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_22130.vcf.gz --id UKB-b:20464 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_22130.txt.gz --cohort_cases 1658 --cohort_controls 110925 --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": "2019-09-13T03:59:31.990890",
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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/public/UKB-b-20464/UKB-b-20464_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20464/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/
Beginning analysis at Thu Oct 17 14:42:16 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20464/UKB-b-20464_data.vcf.gz ...
Read summary statistics for 2749465 SNPs.
Dropped 336 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, 690265 SNPs remain.
After merging with regression SNP LD, 690265 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0098 (0.0054)
Lambda GC: 1.0273
Mean Chi^2: 1.0309
Intercept: 1.0053 (0.0099)
Ratio: 0.1724 (0.3196)
Analysis finished at Thu Oct 17 14:42:56 2019
Total time elapsed: 40.1sQC metrics
Metrics
Metrics
{
"af_correlation": 0.795,
"inflation_factor": 1.0475,
"mean_EFFECT": -8.2512e-08,
"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": 21835,
"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": 690265,
"ldsc_nsnp_merge_regression_ld": 690265,
"ldsc_observed_scale_h2_beta": 0.0098,
"ldsc_observed_scale_h2_se": 0.0054,
"ldsc_intercept_beta": 1.0053,
"ldsc_intercept_se": 0.0099,
"ldsc_lambda_gc": 1.0273,
"ldsc_mean_chisq": 1.0309,
"ldsc_ratio": 0.1715
}
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 | 4 | 58 | 0 | 2749132 | 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 | 2749465 | 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 | 8.660581e+00 | 5.769506e+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 | 7.855954e+07 | 5.664253e+07 | 5687.0000000 | 3.170242e+07 | 6.898188e+07 | 1.147379e+08 | 2.492013e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.000000e-07 | 5.532000e-04 | -0.0037251 | -3.725000e-04 | -2.000000e-06 | 3.698000e-04 | 2.885700e-03 | ▁▁▇▅▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.448000e-04 | 3.520000e-05 | 0.0004884 | 5.144000e-04 | 5.344000e-04 | 5.696000e-04 | 1.112400e-03 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.957705e-01 | 2.901709e-01 | 0.0000071 | 2.399999e-01 | 4.899999e-01 | 7.499995e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.957659e-01 | 2.901452e-01 | 0.0000071 | 2.435383e-01 | 4.945299e-01 | 7.470109e-01 | 9.999998e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.442882e-01 | 1.637050e-01 | 0.2110980 | 3.003440e-01 | 4.175950e-01 | 5.741240e-01 | 7.889020e-01 | ▇▆▅▃▃ |
| numeric | AF_reference | 21835 | 0.9920585 | NA | NA | NA | NA | NA | NA | NA | 4.269452e-01 | 1.841686e-01 | 0.0001997 | 2.803510e-01 | 4.077480e-01 | 5.621010e-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 | -0.0006148 | 0.0008977 | 0.4899999 | 0.4934370 | 0.624290 | 0.7821490 | NA |
| 1 | 54676 | rs2462492 | C | T | -0.0008202 | 0.0008898 | 0.3599996 | 0.3566782 | 0.400055 | NA | NA |
| 1 | 91536 | rs6702460 | G | T | -0.0012321 | 0.0008764 | 0.1600000 | 0.1597708 | 0.456878 | 0.4207270 | NA |
| 1 | 534192 | rs6680723 | C | T | -0.0003555 | 0.0010018 | 0.7199992 | 0.7226935 | 0.240639 | NA | NA |
| 1 | 706368 | rs55727773 | A | G | -0.0000878 | 0.0006213 | 0.8900000 | 0.8876774 | 0.515771 | 0.2751600 | NA |
| 1 | 763394 | rs369924889 | G | A | 0.0002516 | 0.0007292 | 0.7300002 | 0.7301165 | 0.706831 | 0.6176120 | NA |
