760912 rs1048488 C T . PASS AF=0.836369 ES:SE:LP:AF:ID -0.000780932:0.00208441:0.148742:0.836369:rs1048488
1 761147 rs3115850 T C . PASS AF=0.836495 ES:SE:LP:AF:ID -0.000798335:0.00208583:0.154902:0.836495:rs3115850
1 761732 rs2286139 C T . PASS AF=0.860851 ES:SE:LP:AF:ID -0.00104622:0.00223403:0.19382:0.860851:rs2286139
1 763394 rs3115847 G A . PASS AF=0.705804 ES:SE:LP:AF:ID -0.00113239:0.00218002:0.221849:0.705804:rs3115847
1 766007 rs61768174 A C . PASS AF=0.106094 ES:SE:LP:AF:ID 0.000158578:0.00250853:0.0222764:0.106094:rs61768174
1 768253 rs2977608 A C . PASS AF=0.758252 ES:SE:LP:AF:ID -0.00218654:0.00176692:0.657577:0.758252:rs2977608
1 768448 rs12562034 G A . PASS AF=0.108262 ES:SE:LP:AF:ID 0.00245333:0.00243193:0.508638:0.108262:rs12562034
1 769223 rs60320384 C G . PASS AF=0.13066 ES:SE:LP:AF:ID 0.001328:0.00225691:0.251812:0.13066:rs60320384
1 771823 rs2977605 T C . PASS AF=0.867852 ES:SE:LP:AF:ID -0.00148501:0.00224458:0.29243:0.867852:rs2977605
1 771967 rs59066358 G A . PASS AF=0.130756 ES:SE:LP:AF:ID 0.00140946:0.0022554:0.275724:0.130756:rs59066358
1 772755 rs2905039 A C . PASS AF=0.867878 ES:SE:LP:AF:ID -0.00149596:0.00224472:0.29243:0.867878:rs2905039
1 776546 rs12124819 A G . PASS AF=0.263729 ES:SE:LP:AF:ID -0.000347308:0.00199656:0.0655015:0.263729:rs12124819
1 777122 rs2980319 A T . PASS AF=0.869067 ES:SE:LP:AF:ID -0.0012772:0.00225062:0.244125:0.869067:rs2980319
1 777232 rs112618790 C T . PASS AF=0.096639 ES:SE:LP:AF:ID 0.00141812:0.00259237:0.236572:0.096639:rs112618790
1 778745 rs1055606 A G . PASS AF=0.129594 ES:SE:LP:AF:ID 0.00133211:0.00225921:0.251812:0.129594:rs1055606
1 779322 rs4040617 A G . PASS AF=0.129863 ES:SE:LP:AF:ID 0.00154011:0.00225536:0.309804:0.129863:rs4040617
1 780785 rs2977612 T A . PASS AF=0.867843 ES:SE:LP:AF:ID -0.00106855:0.00224503:0.200659:0.867843:rs2977612
1 781845 rs61768199 A G . PASS AF=0.102807 ES:SE:LP:AF:ID 0.000199584:0.00254612:0.0268721:0.102807:rs61768199