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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"Gwas2VCF_command": "--data /data/cromwell-executions/qc/4afe35a5-22be-4b39-af6d-774f382d09a3/call-vcf/inputs/-261044448/upload.txt.gz --id ieu-b-4842 --json /data/cromwell-executions/qc/4afe35a5-22be-4b39-af6d-774f382d09a3/call-vcf/inputs/-261044448/ieu-b-4842_data.json --ref /data/cromwell-executions/qc/4afe35a5-22be-4b39-af6d-774f382d09a3/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/4afe35a5-22be-4b39-af6d-774f382d09a3/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-4842/ieu-b-4842.vcf.gz --alias alias.txt; 1.3.0",
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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 /data/cromwell-executions/qc/4afe35a5-22be-4b39-af6d-774f382d09a3/call-ldsc/inputs/-261044448/ieu-b-4842.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4842/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Wed Jan 5 15:02:23 2022
Reading summary statistics from /data/cromwell-executions/qc/4afe35a5-22be-4b39-af6d-774f382d09a3/call-ldsc/inputs/-261044448/ieu-b-4842.vcf.gz ...
Read summary statistics for 9695862 SNPs.
Dropped 158562 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1210242 SNPs remain.
After merging with regression SNP LD, 1210242 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1678 (0.0193)
Lambda GC: 1.1479
Mean Chi^2: 1.2121
Intercept: 1.0621 (0.0076)
Ratio: 0.2929 (0.0357)
Analysis finished at Wed Jan 5 15:04:28 2022
Total time elapsed: 2.0m:4.58sQC metrics
Metrics
Metrics
{
"af_correlation": "NA",
"inflation_factor": 1.1258,
"mean_EFFECT": -0.0001,
"n": 45734,
"n_snps": 9696819,
"n_clumped_hits": 37,
"n_p_sig": 4380,
"n_mono": 0,
"n_ns": 1136879,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 9696819,
"n_miss_AF_reference": 639022,
"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": 1210242,
"ldsc_nsnp_merge_regression_ld": 1210242,
"ldsc_observed_scale_h2_beta": 0.1678,
"ldsc_observed_scale_h2_se": 0.0193,
"ldsc_intercept_beta": 1.0621,
"ldsc_intercept_se": 0.0076,
"ldsc_lambda_gc": 1.1479,
"ldsc_mean_chisq": 1.2121,
"ldsc_ratio": 0.2928
}
Flags
| name | value |
|---|---|
| af_correlation | NA |
| inflation_factor | FALSE |
| n | FALSE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | FALSE |
| 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 | logical.mean | logical.count | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 580 | 0.9999402 | 3 | 58 | 0 | 9685280 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 101 | 0 | 46015 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 662 | 0 | 30812 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | AF | 9696819 | 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 | 8.676979e+00 | 5.777166e+00 | 1.0000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.848897e+07 | 5.648206e+07 | 302.0000 | 3.210067e+07 | 6.873262e+07 | 1.142951e+08 | 2.492405e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.000000e-04 | 1.611640e-02 | -0.3617 | -7.700000e-03 | -1.000000e-04 | 7.500000e-03 | 2.420000e-01 | ▁▁▇▇▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.315320e-02 | 7.878800e-03 | 0.0060 | 7.300000e-03 | 9.700000e-03 | 1.690000e-02 | 6.780000e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.808010e-01 | 2.941245e-01 | 0.0000 | 2.220000e-01 | 4.742005e-01 | 7.358004e-01 | 1.000000e+00 | ▇▇▇▇▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.808039e-01 | 2.941324e-01 | 0.0000 | 2.220661e-01 | 4.741214e-01 | 7.356177e-01 | 1.000000e+00 | ▇▇▇▇▆ |
