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_41245_1040.vcf.gz --id UKB-b:19023 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_41245_1040.txt.gz --cohort_cases 5479 --cohort_controls 456017 --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": "2019-09-12T19:13:01.000386",
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"bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-19023/ukb-b-19023.vcf.gz; Date=Sat May 9 18:39:54 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-19023/UKB-b-19023_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19023/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/
Beginning analysis at Thu Oct 17 14:40:56 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19023/UKB-b-19023_data.vcf.gz ...
Read summary statistics for 5049616 SNPs.
Dropped 1484 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, 1122233 SNPs remain.
After merging with regression SNP LD, 1122233 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0049 (0.0012)
Lambda GC: 1.0762
Mean Chi^2: 1.0786
Intercept: 1.0318 (0.0077)
Ratio: 0.4045 (0.0983)
Analysis finished at Thu Oct 17 14:41:55 2019
Total time elapsed: 59.38sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9076,
"inflation_factor": 1.0966,
"mean_EFFECT": 1.1247e-06,
"n": "-Inf",
"n_snps": 9851866,
"n_clumped_hits": 2,
"n_p_sig": 3,
"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": 43229,
"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": 1122233,
"ldsc_nsnp_merge_regression_ld": 1122233,
"ldsc_observed_scale_h2_beta": 0.0049,
"ldsc_observed_scale_h2_se": 0.0012,
"ldsc_intercept_beta": 1.0318,
"ldsc_intercept_se": 0.0077,
"ldsc_lambda_gc": 1.0762,
"ldsc_mean_chisq": 1.0786,
"ldsc_ratio": 0.4046
}
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 | 5048143 | 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 | 5049616 | 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 | 8.671186e+00 | 5.766661e+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 | 7.855750e+07 | 5.663020e+07 | 828.0000000 | 3.187945e+07 | 6.895760e+07 | 1.145711e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.100000e-06 | 3.109000e-04 | -0.0019322 | -1.968000e-04 | 3.000000e-07 | 1.988000e-04 | 2.357000e-03 | ▁▂▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.928000e-04 | 6.680000e-05 | 0.0002176 | 2.362000e-04 | 2.688000e-04 | 3.354000e-04 | 8.355000e-04 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.883137e-01 | 2.914740e-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 | 4.883145e-01 | 2.914490e-01 | 0.0000000 | 2.336635e-01 | 4.838489e-01 | 7.404867e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.497389e-01 | 2.393349e-01 | 0.0638810 | 1.436210e-01 | 2.834250e-01 | 5.163320e-01 | 9.361170e-01 | ▇▅▃▂▂ |
| numeric | AF_reference | 43229 | 0.9914392 | NA | NA | NA | NA | NA | NA | NA | 3.432870e-01 | 2.358325e-01 | 0.0000000 | 1.485620e-01 | 2.857430e-01 | 5.057910e-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 | -0.0004791 | 0.0004004 | 0.2300001 | 0.2314307 | 0.623779 | 0.7821490 | NA |
| 1 | 54676 | rs2462492 | C | T | -0.0001651 | 0.0003967 | 0.6800001 | 0.6772006 | 0.400421 | NA | NA |
| 1 | 86028 | rs114608975 | T | C | -0.0008213 | 0.0006343 | 0.2000000 | 0.1953235 | 0.103549 | 0.0277556 | NA |
| 1 | 91536 | rs6702460 | G | T | -0.0001832 | 0.0003906 | 0.6400000 | 0.6389669 | 0.456872 | 0.4207270 | NA |
| 1 | 234313 | rs8179466 | C | T | 0.0023570 | 0.0007701 | 0.0022000 | 0.0022073 | 0.074513 | NA | NA |
| 1 | 534192 | rs6680723 | C | T | -0.0007527 | 0.0004461 | 0.0920005 | 0.0915684 | 0.240950 | NA | NA |
