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_20003_1140922174.vcf.gz --id UKB-b:16508 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20003_1140922174.txt.gz --cohort_cases 5360 --cohort_controls 457573 --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": "2019-09-13T02:11:02.137400",
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"bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-16508/ukb-b-16508.vcf.gz; Date=Sun May 10 01:20:20 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-16508/UKB-b-16508_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16508/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/
Beginning analysis at Thu Oct 17 14:45:05 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16508/UKB-b-16508_data.vcf.gz ...
Read summary statistics for 5014241 SNPs.
Dropped 1443 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, 1117422 SNPs remain.
After merging with regression SNP LD, 1117422 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0072 (0.0013)
Lambda GC: 1.0768
Mean Chi^2: 1.081
Intercept: 1.0118 (0.0087)
Ratio: 0.1453 (0.1075)
Analysis finished at Thu Oct 17 14:46:01 2019
Total time elapsed: 55.96sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9067,
"inflation_factor": 1.0966,
"mean_EFFECT": -1.1097e-06,
"n": "-Inf",
"n_snps": 9851866,
"n_clumped_hits": 2,
"n_p_sig": 134,
"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": 42847,
"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": 1117422,
"ldsc_nsnp_merge_regression_ld": 1117422,
"ldsc_observed_scale_h2_beta": 0.0072,
"ldsc_observed_scale_h2_se": 0.0013,
"ldsc_intercept_beta": 1.0118,
"ldsc_intercept_se": 0.0087,
"ldsc_lambda_gc": 1.0768,
"ldsc_mean_chisq": 1.081,
"ldsc_ratio": 0.1457
}
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 | 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 | 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 | 5012809 | 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 | 5014241 | 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 | 8.668390e+00 | 5.765653e+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 | 7.857117e+07 | 5.663851e+07 | 828.0000000 | 3.188595e+07 | 6.896576e+07 | 1.145996e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.100000e-06 | 3.063000e-04 | -0.0025826 | -1.960000e-04 | -2.700000e-06 | 1.934000e-04 | 2.762100e-03 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.870000e-04 | 6.450000e-05 | 0.0002141 | 2.323000e-04 | 2.639000e-04 | 3.282000e-04 | 8.131000e-04 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.873255e-01 | 2.919874e-01 | 0.0000000 | 2.300001e-01 | 4.799997e-01 | 7.400005e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.873261e-01 | 2.919601e-01 | 0.0000000 | 2.312394e-01 | 4.826703e-01 | 7.402532e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.511606e-01 | 2.386069e-01 | 0.0652990 | 1.456620e-01 | 2.854290e-01 | 5.176450e-01 | 9.347010e-01 | ▇▅▃▂▂ |
| numeric | AF_reference | 42847 | 0.9914549 | NA | NA | NA | NA | NA | NA | NA | 3.445805e-01 | 2.353071e-01 | 0.0000000 | 1.503590e-01 | 2.877400e-01 | 5.069890e-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 | -0.0000717 | 0.0003940 | 0.8600001 | 0.8555690 | 0.623763 | 0.7821490 | NA |
| 1 | 54676 | rs2462492 | C | T | 0.0003250 | 0.0003904 | 0.4100001 | 0.4051779 | 0.400401 | NA | NA |
| 1 | 86028 | rs114608975 | T | C | 0.0001591 | 0.0006241 | 0.8000000 | 0.7988341 | 0.103556 | 0.0277556 | NA |
| 1 | 91536 | rs6702460 | G | T | 0.0001609 | 0.0003844 | 0.6800001 | 0.6755896 | 0.456851 | 0.4207270 | NA |
| 1 | 234313 | rs8179466 | C | T | 0.0007360 | 0.0007579 | 0.3300000 | 0.3315058 | 0.074508 | NA | NA |
