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": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30050_irnt/ukb-d-30050_irnt_data.json --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/b37/human_g1k_v37.fasta; 1.1.1",
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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-d-import/processed/ukb-d-30050_irnt/ukb-d-30050_irnt.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-d-import/processed/ukb-d-30050_irnt/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Mon Nov 25 14:49:31 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30050_irnt/ukb-d-30050_irnt.vcf.gz ...
Read summary statistics for 13586284 SNPs.
Dropped 12710 SNPs with duplicated rs numbers.
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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2285 (0.028)
Lambda GC: 1.4991
Mean Chi^2: 2.7191
Intercept: 1.1492 (0.0201)
Ratio: 0.0868 (0.0117)
Analysis finished at Mon Nov 25 14:52:13 2019
Total time elapsed: 2.0m:42.69sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9521,
"inflation_factor": 1.3297,
"mean_EFFECT": -0.0001,
"n": 350472,
"n_snps": 13586284,
"n_clumped_hits": 361,
"n_p_sig": 101350,
"n_mono": 0,
"n_ns": 1251793,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 569192,
"n_est": 351807.6277,
"ratio_se_n": 1.0019,
"mean_diff": -2.1744e-06,
"ratio_diff": 1.2306,
"sd_y_est1": 0.9924,
"sd_y_est2": 0.9943,
"r2_sum1": 0.154,
"r2_sum2": 0.1564,
"r2_sum3": 0.1558,
"r2_sum4": 0.1549,
"ldsc_nsnp_merge_refpanel_ld": 1283504,
"ldsc_nsnp_merge_regression_ld": 1283504,
"ldsc_observed_scale_h2_beta": 0.2285,
"ldsc_observed_scale_h2_se": 0.028,
"ldsc_intercept_beta": 1.1492,
"ldsc_intercept_se": 0.0201,
"ldsc_lambda_gc": 1.4991,
"ldsc_mean_chisq": 2.7191,
"ldsc_ratio": 0.0868
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | TRUE |
| n | FALSE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | TRUE |
| n_p_sig | TRUE |
| 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 | 94 | 0 | 13574238 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 57080 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33337 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.051337e+00 | 6.184982e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.902520e+07 | 5.591483e+07 | 3.02000e+02 | 3.293108e+07 | 7.013883e+07 | 1.148590e+08 | 2.492309e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -7.140000e-05 | 1.510370e-02 | -7.80999e-01 | -4.466900e-03 | -1.500000e-06 | 4.417900e-03 | 4.316020e-01 | ▁▁▁▇▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.961300e-03 | 9.609000e-03 | 1.94840e-03 | 2.836000e-03 | 5.226000e-03 | 1.431540e-02 | 4.871490e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.514550e-01 | 3.037621e-01 | 0.00000e+00 | 1.758559e-01 | 4.367119e-01 | 7.148633e-01 | 1.000000e+00 | ▇▆▅▅▅ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.514545e-01 | 3.037623e-01 | 0.00000e+00 | 1.758554e-01 | 4.367115e-01 | 7.148625e-01 | 9.999999e-01 | ▇▆▅▅▅ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.908060e-01 | 2.544034e-01 | 1.00000e-03 | 7.430500e-03 | 6.003380e-02 | 2.953170e-01 | 9.990000e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 569192 | 0.9581054 | NA | NA | NA | NA | NA | 1.963357e-01 | 2.471015e-01 | 0.00000e+00 | 5.591000e-03 | 8.426520e-02 | 3.081070e-01 | 1.000000e+00 | ▇▂▁▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.504720e+05 | 0.000000e+00 | 3.50472e+05 | 3.504720e+05 | 3.504720e+05 | 3.504720e+05 | 3.504720e+05 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 692794 | rs530212009 | CA | C | -0.0013720 | 0.0041499 | 0.7409433 | 0.7409431 | 0.1106770 | 0.1894970 | 350472 |
| 1 | 693731 | rs12238997 | A | G | -0.0041753 | 0.0039212 | 0.2869650 | 0.2869642 | 0.1158580 | 0.1417730 | 350472 |
| 1 | 707522 | rs371890604 | G | C | -0.0001300 | 0.0044096 | 0.9764781 | 0.9764782 | 0.0972836 | 0.1293930 | 350472 |
| 1 | 717587 | rs144155419 | G | A | -0.0201193 | 0.0105101 | 0.0555840 | 0.0555841 | 0.0157162 | 0.0045926 | 350472 |
| 1 | 723329 | rs189787166 | A | T | -0.0233479 | 0.0311461 | 0.4534809 | 0.4534805 | 0.0017252 | 0.0003994 | 350472 |
| 1 | 730087 | rs148120343 | T | C | -0.0013155 | 0.0054610 | 0.8096449 | 0.8096454 | 0.0564941 | 0.0127796 | 350472 |
| 1 | 731718 | rs142557973 | T | C | -0.0022943 | 0.0037187 | 0.5372594 | 0.5372574 | 0.1217800 | 0.1543530 | 350472 |
| 1 | 732032 | rs61770163 | A | C | -0.0031824 | 0.0039673 | 0.4224623 | 0.4224606 | 0.1211750 | 0.1555510 | 350472 |
| 1 | 734349 | rs141242758 | T | C | -0.0024807 | 0.0037207 | 0.5049449 | 0.5049439 | 0.1210100 | 0.1525560 | 350472 |
| 1 | 740284 | rs61770167 | C | T | -0.0196364 | 0.0170226 | 0.2486858 | 0.2486852 | 0.0057871 | 0.0023962 | 350472 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154923311 | rs141127553 | C | T | -0.0034650 | 0.0042954 | 0.4198547 | 0.4198539 | 0.0561535 | 0.0309934 | 350472 |
| 23 | 154923374 | rs111332691 | T | A | 0.0109091 | 0.0047218 | 0.0208675 | 0.0208672 | 0.0447910 | 0.0116556 | 350472 |
| 23 | 154925045 | rs509981 | C | T | -0.0002512 | 0.0022723 | 0.9119760 | 0.9119758 | 0.2454590 | 0.3634440 | 350472 |
| 23 | 154925895 | rs538470 | C | T | -0.0003302 | 0.0023242 | 0.8870410 | 0.8870415 | 0.2418070 | 0.3634440 | 350472 |
| 23 | 154927581 | rs644138 | G | A | -0.0011687 | 0.0021367 | 0.5844118 | 0.5844107 | 0.3020080 | 0.4635760 | 350472 |
| 23 | 154929412 | rs557132 | C | T | -0.0001627 | 0.0022729 | 0.9429221 | 0.9429222 | 0.2453140 | 0.3568210 | 350472 |
| 23 | 154929637 | rs35185538 | CT | C | 0.0011173 | 0.0023725 | 0.6376759 | 0.6376765 | 0.2295360 | 0.3011920 | 350472 |
| 23 | 154929952 | rs4012982 | CAA | C | -0.0002113 | 0.0023906 | 0.9295569 | 0.9295567 | 0.2392700 | 0.3165560 | 350472 |
| 23 | 154930230 | rs781880 | A | G | -0.0003402 | 0.0022726 | 0.8809990 | 0.8809991 | 0.2457250 | 0.3618540 | 350472 |
| 23 | 154930487 | rs781879 | T | A | 0.0029128 | 0.0077989 | 0.7087874 | 0.7087876 | 0.0195285 | 0.1263580 | 350472 |
bcf preview