| 1 | 546697 | rs12025928 | A | G | -0.0000815 | 0.0005565 | 0.8800001 | 0.8836007 | 0.913469 | NA | NA |
| 1 | 693731 | rs12238997 | A | G | 0.0002154 | 0.0003739 | 0.5600000 | 0.5645776 | 0.116330 | 0.1417730 | NA |
| 1 | 705882 | rs72631875 | G | A | -0.0008686 | 0.0005478 | 0.1100001 | 0.1128577 | 0.067305 | 0.0315495 | NA |
| 1 | 706368 | rs55727773 | A | G | -0.0000507 | 0.0002770 | 0.8499999 | 0.8546831 | 0.515673 | 0.2751600 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51213613 | rs34726907 | C | T | -0.0000162 | 0.0003428 | 0.9599999 | 0.9622423 | 0.127813 | 0.1727240 | NA |
| 22 | 51216564 | rs9616970 | T | C | -0.0000217 | 0.0003413 | 0.9500000 | 0.9492701 | 0.128325 | 0.1563500 | NA |
| 22 | 51217954 | rs9616974 | G | A | 0.0001011 | 0.0004331 | 0.8200001 | 0.8154991 | 0.073303 | 0.0621006 | NA |
| 22 | 51218224 | rs9616975 | C | A | 0.0000974 | 0.0004333 | 0.8200001 | 0.8222300 | 0.073323 | 0.0619010 | NA |
| 22 | 51218377 | rs2519461 | G | C | 0.0000985 | 0.0004328 | 0.8200001 | 0.8199880 | 0.073611 | 0.0826677 | NA |
| 22 | 51219006 | rs28729663 | G | A | 0.0000246 | 0.0003341 | 0.9400001 | 0.9412166 | 0.137949 | 0.2052720 | NA |
| 22 | 51219387 | rs9616832 | T | C | 0.0000819 | 0.0004336 | 0.8499999 | 0.8502698 | 0.073736 | 0.0654952 | NA |
| 22 | 51221731 | rs115055839 | T | C | 0.0000964 | 0.0004339 | 0.8200001 | 0.8241332 | 0.073226 | 0.0625000 | NA |
| 22 | 51229805 | rs9616985 | T | C | 0.0000737 | 0.0004355 | 0.8700001 | 0.8656254 | 0.073063 | 0.0730831 | NA |
| 22 | 51237063 | rs3896457 | T | C | 0.0005636 | 0.0002664 | 0.0340001 | 0.0343529 | 0.298009 | 0.2050720 | NA |
bcf preview
1 49298 rs10399793 T C . PASS AF=0.623779 ES:SE:LP:AF:ID -0.000479113:0.000400368:0.638272:0.623779:rs10399793
1 54676 rs2462492 C T . PASS AF=0.400421 ES:SE:LP:AF:ID -0.000165147:0.000396715:0.167491:0.400421:rs2462492
1 86028 rs114608975 T C . PASS AF=0.103549 ES:SE:LP:AF:ID -0.000821349:0.000634251:0.69897:0.103549:rs114608975
1 91536 rs6702460 G T . PASS AF=0.456872 ES:SE:LP:AF:ID -0.000183225:0.000390552:0.19382:0.456872:rs6702460
1 234313 rs8179466 C T . PASS AF=0.074513 ES:SE:LP:AF:ID 0.00235702:0.000770062:2.65758:0.074513:rs8179466
1 534192 rs6680723 C T . PASS AF=0.24095 ES:SE:LP:AF:ID -0.000752699:0.000446128:1.03621:0.24095:rs6680723
1 546697 rs12025928 A G . PASS AF=0.913469 ES:SE:LP:AF:ID -8.14818e-05:0.000556546:0.0555173:0.913469:rs12025928
1 693731 rs12238997 A G . PASS AF=0.11633 ES:SE:LP:AF:ID 0.000215378:0.000373884:0.251812:0.11633:rs12238997
1 705882 rs72631875 G A . PASS AF=0.067305 ES:SE:LP:AF:ID -0.000868552:0.000547817:0.958607:0.067305:rs72631875
1 706368 rs12029736 A G . PASS AF=0.515673 ES:SE:LP:AF:ID -5.07257e-05:0.000276968:0.0705811:0.515673:rs12029736
1 722670 rs116030099 T C . PASS AF=0.1012 ES:SE:LP:AF:ID 6.65684e-05:0.000456986:0.0555173:0.1012:rs116030099
1 729679 rs4951859 C G . PASS AF=0.843191 ES:SE:LP:AF:ID 0.000322817:0.000324016:0.49485:0.843191:rs4951859
1 731718 rs58276399 T C . PASS AF=0.12232 ES:SE:LP:AF:ID 8.76244e-05:0.000354662:0.09691:0.12232:rs58276399
1 734349 rs141242758 T C . PASS AF=0.121563 ES:SE:LP:AF:ID 7.9107e-05:0.000354811:0.0861861:0.121563:rs141242758
1 736289 rs79010578 T A . PASS AF=0.132343 ES:SE:LP:AF:ID -0.00024595:0.000349712:0.318759:0.132343:rs79010578
1 752566 rs3094315 G A . PASS AF=0.838931 ES:SE:LP:AF:ID 0.000195405:0.000313785:0.275724:0.838931:rs3094315
1 752721 rs3131972 A G . PASS AF=0.83856 ES:SE:LP:AF:ID 0.000216247:0.000313447:0.309804:0.83856:rs3131972