| 1 | 534192 | rs6680723 | C | T | -0.0007603 | 0.0004391 | 0.0830004 | 0.0833427 | 0.240960 | NA | NA |
| 1 | 546697 | rs12025928 | A | G | 0.0003290 | 0.0005477 | 0.5500004 | 0.5480829 | 0.913473 | NA | NA |
| 1 | 693731 | rs12238997 | A | G | 0.0000452 | 0.0003680 | 0.9000000 | 0.9021434 | 0.116325 | 0.1417730 | NA |
| 1 | 705882 | rs72631875 | G | A | -0.0004001 | 0.0005392 | 0.4600002 | 0.4580497 | 0.067285 | 0.0315495 | NA |
| 1 | 706368 | rs55727773 | A | G | -0.0000281 | 0.0002726 | 0.9199999 | 0.9179638 | 0.515650 | 0.2751600 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51213613 | rs34726907 | C | T | -0.0002520 | 0.0003374 | 0.4600002 | 0.4550240 | 0.127816 | 0.1727240 | NA |
| 22 | 51216564 | rs9616970 | T | C | -0.0002584 | 0.0003359 | 0.4400003 | 0.4417968 | 0.128330 | 0.1563500 | NA |
| 22 | 51217954 | rs9616974 | G | A | -0.0003007 | 0.0004263 | 0.4799997 | 0.4804737 | 0.073314 | 0.0621006 | NA |
| 22 | 51218224 | rs9616975 | C | A | -0.0003032 | 0.0004264 | 0.4799997 | 0.4770674 | 0.073336 | 0.0619010 | NA |
| 22 | 51218377 | rs2519461 | G | C | -0.0002630 | 0.0004259 | 0.5400003 | 0.5369499 | 0.073625 | 0.0826677 | NA |
| 22 | 51219006 | rs28729663 | G | A | -0.0001497 | 0.0003288 | 0.6499995 | 0.6487944 | 0.137953 | 0.2052720 | NA |
| 22 | 51219387 | rs9616832 | T | C | -0.0003231 | 0.0004268 | 0.4500005 | 0.4490871 | 0.073747 | 0.0654952 | NA |
| 22 | 51221731 | rs115055839 | T | C | -0.0002982 | 0.0004271 | 0.4799997 | 0.4849909 | 0.073238 | 0.0625000 | NA |
| 22 | 51229805 | rs9616985 | T | C | -0.0003180 | 0.0004286 | 0.4600002 | 0.4580833 | 0.073073 | 0.0730831 | NA |
| 22 | 51237063 | rs3896457 | T | C | 0.0000689 | 0.0002621 | 0.7899998 | 0.7927111 | 0.297971 | 0.2050720 | NA |
bcf preview
1 49298 rs10399793 T C . PASS AF=0.623763 ES:SE:LP:AF:ID -7.17231e-05:0.000394045:0.0655015:0.623763:rs10399793
1 54676 rs2462492 C T . PASS AF=0.400401 ES:SE:LP:AF:ID 0.000324951:0.000390374:0.387216:0.400401:rs2462492
1 86028 rs114608975 T C . PASS AF=0.103556 ES:SE:LP:AF:ID 0.000159064:0.000624132:0.09691:0.103556:rs114608975
1 91536 rs6702460 G T . PASS AF=0.456851 ES:SE:LP:AF:ID 0.000160858:0.000384378:0.167491:0.456851:rs6702460
1 234313 rs8179466 C T . PASS AF=0.074508 ES:SE:LP:AF:ID 0.000735971:0.000757885:0.481486:0.074508:rs8179466
1 534192 rs6680723 C T . PASS AF=0.24096 ES:SE:LP:AF:ID -0.000760271:0.000439054:1.08092:0.24096:rs6680723
1 546697 rs12025928 A G . PASS AF=0.913473 ES:SE:LP:AF:ID 0.000328995:0.000547745:0.259637:0.913473:rs12025928
1 693731 rs12238997 A G . PASS AF=0.116325 ES:SE:LP:AF:ID 4.5241e-05:0.00036795:0.0457575:0.116325:rs12238997
1 705882 rs72631875 G A . PASS AF=0.067285 ES:SE:LP:AF:ID -0.000400111:0.000539188:0.337242:0.067285:rs72631875
1 706368 rs12029736 A G . PASS AF=0.51565 ES:SE:LP:AF:ID -2.80734e-05:0.00027256:0.0362122:0.51565:rs12029736
1 722670 rs116030099 T C . PASS AF=0.101199 ES:SE:LP:AF:ID 0.00029259:0.000449706:0.283997:0.101199:rs116030099
1 729679 rs4951859 C G . PASS AF=0.843212 ES:SE:LP:AF:ID 4.97411e-05:0.000318876:0.0555173:0.843212:rs4951859
1 731718 rs58276399 T C . PASS AF=0.122307 ES:SE:LP:AF:ID -0.000161903:0.000349037:0.19382:0.122307:rs58276399
1 734349 rs141242758 T C . PASS AF=0.121549 ES:SE:LP:AF:ID -0.000180727:0.000349184:0.221849:0.121549:rs141242758
1 736289 rs79010578 T A . PASS AF=0.13233 ES:SE:LP:AF:ID -4.14342e-05:0.000344155:0.0457575:0.13233:rs79010578
1 752566 rs3094315 G A . PASS AF=0.838951 ES:SE:LP:AF:ID 7.18917e-05:0.000308808:0.0861861:0.838951:rs3094315
1 752721 rs3131972 A G . PASS AF=0.83858 ES:SE:LP:AF:ID 7.41807e-05:0.000308476:0.091515:0.83858:rs3131972