| 1 | 768253 | rs2977608 | A | C | 0.0011477 | 0.0005953 | 0.0539995 | 0.0538580 | 0.760925 | 0.4894170 | NA |
| 1 | 776546 | rs12124819 | A | G | 0.0004976 | 0.0006644 | 0.4500005 | 0.4539176 | 0.264797 | 0.0756789 | NA |
| 1 | 808631 | rs11240779 | G | A | 0.0002333 | 0.0006032 | 0.6999999 | 0.6989272 | 0.772089 | 0.4534740 | NA |
| 1 | 808928 | rs11240780 | C | T | 0.0002585 | 0.0006042 | 0.6700003 | 0.6687933 | 0.772288 | 0.4522760 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51180501 | rs5770999 | T | C | 0.0006226 | 0.0005840 | 0.2900000 | 0.2863390 | 0.712166 | 0.6369810 | NA |
| 22 | 51181919 | rs9616825 | G | C | 0.0005742 | 0.0005814 | 0.3200000 | 0.3233714 | 0.694545 | 0.6194090 | NA |
| 22 | 51182485 | rs6009961 | A | G | 0.0006971 | 0.0005859 | 0.2300001 | 0.2340569 | 0.714054 | 0.6383790 | NA |
| 22 | 51186143 | rs2879914 | T | C | 0.0002339 | 0.0005436 | 0.6700003 | 0.6670323 | 0.380938 | 0.2733630 | NA |
| 22 | 51186228 | rs3865766 | C | T | 0.0002474 | 0.0005300 | 0.6400000 | 0.6406846 | 0.449163 | 0.4532750 | NA |
| 22 | 51197266 | rs61290853 | A | G | 0.0004736 | 0.0005473 | 0.3900004 | 0.3868629 | 0.385056 | 0.4229230 | NA |
| 22 | 51198027 | rs34939255 | A | G | 0.0002915 | 0.0006189 | 0.6400000 | 0.6377020 | 0.255274 | 0.0984425 | NA |
| 22 | 51211106 | rs9628250 | T | C | 0.0001533 | 0.0006143 | 0.8000000 | 0.8029002 | 0.272131 | 0.1671330 | NA |
| 22 | 51212875 | rs2238837 | A | C | 0.0007725 | 0.0005830 | 0.1900002 | 0.1851464 | 0.330790 | 0.3724040 | NA |
| 22 | 51237063 | rs3896457 | T | C | 0.0009146 | 0.0005967 | 0.1299999 | 0.1253177 | 0.297871 | 0.2050720 | NA |
bcf preview
1 49298 rs10399793 T C . PASS AF=0.62429 ES:SE:LP:AF:ID -0.00061479:0.000897697:0.309804:0.62429:rs10399793
1 54676 rs2462492 C T . PASS AF=0.400055 ES:SE:LP:AF:ID -0.000820169:0.000889831:0.443698:0.400055:rs2462492
1 91536 rs6702460 G T . PASS AF=0.456878 ES:SE:LP:AF:ID -0.00123212:0.000876428:0.79588:0.456878:rs6702460
1 534192 rs6680723 C T . PASS AF=0.240639 ES:SE:LP:AF:ID -0.0003555:0.0010018:0.142668:0.240639:rs6680723
1 706368 rs12029736 A G . PASS AF=0.515771 ES:SE:LP:AF:ID -8.77547e-05:0.0006213:0.05061:0.515771:rs12029736
1 763394 rs3115847 G A . PASS AF=0.706831 ES:SE:LP:AF:ID 0.000251557:0.000729213:0.136677:0.706831:rs3115847
1 768253 rs2977608 A C . PASS AF=0.760925 ES:SE:LP:AF:ID 0.00114769:0.000595282:1.26761:0.760925:rs2977608
1 776546 rs12124819 A G . PASS AF=0.264797 ES:SE:LP:AF:ID 0.000497566:0.000664396:0.346787:0.264797:rs12124819
1 808631 rs11240779 G A . PASS AF=0.772089 ES:SE:LP:AF:ID 0.000233313:0.000603236:0.154902:0.772089:rs11240779
1 808928 rs11240780 C T . PASS AF=0.772288 ES:SE:LP:AF:ID 0.00025848:0.000604201:0.173925:0.772288:rs11240780
1 814495 rs74461805 C A . PASS AF=0.340813 ES:SE:LP:AF:ID 4.29842e-05:0.000852589:0.0177288:0.340813:rs74461805
1 830181 rs28444699 A G . PASS AF=0.69696 ES:SE:LP:AF:ID 0.000376518:0.000571278:0.29243:0.69696:rs28444699
1 831489 rs4970385 C T . PASS AF=0.705749 ES:SE:LP:AF:ID 1.80179e-05:0.000561035:0.0132283:0.705749:rs4970385
1 831909 rs9697642 C T . PASS AF=0.705791 ES:SE:LP:AF:ID 3.65382e-05:0.00056098:0.0222764:0.705791:rs9697642
1 832066 rs9697380 G C . PASS AF=0.705939 ES:SE:LP:AF:ID 2.826e-05:0.000560965:0.0177288:0.705939:rs9697380
1 832318 rs4500250 C A . PASS AF=0.705972 ES:SE:LP:AF:ID 2.73624e-05:0.000561045:0.0177288:0.705972:rs4500250
1 832398 rs4553118 T C . PASS AF=0.729979 ES:SE:LP:AF:ID 0.000223428:0.000577009:0.154902:0.729979:rs4553118
1 832918 rs28765502 T C . PASS AF=0.294052 ES:SE:LP:AF:ID -2.8355e-05:0.000561029:0.0177288:0.294052:rs28765502
