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/0214720b-f2cd-4418-9e81-4b77d32a3666/call-vcf/inputs/-261044416/upload.txt.gz --id ieu-b-4853 --json /data/cromwell-executions/qc/0214720b-f2cd-4418-9e81-4b77d32a3666/call-vcf/inputs/-261044416/ieu-b-4853_data.json --ref /data/cromwell-executions/qc/0214720b-f2cd-4418-9e81-4b77d32a3666/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/0214720b-f2cd-4418-9e81-4b77d32a3666/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-4853/ieu-b-4853.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/0214720b-f2cd-4418-9e81-4b77d32a3666/call-ldsc/inputs/-261044416/ieu-b-4853.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4853/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Wed Jan 5 19:50:40 2022
Reading summary statistics from /data/cromwell-executions/qc/0214720b-f2cd-4418-9e81-4b77d32a3666/call-ldsc/inputs/-261044416/ieu-b-4853.vcf.gz ...
Read summary statistics for 9702569 SNPs.
Dropped 158595 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, 1210351 SNPs remain.
After merging with regression SNP LD, 1210351 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.117 (0.037)
Lambda GC: 1.0456
Mean Chi^2: 1.0387
Intercept: 1.0057 (0.0065)
Ratio: 0.1481 (0.1684)
Analysis finished at Wed Jan 5 19:52:31 2022
Total time elapsed: 1.0m:51.06sQC metrics
Metrics
Metrics
{
"af_correlation": "NA",
"inflation_factor": 1.0518,
"mean_EFFECT": -0.0001,
"n": 14444,
"n_snps": 9703526,
"n_clumped_hits": 0,
"n_p_sig": 0,
"n_mono": 0,
"n_ns": 1137206,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 9703526,
"n_miss_AF_reference": 639200,
"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": 1210351,
"ldsc_nsnp_merge_regression_ld": 1210351,
"ldsc_observed_scale_h2_beta": 0.117,
"ldsc_observed_scale_h2_se": 0.037,
"ldsc_intercept_beta": 1.0057,
"ldsc_intercept_se": 0.0065,
"ldsc_lambda_gc": 1.0456,
"ldsc_mean_chisq": 1.0387,
"ldsc_ratio": 0.1473
}
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 | 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 | 579 | 0.9999403 | 3 | 58 | 0 | 9691993 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 101 | 0 | 46035 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 662 | 0 | 30808 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | AF | 9703526 | 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 | 8.676602e+00 | 5.777061e+00 | 1.0000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.849253e+07 | 5.648448e+07 | 3.0200e+02 | 3.210172e+07 | 6.873651e+07 | 1.143012e+08 | 2.492405e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -9.010000e-05 | 2.821800e-02 | -3.4940e-01 | -1.320000e-02 | -1.000000e-04 | 1.300000e-02 | 3.473000e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.372330e-02 | 1.483670e-02 | 9.7000e-03 | 1.320000e-02 | 1.740000e-02 | 2.980000e-02 | 2.148000e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.928009e-01 | 2.894811e-01 | 4.0000e-07 | 2.406999e-01 | 4.891004e-01 | 7.432998e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.928004e-01 | 2.894854e-01 | 4.0000e-07 | 2.407042e-01 | 4.890750e-01 | 7.432246e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF_reference | 639200 | 0.9341270 | NA | NA | NA | NA | NA | NA | NA | 2.597932e-01 | 2.537070e-01 | 0.0000e+00 | 4.912140e-02 | 1.723240e-01 | 4.095450e-01 | 1.000000e+00 | ▇▃▂▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.336844e+04 | 1.134145e+03 | 1.1796e+04 | 1.179600e+04 | 1.394900e+04 | 1.444400e+04 | 1.444400e+04 | ▅▁▂▁▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 10177 | rs1264289758 | AC | A | -0.0197 | 0.0157 | 0.2088998 | 0.2095597 | NA | NA | 11796 |