1 692794 rs530212009 CA C . PASS AF=0.110677 ES:SE:LP:AF:SS:ID -0.00137197:0.00414988:0.130215:0.110677:350472:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.115858 ES:SE:LP:AF:SS:ID -0.00417526:0.00392115:0.542171:0.115858:350472:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0972836 ES:SE:LP:AF:SS:ID -0.000130015:0.00440961:0.0103375:0.0972836:350472:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0157162 ES:SE:LP:AF:SS:ID -0.0201193:0.0105101:1.25505:0.0157162:350472:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00172519 ES:SE:LP:AF:SS:ID -0.0233479:0.0311461:0.343441:0.00172519:350472:rs189787166
1 730087 rs148120343 T C . PASS AF=0.0564941 ES:SE:LP:AF:SS:ID -0.00131547:0.00546102:0.0917054:0.0564941:350472:rs148120343
1 731718 rs58276399 T C . PASS AF=0.12178 ES:SE:LP:AF:SS:ID -0.00229431:0.0037187:0.269816:0.12178:350472:rs58276399
1 732032 rs61770163 A C . PASS AF=0.121175 ES:SE:LP:AF:SS:ID -0.0031824:0.00396729:0.374212:0.121175:350472:rs61770163
1 734349 rs141242758 T C . PASS AF=0.12101 ES:SE:LP:AF:SS:ID -0.0024807:0.00372069:0.296756:0.12101:350472:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00578714 ES:SE:LP:AF:SS:ID -0.0196364:0.0170226:0.604349:0.00578714:350472:rs61770167
1 742813 rs112573343 C T . PASS AF=0.0018841 ES:SE:LP:AF:SS:ID -0.0310125:0.0321277:0.475732:0.0018841:350472:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.869714 ES:SE:LP:AF:SS:ID 0.00397577:0.00366834:0.55525:0.869714:350472:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00153228 ES:SE:LP:AF:SS:ID -0.0189668:0.0331854:0.245931:0.00153228:350472:rs190826124
1 751343 rs28544273 T A . PASS AF=0.122938 ES:SE:LP:AF:SS:ID -0.00275102:0.0036328:0.347863:0.122938:350472:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.142739 ES:SE:LP:AF:SS:ID -0.00194512:0.00359106:0.230581:0.142739:350472:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123054 ES:SE:LP:AF:SS:ID -0.00286549:0.00362771:0.366942:0.123054:350472:rs28527770
1 753405 rs3115860 C A . PASS AF=0.870849 ES:SE:LP:AF:SS:ID 0.00361167:0.00353507:0.512948:0.870849:350472:rs3115860
1 753425 rs3131970 T C . PASS AF=0.875449 ES:SE:LP:AF:SS:ID 0.00401024:0.00359369:0.577638:0.875449:350472:rs3131970
1 753541 rs2073813 G A . PASS AF=0.128671 ES:SE:LP:AF:SS:ID -0.003006:0.00354393:0.401952:0.128671:350472:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0363367 ES:SE:LP:AF:SS:ID 0.00919398:0.00643437:0.815201:0.0363367:350472:rs12184325
1 754182 rs3131969 A G . PASS AF=0.870443 ES:SE:LP:AF:SS:ID 0.00362803:0.00353136:0.516778:0.870443:350472:rs3131969
1 754192 rs3131968 A G . PASS AF=0.870544 ES:SE:LP:AF:SS:ID 0.0034229:0.00353291:0.478058:0.870544:350472:rs3131968
1 754334 rs3131967 T C . PASS AF=0.870438 ES:SE:LP:AF:SS:ID 0.00366093:0.00353121:0.523081:0.870438:350472:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00504299 ES:SE:LP:AF:SS:ID -0.021703:0.0181404:0.635365:0.00504299:350472:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00500986 ES:SE:LP:AF:SS:ID -0.0225801:0.0181888:0.668682:0.00500986:350472:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00558059 ES:SE:LP:AF:SS:ID -0.00315706:0.0175702:0.0668155:0.00558059:350472:rs184270342