| numeric | AF_reference | 639022 | 0.9340998 | NA | NA | NA | NA | NA | NA | NA | 2.599542e-01 | 2.537058e-01 | 0.0000 | 4.932110e-02 | 1.725240e-01 | 4.097440e-01 | 1.000000e+00 | ▇▃▂▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.141714e+04 | 5.953995e+03 | 29292.0000 | 4.188900e+04 | 4.433700e+04 | 4.573400e+04 | 4.573400e+04 | ▃▁▁▃▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 10177 | rs1264289758 | AC | A | 0.0179 | 0.0096 | 0.0630101 | 0.0622398 | NA | NA | 29292 |
| 1 | 10352 | rs1557426776 | TA | T | 0.0088 | 0.0099 | 0.3740003 | 0.3740628 | NA | NA | 29292 |
| 1 | 11008 | rs575272151 | C | G | -0.0109 | 0.0172 | 0.5276999 | 0.5262630 | NA | 0.0880591 | 29292 |
| 1 | 11012 | rs544419019 | C | G | -0.0109 | 0.0172 | 0.5276999 | 0.5262630 | NA | 0.0880591 | 29292 |
| 1 | 13110 | rs540538026 | G | A | 0.0544 | 0.0266 | 0.0410299 | 0.0408437 | NA | 0.0267572 | 29292 |
| 1 | 13116 | rs62635286 | T | G | 0.0008 | 0.0117 | 0.9472000 | 0.9454863 | NA | 0.0970447 | 29292 |
| 1 | 13118 | rs200579949 | A | G | 0.0008 | 0.0117 | 0.9472000 | 0.9454863 | NA | 0.0970447 | 29292 |
| 1 | 13273 | rs531730856 | G | C | -0.0220 | 0.0143 | 0.1235000 | 0.1239358 | NA | 0.0950479 | 29292 |
| 1 | 14464 | rs546169444 | A | T | -0.0214 | 0.0128 | 0.0937389 | 0.0945490 | NA | 0.0958466 | 29292 |
| 1 | 14599 | rs531646671 | T | A | -0.0155 | 0.0119 | 0.1911001 | 0.1927383 | NA | 0.1475640 | 29292 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51233182 | rs4040317 | G | A | 0.0037 | 0.0091 | 0.6865007 | 0.6843066 | NA | 0.2633790 | 29292 |
| 22 | 51233300 | rs9616839 | C | T | 0.0028 | 0.0090 | 0.7520003 | 0.7557162 | NA | 0.3146960 | 29292 |
| 22 | 51233312 | rs62240043 | A | G | 0.0025 | 0.0095 | 0.7909008 | 0.7924289 | NA | 0.2134580 | 29292 |
| 22 | 51233347 | rs62240044 | T | C | 0.0025 | 0.0095 | 0.7909008 | 0.7924289 | NA | 0.2134580 | 29292 |
| 22 | 51234799 | rs191117135 | G | A | -0.0287 | 0.0325 | 0.3762998 | 0.3771947 | NA | 0.0059904 | 29292 |
| 22 | 51235959 | rs200189535 | T | C | -0.0199 | 0.0102 | 0.0521495 | 0.0510594 | NA | 0.1996810 | 29292 |
| 22 | 51235979 | rs62240045 | G | A | 0.0065 | 0.0104 | 0.5314006 | 0.5319711 | NA | 0.2400160 | 29292 |
| 22 | 51236013 | rs200507571 | AT | A | -0.0057 | 0.0091 | 0.5357004 | 0.5310699 | NA | NA | 29292 |
| 22 | 51237063 | rs3896457 | T | C | 0.0020 | 0.0084 | 0.8105000 | 0.8118072 | NA | 0.2050720 | 33137 |
| 22 | 51237712 | rs370652263 | G | A | 0.0302 | 0.0180 | 0.0946106 | 0.0933905 | NA | 0.0690895 | 29292 |
bcf preview
1 10177 rs1264289758 AC A . PASS . ES:SE:LP:SS:ID 0.0179:0.0096:1.20059:29292:rs1264289758
1 10352 rs1557426776 TA T . PASS . ES:SE:LP:SS:ID 0.0088:0.0099:0.427128:29292:rs1557426776
1 11008 rs575272151 C G . PASS . ES:SE:LP:SS:ID -0.0109:0.0172:0.277613:29292:rs575272151
1 11012 rs544419019 C G . PASS . ES:SE:LP:SS:ID -0.0109:0.0172:0.277613:29292:rs544419019
1 13110 rs540538026 G A . PASS . ES:SE:LP:SS:ID 0.0544:0.0266:1.3869:29292:rs540538026
1 13116 rs62635286 T G . PASS . ES:SE:LP:SS:ID 0.0008:0.0117:0.0235583:29292:rs62635286
1 13118 rs62028691 A G . PASS . ES:SE:LP:SS:ID 0.0008:0.0117:0.0235583:29292:rs62028691
1 13273 rs531730856 G C . PASS . ES:SE:LP:SS:ID -0.022:0.0143:0.908333:29292:rs531730856
1 14464 rs546169444 A T . PASS . ES:SE:LP:SS:ID -0.0214:0.0128:1.02808:29292:rs546169444
1 14599 rs707680 T A . PASS . ES:SE:LP:SS:ID -0.0155:0.0119:0.718739:29292:rs707680