| 1 | 10352 | rs1557426776 | TA | T | -0.0106 | 0.0146 | 0.4675995 | 0.4678220 | NA | NA | 11796 |
| 1 | 11008 | rs575272151 | C | G | -0.0117 | 0.0255 | 0.6448994 | 0.6463609 | NA | 0.0880591 | 11796 |
| 1 | 11012 | rs544419019 | C | G | -0.0117 | 0.0255 | 0.6448994 | 0.6463609 | NA | 0.0880591 | 11796 |
| 1 | 13110 | rs540538026 | G | A | -0.0352 | 0.0390 | 0.3665996 | 0.3667573 | NA | 0.0267572 | 11796 |
| 1 | 13116 | rs62635286 | T | G | 0.0197 | 0.0182 | 0.2782999 | 0.2790670 | NA | 0.0970447 | 11796 |
| 1 | 13118 | rs200579949 | A | G | 0.0197 | 0.0182 | 0.2782999 | 0.2790670 | NA | 0.0970447 | 11796 |
| 1 | 13273 | rs531730856 | G | C | 0.0262 | 0.0187 | 0.1602002 | 0.1611933 | NA | 0.0950479 | 11796 |
| 1 | 14464 | rs546169444 | A | T | 0.0086 | 0.0204 | 0.6729007 | 0.6733399 | NA | 0.0958466 | 11796 |
| 1 | 14599 | rs531646671 | T | A | -0.0328 | 0.0186 | 0.0780495 | 0.0778262 | NA | 0.1475640 | 11796 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51233182 | rs4040317 | G | A | 0.0038 | 0.0132 | 0.7709993 | 0.7734395 | NA | 0.2633790 | 11796 |
| 22 | 51233300 | rs9616839 | C | T | 0.0049 | 0.0135 | 0.7144996 | 0.7166326 | NA | 0.3146960 | 11796 |
| 22 | 51233312 | rs62240043 | A | G | 0.0016 | 0.0139 | 0.9113999 | 0.9083596 | NA | 0.2134580 | 11796 |
| 22 | 51233347 | rs62240044 | T | C | 0.0016 | 0.0139 | 0.9113999 | 0.9083596 | NA | 0.2134580 | 11796 |
| 22 | 51234799 | rs191117135 | G | A | -0.0213 | 0.0514 | 0.6780005 | 0.6785835 | NA | 0.0059904 | 11796 |
| 22 | 51235959 | rs200189535 | T | C | 0.0018 | 0.0160 | 0.9108000 | 0.9104270 | NA | 0.1996810 | 11796 |
| 22 | 51235979 | rs62240045 | G | A | -0.0041 | 0.0171 | 0.8128000 | 0.8105116 | NA | 0.2400160 | 11796 |
| 22 | 51236013 | rs200507571 | AT | A | 0.0077 | 0.0141 | 0.5840002 | 0.5849977 | NA | NA | 11796 |
| 22 | 51237063 | rs3896457 | T | C | 0.0100 | 0.0121 | 0.4094002 | 0.4085510 | NA | 0.2050720 | 13002 |
| 22 | 51237712 | rs370652263 | G | A | -0.0091 | 0.0252 | 0.7190995 | 0.7180164 | NA | 0.0690895 | 11796 |
bcf preview
1 10177 rs1264289758 AC A . PASS . ES:SE:LP:SS:ID -0.0197:0.0157:0.680062:11796:rs1264289758
1 10352 rs1557426776 TA T . PASS . ES:SE:LP:SS:ID -0.0106:0.0146:0.330126:11796:rs1557426776
1 11008 rs575272151 C G . PASS . ES:SE:LP:SS:ID -0.0117:0.0255:0.190508:11796:rs575272151
1 11012 rs544419019 C G . PASS . ES:SE:LP:SS:ID -0.0117:0.0255:0.190508:11796:rs544419019
1 13110 rs540538026 G A . PASS . ES:SE:LP:SS:ID -0.0352:0.039:0.435808:11796:rs540538026
1 13116 rs62635286 T G . PASS . ES:SE:LP:SS:ID 0.0197:0.0182:0.555487:11796:rs62635286
1 13118 rs62028691 A G . PASS . ES:SE:LP:SS:ID 0.0197:0.0182:0.555487:11796:rs62028691
1 13273 rs531730856 G C . PASS . ES:SE:LP:SS:ID 0.0262:0.0187:0.795337:11796:rs531730856
1 14464 rs546169444 A T . PASS . ES:SE:LP:SS:ID 0.0086:0.0204:0.172049:11796:rs546169444
1 14599 rs707680 T A . PASS . ES:SE:LP:SS:ID -0.0328:0.0186:1.10763:11796:rs707680
1 14604 rs1418508701 A G . PASS . ES:SE:LP:SS:ID -0.0328:0.0186:1.10763:11796:rs1418508701
1 14930 rs6682385 A G . PASS . ES:SE:LP:SS:ID -0.0083:0.0143:0.249106:11796:rs6682385