1 755890 rs3115858 A T . PASS AF=0.870522 ES:SE:LP:AF:SS:ID 0.00365183:0.00352502:0.522566:0.870522:350472:rs3115858
1 756434 rs61768170 G C . PASS AF=0.126015 ES:SE:LP:AF:SS:ID -0.00296739:0.0035971:0.387845:0.126015:350472:rs61768170
1 756604 rs3131962 A G . PASS AF=0.870085 ES:SE:LP:AF:SS:ID 0.00343636:0.00351653:0.483506:0.870085:350472:rs3131962
1 757640 rs3115853 G A . PASS AF=0.869363 ES:SE:LP:AF:SS:ID 0.00312827:0.00351319:0.428021:0.869363:350472:rs3115853
1 757734 rs4951929 C T . PASS AF=0.870239 ES:SE:LP:AF:SS:ID 0.0034785:0.00351956:0.49081:0.870239:350472:rs4951929
1 757936 rs4951862 C A . PASS AF=0.870245 ES:SE:LP:AF:SS:ID 0.00347789:0.00351982:0.490651:0.870245:350472:rs4951862
1 758144 rs3131956 A G . PASS AF=0.870254 ES:SE:LP:AF:SS:ID 0.00349152:0.00351993:0.49318:0.870254:350472:rs3131956
1 758626 rs3131954 C T . PASS AF=0.870696 ES:SE:LP:AF:SS:ID 0.00362605:0.00352889:0.516884:0.870696:350472:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0988388 ES:SE:LP:AF:SS:ID 0.000602573:0.0041018:0.053937:0.0988388:350472:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00647159 ES:SE:LP:AF:SS:ID -0.00485874:0.0158736:0.119451:0.00647159:350472:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.874605 ES:SE:LP:AF:SS:ID 0.00359004:0.00358157:0.500083:0.874605:350472:rs3115851
1 761732 rs2286139 C T . PASS AF=0.863993 ES:SE:LP:AF:SS:ID 0.00327535:0.00351224:0.454629:0.863993:350472:rs2286139
1 761752 rs1057213 C T . PASS AF=0.869377 ES:SE:LP:AF:SS:ID 0.00415971:0.00354631:0.618327:0.869377:350472:rs1057213
1 762273 rs3115849 G A . PASS AF=0.866336 ES:SE:LP:AF:SS:ID 0.00294013:0.00354714:0.390218:0.866336:350472:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0987498 ES:SE:LP:AF:SS:ID -0.00367507:0.00424784:0.412345:0.0987498:350472:rs12095200
1 762589 rs3115848 G C . PASS AF=0.871519 ES:SE:LP:AF:SS:ID 0.00371805:0.00358749:0.522851:0.871519:350472:rs3115848
1 762592 rs3131950 C G . PASS AF=0.871519 ES:SE:LP:AF:SS:ID 0.00371807:0.00358749:0.522856:0.871519:350472:rs3131950
1 762601 rs3131949 T C . PASS AF=0.871518 ES:SE:LP:AF:SS:ID 0.0036925:0.00358756:0.51804:0.871518:350472:rs3131949
1 762632 rs3131948 T A . PASS AF=0.87189 ES:SE:LP:AF:SS:ID 0.00380719:0.00358959:0.539308:0.87189:350472:rs3131948
1 764191 rs7515915 T G . PASS AF=0.125596 ES:SE:LP:AF:SS:ID -0.00268322:0.00359244:0.341873:0.125596:350472:rs7515915
1 766007 rs61768174 A C . PASS AF=0.105425 ES:SE:LP:AF:SS:ID 0.00141407:0.00391151:0.144048:0.105425:350472:rs61768174
1 766105 rs2519015 T A . PASS AF=0.855335 ES:SE:LP:AF:SS:ID 0.00289188:0.00351132:0.387032:0.855335:350472:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00164753 ES:SE:LP:AF:SS:ID -0.0151288:0.0312:0.202214:0.00164753:350472:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.838287 ES:SE:LP:AF:SS:ID 0.000163347:0.00345874:0.0166751:0.838287:350472:rs376645387