1 753405 rs3115860 C A . PASS AF=0.869769 ES:SE:LP:AF:ID -4.87621e-05:0.000336341:0.0555173:0.869769:rs3115860
1 753541 rs2073813 G A . PASS AF=0.129885 ES:SE:LP:AF:ID 6.97666e-05:0.000337022:0.0757207:0.129885:rs2073813
1 754182 rs3131969 A G . PASS AF=0.86911 ES:SE:LP:AF:ID -2.97355e-05:0.00033568:0.0315171:0.86911:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869207 ES:SE:LP:AF:ID -3.8338e-05:0.000335812:0.0409586:0.869207:rs3131968
1 754334 rs3131967 T C . PASS AF=0.869113 ES:SE:LP:AF:ID -3.19068e-05:0.000335674:0.0362122:0.869113:rs3131967
1 754503 rs3115859 G A . PASS AF=0.838012 ES:SE:LP:AF:ID 0.000209384:0.000312578:0.30103:0.838012:rs3115859
1 754964 rs3131966 C T . PASS AF=0.838643 ES:SE:LP:AF:ID 0.000226949:0.000313456:0.327902:0.838643:rs3131966
1 755775 rs3131965 A G . PASS AF=0.839761 ES:SE:LP:AF:ID 0.000180129:0.0003177:0.244125:0.839761:rs3131965
1 755890 rs3115858 A T . PASS AF=0.869393 ES:SE:LP:AF:ID -6.9898e-05:0.000335288:0.0809219:0.869393:rs3115858
1 756604 rs3131962 A G . PASS AF=0.868942 ES:SE:LP:AF:ID -8.5935e-05:0.000334445:0.09691:0.868942:rs3131962
1 757640 rs3115853 G A . PASS AF=0.867892 ES:SE:LP:AF:ID -7.76836e-05:0.000333802:0.0861861:0.867892:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869085 ES:SE:LP:AF:ID -8.67583e-05:0.000334719:0.09691:0.869085:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869094 ES:SE:LP:AF:ID -8.71269e-05:0.000334745:0.102373:0.869094:rs4951862
1 758144 rs3131956 A G . PASS AF=0.869102 ES:SE:LP:AF:ID -8.68493e-05:0.000334753:0.09691:0.869102:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869577 ES:SE:LP:AF:ID -7.17508e-05:0.000335669:0.0809219:0.869577:rs3131954
1 760912 rs1048488 C T . PASS AF=0.838293 ES:SE:LP:AF:ID 0.000191513:0.000311984:0.267606:0.838293:rs1048488
1 761147 rs3115850 T C . PASS AF=0.838414 ES:SE:LP:AF:ID 0.000189448:0.000312205:0.267606:0.838414:rs3115850
1 761732 rs2286139 C T . PASS AF=0.862248 ES:SE:LP:AF:ID 1.34855e-06:0.000333539:-0:0.862248:rs2286139
1 763394 rs3115847 G A . PASS AF=0.706757 ES:SE:LP:AF:ID -0.000102034:0.000324715:0.124939:0.706757:rs3115847
1 766007 rs61768174 A C . PASS AF=0.105135 ES:SE:LP:AF:ID 0.000294148:0.000374077:0.366532:0.105135:rs61768174
1 768253 rs2977608 A C . PASS AF=0.761327 ES:SE:LP:AF:ID -0.000137692:0.000265039:0.221849:0.761327:rs2977608
1 768448 rs12562034 G A . PASS AF=0.10646 ES:SE:LP:AF:ID 0.000164347:0.000365335:0.187087:0.10646:rs12562034
1 769223 rs60320384 C G . PASS AF=0.129582 ES:SE:LP:AF:ID 0.000157222:0.000336828:0.19382:0.129582:rs60320384
1 771823 rs2977605 T C . PASS AF=0.868905 ES:SE:LP:AF:ID -0.000117365:0.000335034:0.136677:0.868905:rs2977605
1 771967 rs59066358 G A . PASS AF=0.129684 ES:SE:LP:AF:ID 0.000154389:0.000336611:0.187087:0.129684:rs59066358
1 772755 rs2905039 A C . PASS AF=0.868915 ES:SE:LP:AF:ID -0.000110646:0.000335041:0.130768:0.868915:rs2905039
1 776546 rs12124819 A G . PASS AF=0.265358 ES:SE:LP:AF:ID 0.000125223:0.000296038:0.173925:0.265358:rs12124819
1 777122 rs2980319 A T . PASS AF=0.870033 ES:SE:LP:AF:ID -4.02163e-05:0.00033572:0.0457575:0.870033:rs2980319
1 777232 rs112618790 C T . PASS AF=0.095124 ES:SE:LP:AF:ID 0.000103395:0.000389138:0.102373:0.095124:rs112618790
1 778745 rs1055606 A G . PASS AF=0.128586 ES:SE:LP:AF:ID 8.67512e-05:0.000337041:0.09691:0.128586:rs1055606
1 779322 rs4040617 A G . PASS AF=0.128884 ES:SE:LP:AF:ID 7.29994e-05:0.000336468:0.0809219:0.128884:rs4040617
1 780785 rs2977612 T A . PASS AF=0.868774 ES:SE:LP:AF:ID 7.97641e-08:0.000334823:-0:0.868774:rs2977612
1 781845 rs61768199 A G . PASS AF=0.10187 ES:SE:LP:AF:ID 0.000206525:0.000379409:0.229148:0.10187:rs61768199