1 753405 rs3115860 C A . PASS AF=0.869781 ES:SE:LP:AF:ID 0.000107128:0.000331007:0.124939:0.869781:rs3115860
1 753541 rs2073813 G A . PASS AF=0.129871 ES:SE:LP:AF:ID -8.65101e-05:0.000331685:0.102373:0.129871:rs2073813
1 754182 rs3131969 A G . PASS AF=0.869123 ES:SE:LP:AF:ID 0.000104482:0.000330359:0.124939:0.869123:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869221 ES:SE:LP:AF:ID 9.89883e-05:0.00033049:0.119186:0.869221:rs3131968
1 754334 rs3131967 T C . PASS AF=0.869126 ES:SE:LP:AF:ID 8.97252e-05:0.000330352:0.102373:0.869126:rs3131967
1 754503 rs3115859 G A . PASS AF=0.838033 ES:SE:LP:AF:ID 6.52539e-05:0.00030762:0.0809219:0.838033:rs3115859
1 754964 rs3131966 C T . PASS AF=0.838664 ES:SE:LP:AF:ID 6.03677e-05:0.000308484:0.0757207:0.838664:rs3131966
1 755775 rs3131965 A G . PASS AF=0.839777 ES:SE:LP:AF:ID 6.80862e-05:0.000312657:0.0809219:0.839777:rs3131965
1 755890 rs3115858 A T . PASS AF=0.869405 ES:SE:LP:AF:ID 0.000125888:0.00032997:0.154902:0.869405:rs3115858
1 756604 rs3131962 A G . PASS AF=0.868952 ES:SE:LP:AF:ID 0.00013975:0.00032914:0.173925:0.868952:rs3131962
1 757640 rs3115853 G A . PASS AF=0.867905 ES:SE:LP:AF:ID 0.000117814:0.000328509:0.142668:0.867905:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869095 ES:SE:LP:AF:ID 0.000136317:0.00032941:0.167491:0.869095:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869104 ES:SE:LP:AF:ID 0.000136043:0.000329435:0.167491:0.869104:rs4951862
1 758144 rs3131956 A G . PASS AF=0.869112 ES:SE:LP:AF:ID 0.000135775:0.000329442:0.167491:0.869112:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869589 ES:SE:LP:AF:ID 0.000120664:0.000330347:0.148742:0.869589:rs3131954
1 760912 rs1048488 C T . PASS AF=0.838313 ES:SE:LP:AF:ID 2.43718e-05:0.000307036:0.0268721:0.838313:rs1048488
1 761147 rs3115850 T C . PASS AF=0.838434 ES:SE:LP:AF:ID 2.20462e-05:0.000307253:0.0268721:0.838434:rs3115850
1 761732 rs2286139 C T . PASS AF=0.862261 ES:SE:LP:AF:ID 7.50335e-06:0.000328251:0.00877392:0.862261:rs2286139
1 763394 rs3115847 G A . PASS AF=0.706753 ES:SE:LP:AF:ID -0.000294838:0.00031955:0.443698:0.706753:rs3115847
1 766007 rs61768174 A C . PASS AF=0.105142 ES:SE:LP:AF:ID -7.95291e-05:0.000368119:0.0809219:0.105142:rs61768174
1 768253 rs2977608 A C . PASS AF=0.761304 ES:SE:LP:AF:ID 7.91338e-05:0.00026081:0.119186:0.761304:rs2977608
1 768448 rs12562034 G A . PASS AF=0.106488 ES:SE:LP:AF:ID -9.36051e-05:0.000359475:0.102373:0.106488:rs12562034
1 769223 rs60320384 C G . PASS AF=0.129576 ES:SE:LP:AF:ID -3.94494e-05:0.000331487:0.0409586:0.129576:rs60320384
1 771823 rs2977605 T C . PASS AF=0.868911 ES:SE:LP:AF:ID 9.56337e-05:0.000329716:0.113509:0.868911:rs2977605
1 771967 rs59066358 G A . PASS AF=0.129677 ES:SE:LP:AF:ID -4.89942e-05:0.000331273:0.0555173:0.129677:rs59066358
1 772755 rs2905039 A C . PASS AF=0.868921 ES:SE:LP:AF:ID 9.08871e-05:0.000329723:0.107905:0.868921:rs2905039
1 776546 rs12124819 A G . PASS AF=0.26539 ES:SE:LP:AF:ID 0.000533256:0.000291329:1.17393:0.26539:rs12124819
1 777122 rs2980319 A T . PASS AF=0.870044 ES:SE:LP:AF:ID 6.09544e-05:0.000330395:0.0705811:0.870044:rs2980319
1 777232 rs112618790 C T . PASS AF=0.095139 ES:SE:LP:AF:ID -0.000112636:0.000382915:0.113509:0.095139:rs112618790
1 778745 rs1055606 A G . PASS AF=0.128576 ES:SE:LP:AF:ID -1.70191e-05:0.000331699:0.0177288:0.128576:rs1055606
1 779322 rs4040617 A G . PASS AF=0.128873 ES:SE:LP:AF:ID -1.39167e-05:0.000331137:0.0132283:0.128873:rs4040617
1 780785 rs2977612 T A . PASS AF=0.868786 ES:SE:LP:AF:ID 2.36089e-05:0.000329514:0.0268721:0.868786:rs2977612
1 781845 rs61768199 A G . PASS AF=0.10187 ES:SE:LP:AF:ID 2.86939e-05:0.000373371:0.0268721:0.10187:rs61768199