1 833223 rs13303211 C T . PASS AF=0.2364 ES:SE:LP:AF:ID -0.000221676:0.00059585:0.148742:0.2364:rs13303211
1 833302 rs28752186 C T . PASS AF=0.236424 ES:SE:LP:AF:ID -0.0002234:0.000595825:0.148742:0.236424:rs28752186
1 833641 rs28594623 T C . PASS AF=0.239554 ES:SE:LP:AF:ID -0.000340543:0.000593542:0.244125:0.239554:rs28594623
1 833824 rs28484835 T C . PASS AF=0.236397 ES:SE:LP:AF:ID -0.000221586:0.000595841:0.148742:0.236397:rs28484835
1 833927 rs28593608 T C . PASS AF=0.212584 ES:SE:LP:AF:ID -0.000474304:0.000619867:0.356547:0.212584:rs28593608
1 834198 rs28385272 T C . PASS AF=0.212472 ES:SE:LP:AF:ID -0.000468457:0.000620046:0.346787:0.212472:rs28385272
1 834832 rs4411087 G C . PASS AF=0.236917 ES:SE:LP:AF:ID -0.000223282:0.000595433:0.148742:0.236917:rs4411087
1 834928 rs4422949 A G . PASS AF=0.213107 ES:SE:LP:AF:ID -0.000484344:0.000619185:0.366532:0.213107:rs4422949
1 834999 rs28570054 G A . PASS AF=0.213064 ES:SE:LP:AF:ID -0.000474286:0.000619253:0.356547:0.213064:rs28570054
1 835499 rs4422948 A G . PASS AF=0.240707 ES:SE:LP:AF:ID -0.000126949:0.000591765:0.0809219:0.240707:rs4422948
1 836529 rs28731045 C G . PASS AF=0.213725 ES:SE:LP:AF:ID -0.000479799:0.000618362:0.356547:0.213725:rs28731045
1 836896 rs28705752 T C . PASS AF=0.268788 ES:SE:LP:AF:ID -0.000454992:0.000570657:0.366532:0.268788:rs28705752
1 836924 rs72890788 G A . PASS AF=0.213705 ES:SE:LP:AF:ID -0.000491789:0.000618413:0.366532:0.213705:rs72890788
1 838387 rs4970384 T C . PASS AF=0.214775 ES:SE:LP:AF:ID -0.000445675:0.000617157:0.327902:0.214775:rs4970384
1 838555 rs4970383 C A . PASS AF=0.246001 ES:SE:LP:AF:ID -0.000639596:0.000587932:0.552842:0.246001:rs4970383
1 839103 rs28562941 A G . PASS AF=0.269302 ES:SE:LP:AF:ID -0.000437427:0.000571117:0.356547:0.269302:rs28562941
1 840753 rs4970382 T C . PASS AF=0.400563 ES:SE:LP:AF:ID 0.000194228:0.000516748:0.148742:0.400563:rs4970382
1 841085 rs1574243 C G . PASS AF=0.236822 ES:SE:LP:AF:ID -0.000380158:0.000600497:0.275724:0.236822:rs1574243
1 842013 rs7419119 T G . PASS AF=0.215671 ES:SE:LP:AF:ID -0.000542957:0.000617582:0.420216:0.215671:rs7419119
1 842362 rs28540380 C T . PASS AF=0.234923 ES:SE:LP:AF:ID -0.000852659:0.000609699:0.79588:0.234923:rs28540380
1 843405 rs11516185 A G . PASS AF=0.361607 ES:SE:LP:AF:ID 0.000153002:0.000641441:0.091515:0.361607:rs11516185
1 845938 rs57760052 G A . PASS AF=0.211306 ES:SE:LP:AF:ID -0.000997952:0.000620814:0.958607:0.211306:rs57760052
1 847491 rs28407778 G A . PASS AF=0.215487 ES:SE:LP:AF:ID -0.000638333:0.000615459:0.522879:0.215487:rs28407778
1 848090 rs4246505 G A . PASS AF=0.21378 ES:SE:LP:AF:ID -0.0006027:0.000617127:0.481486:0.21378:rs4246505
1 848738 rs3829741 C T . PASS AF=0.213623 ES:SE:LP:AF:ID -0.000603071:0.000617657:0.481486:0.213623:rs3829741
1 850062 rs28723578 A T . PASS AF=0.215638 ES:SE:LP:AF:ID -0.000646613:0.00061496:0.537602:0.215638:rs28723578
1 850123 rs28622257 C T . PASS AF=0.213991 ES:SE:LP:AF:ID -0.000611167:0.000616562:0.49485:0.213991:rs28622257
1 850218 rs6664536 T A . PASS AF=0.589752 ES:SE:LP:AF:ID 1.42944e-05:0.000514007:0.00877392:0.589752:rs6664536
1 850371 rs6679046 G T . PASS AF=0.602907 ES:SE:LP:AF:ID -9.54826e-05:0.000517345:0.0705811:0.602907:rs6679046
1 850780 rs6657440 C T . PASS AF=0.603088 ES:SE:LP:AF:ID -0.000116452:0.00051706:0.0861861:0.603088:rs6657440
1 851190 rs28609852 G A . PASS AF=0.215721 ES:SE:LP:AF:ID -0.000654068:0.00061489:0.537602:0.215721:rs28609852
1 851204 rs28552953 G C . PASS AF=0.22574 ES:SE:LP:AF:ID -0.000617283:0.000611086:0.508638:0.22574:rs28552953