1 14933 rs199856693 G A . PASS . ES:SE:LP:SS:ID 0.0232:0.0328:0.318216:11796:rs199856693
1 15211 rs3982632 T G . PASS . ES:SE:LP:SS:ID -0.0164:0.0167:0.487182:11796:rs3982632
1 15820 rs1316988498 G T . PASS . ES:SE:LP:SS:ID 0.0125:0.0158:0.36734:11796:rs1316988498
1 15903 rs557514207 GC G . PASS . ES:SE:LP:SS:ID 0.0075:0.0138:0.230697:11796:rs557514207
1 28590 rs1344649620 T TTGG . PASS . ES:SE:LP:SS:ID -0.1083:0.0569:1.24352:11796:rs1344649620
1 30923 rs1165072081 G T . PASS . ES:SE:LP:SS:ID 0.0233:0.031:0.344477:11796:rs1165072081
1 47159 rs540662756 T C . PASS . ES:SE:LP:SS:ID -0.0317:0.0335:0.463442:11796:rs540662756
1 49298 rs10399793 T C . PASS . ES:SE:LP:SS:ID 0.0134:0.0143:0.461175:12760:rs10399793
1 49554 rs539322794 A G . PASS . ES:SE:LP:SS:ID 0.0192:0.0303:0.278849:11796:rs539322794
1 51479 rs116400033 T A . PASS . ES:SE:LP:SS:ID 0.0199:0.0184:0.552842:11796:rs116400033
1 54490 rs141149254 G A . PASS . ES:SE:LP:SS:ID 0.0507:0.0219:1.68487:11796:rs141149254
1 54676 rs2462492 C T . PASS . ES:SE:LP:SS:ID -0.0189:0.0146:0.711751:12760:rs2462492
1 54712 rs573184866 TTTTC T . PASS . ES:SE:LP:SS:ID 0.0187:0.0134:0.783306:11796:rs573184866
1 54716 rs1166278911 C T . PASS . ES:SE:LP:SS:ID -0.0096:0.0183:0.220909:11796:rs1166278911
1 55545 rs28396308 C T . PASS . ES:SE:LP:SS:ID -0.0242:0.0156:0.916497:11796:rs28396308
1 58814 rs114420996 G A . PASS . ES:SE:LP:SS:ID -0.0014:0.031:0.0158329:11796:rs114420996
1 59040 rs62637815 T C . PASS . ES:SE:LP:SS:ID 0.0093:0.0317:0.114017:11796:rs62637815
1 60351 rs62637817 A G . PASS . ES:SE:LP:SS:ID 0.0108:0.0337:0.12517:11796:rs62637817
1 62777 rs3844233 A T . PASS . ES:SE:LP:SS:ID 0.0156:0.0159:0.486782:11796:rs3844233
1 63268 rs28664618 T C . PASS . ES:SE:LP:SS:ID -0.0202:0.0171:0.623971:11796:rs28664618
1 63671 rs80011619 G A . PASS . ES:SE:LP:SS:ID -0.0083:0.0199:0.168514:11796:rs80011619
1 63735 rs61158452 C CCTA . PASS . ES:SE:LP:SS:ID -0.0014:0.0152:0.0325924:11796:rs61158452
1 64931 rs62639104 G A . PASS . ES:SE:LP:SS:ID 0.0204:0.0342:0.259164:11796:rs62639104
1 68082 rs367789441 T C . PASS . ES:SE:LP:SS:ID -0.0126:0.0263:0.200522:11796:rs367789441
1 69428 rs140739101 T G . PASS . ES:SE:LP:SS:ID -0.0377:0.0434:0.414991:11796:rs140739101
1 69761 rs200505207 A T . PASS . ES:SE:LP:SS:ID -0.0202:0.0251:0.375099:11796:rs200505207
1 69897 rs200676709 T C . PASS . ES:SE:LP:SS:ID 0.0145:0.0156:0.452102:11796:rs200676709
1 74790 rs13328700 C G . PASS . ES:SE:LP:SS:ID 0.0574:0.039:0.848937:11796:rs13328700
1 74792 rs1335672253 G A . PASS . ES:SE:LP:SS:ID 0.0574:0.039:0.848937:11796:rs1335672253
1 76838 rs563953605 T G . PASS . ES:SE:LP:SS:ID 0.026:0.0297:0.417369:11796:rs563953605
1 76854 rs367666799 A G . PASS . ES:SE:LP:SS:ID -0.0423:0.0272:0.920096:11796:rs367666799
1 77866 rs563593912 C T . PASS . ES:SE:LP:SS:ID 0.0261:0.0298:0.420674:11796:rs563593912
1 77874 rs62641297 G A . PASS . ES:SE:LP:SS:ID 0.0261:0.0298:0.420674:11796:rs62641297
1 81260 rs571136476 C T . PASS . ES:SE:LP:SS:ID -0.0702:0.0634:0.571217:11796:rs571136476
1 81587 rs536406113 C T . PASS . ES:SE:LP:SS:ID -0.0163:0.0286:0.245346:11796:rs536406113
1 82163 rs139113303 G A . PASS . ES:SE:LP:SS:ID -0.0407:0.0279:0.839832:11796:rs139113303
1 82609 rs149189449 C G . PASS . ES:SE:LP:SS:ID -0.0407:0.0279:0.839832:11796:rs149189449
1 83514 rs201754587 C T . PASS . ES:SE:LP:SS:ID 0.0119:0.0142:0.395018:11796:rs201754587