1 14604 rs1418508701 A G . PASS . ES:SE:LP:SS:ID -0.0155:0.0119:0.718739:29292:rs1418508701
1 14930 rs6682385 A G . PASS . ES:SE:LP:SS:ID -0.0077:0.01:0.355365:29292:rs6682385
1 14933 rs199856693 G A . PASS . ES:SE:LP:SS:ID 0.032:0.0255:0.679646:29292:rs199856693
1 15211 rs3982632 T G . PASS . ES:SE:LP:SS:ID 0.006:0.0104:0.247567:29292:rs3982632
1 15820 rs1316988498 G T . PASS . ES:SE:LP:SS:ID 0.0022:0.0105:0.0783655:29292:rs1316988498
1 15903 rs557514207 GC G . PASS . ES:SE:LP:SS:ID 0.013:0.0098:0.733768:29292:rs557514207
1 28590 rs1344649620 T TTGG . PASS . ES:SE:LP:SS:ID -0.0283:0.0322:0.420559:29292:rs1344649620
1 30923 rs1165072081 G T . PASS . ES:SE:LP:SS:ID 0.0161:0.0186:0.41285:29292:rs1165072081
1 47159 rs540662756 T C . PASS . ES:SE:LP:SS:ID -0.0141:0.0221:0.280255:29292:rs540662756
1 49298 rs10399793 T C . PASS . ES:SE:LP:SS:ID -0.0274:0.0106:2.021:30035:rs10399793
1 49554 rs539322794 A G . PASS . ES:SE:LP:SS:ID 0.0273:0.0197:0.780415:29292:rs539322794
1 51479 rs116400033 T A . PASS . ES:SE:LP:SS:ID -0.0019:0.0111:0.0631848:29292:rs116400033
1 54490 rs141149254 G A . PASS . ES:SE:LP:SS:ID -0.0001:0.013:0.00313823:29292:rs141149254
1 54676 rs2462492 C T . PASS . ES:SE:LP:SS:ID 0.0062:0.0104:0.261219:30035:rs2462492
1 54712 rs573184866 TTTTC T . PASS . ES:SE:LP:SS:ID 0.0093:0.0093:0.49485:29292:rs573184866
1 54716 rs1166278911 C T . PASS . ES:SE:LP:SS:ID -0.0004:0.0102:0.0126913:29292:rs1166278911
1 55545 rs28396308 C T . PASS . ES:SE:LP:SS:ID -0.0072:0.0105:0.307858:29292:rs28396308
1 58814 rs114420996 G A . PASS . ES:SE:LP:SS:ID 0.0274:0.0192:0.81051:29292:rs114420996
1 59040 rs62637815 T C . PASS . ES:SE:LP:SS:ID 0.0235:0.02:0.622876:29292:rs62637815
1 60351 rs62637817 A G . PASS . ES:SE:LP:SS:ID 0.0268:0.0205:0.719194:29292:rs62637817
1 62777 rs3844233 A T . PASS . ES:SE:LP:SS:ID -0.0159:0.0101:0.938547:29292:rs3844233
1 63268 rs28664618 T C . PASS . ES:SE:LP:SS:ID 0.0117:0.0103:0.594483:29292:rs28664618
1 63671 rs80011619 G A . PASS . ES:SE:LP:SS:ID 0.0035:0.0131:0.102593:29292:rs80011619
1 63735 rs61158452 C CCTA . PASS . ES:SE:LP:SS:ID -0.0104:0.0099:0.537902:29292:rs61158452
1 64931 rs62639104 G A . PASS . ES:SE:LP:SS:ID 0.0254:0.0208:0.656001:29292:rs62639104
1 68082 rs367789441 T C . PASS . ES:SE:LP:SS:ID 0.0079:0.0189:0.170889:29292:rs367789441
1 69428 rs140739101 T G . PASS . ES:SE:LP:SS:ID 0.0266:0.0322:0.387322:29292:rs140739101
1 69761 rs200505207 A T . PASS . ES:SE:LP:SS:ID -0.0039:0.0184:0.0787819:29292:rs200505207
1 69897 rs200676709 T C . PASS . ES:SE:LP:SS:ID -0.011:0.0106:0.523024:29292:rs200676709
1 74790 rs13328700 C G . PASS . ES:SE:LP:SS:ID -0.0111:0.0289:0.154096:29292:rs13328700
1 74792 rs1335672253 G A . PASS . ES:SE:LP:SS:ID -0.0111:0.0289:0.154096:29292:rs1335672253
1 76838 rs563953605 T G . PASS . ES:SE:LP:SS:ID 0.032:0.0217:0.853562:29292:rs563953605
1 76854 rs367666799 A G . PASS . ES:SE:LP:SS:ID -0.0099:0.0188:0.221994:29292:rs367666799
1 77866 rs563593912 C T . PASS . ES:SE:LP:SS:ID 0.0328:0.0217:0.887395:29292:rs563593912
1 77874 rs62641297 G A . PASS . ES:SE:LP:SS:ID 0.0328:0.0217:0.887395:29292:rs62641297
1 81260 rs571136476 C T . PASS . ES:SE:LP:SS:ID 0.0281:0.0302:0.454693:29292:rs571136476
1 81587 rs536406113 C T . PASS . ES:SE:LP:SS:ID 0.002:0.02:0.0354575:29292:rs536406113
1 82163 rs139113303 G A . PASS . ES:SE:LP:SS:ID -0.0068:0.0191:0.142607:29292:rs139113303
1 82609 rs149189449 C G . PASS . ES:SE:LP:SS:ID -0.0063:0.0191:0.12907:29292:rs149189449
1 83514 rs201754587 C T . PASS . ES:SE:LP:SS:ID -0.0042:0.0105:0.163359:29292:rs201754587