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/efb29432-0f02-45ca-b379-e39832784245/call-vcf/inputs/-261045345/upload.txt.gz --id ieu-b-4764 --json /data/cromwell-executions/qc/efb29432-0f02-45ca-b379-e39832784245/call-vcf/inputs/-261045345/ieu-b-4764_data.json --ref /data/cromwell-executions/qc/efb29432-0f02-45ca-b379-e39832784245/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/efb29432-0f02-45ca-b379-e39832784245/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-4764/ieu-b-4764.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/efb29432-0f02-45ca-b379-e39832784245/call-ldsc/inputs/-261045345/ieu-b-4764.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4764/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Thu Nov 25 08:19:26 2021
Reading summary statistics from /data/cromwell-executions/qc/efb29432-0f02-45ca-b379-e39832784245/call-ldsc/inputs/-261045345/ieu-b-4764.vcf.gz ...
Read summary statistics for 8036486 SNPs.
Dropped 39424 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, 1204384 SNPs remain.
After merging with regression SNP LD, 1204384 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.059 (0.0146)
Lambda GC: 1.1319
Mean Chi^2: 1.1744
Intercept: 1.1013 (0.009)
Ratio: 0.5806 (0.0516)
Analysis finished at Thu Nov 25 08:21:20 2021
Total time elapsed: 1.0m:54.23sQC metrics
Metrics
Metrics
{
"af_correlation": "NA",
"inflation_factor": 1.1391,
"mean_EFFECT": -0.0011,
"n": 61308,
"n_snps": 8036590,
"n_clumped_hits": 38,
"n_p_sig": 1637,
"n_mono": 0,
"n_ns": 285308,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 8036590,
"n_miss_AF_reference": 171044,
"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": 1204384,
"ldsc_nsnp_merge_regression_ld": 1204384,
"ldsc_observed_scale_h2_beta": 0.059,
"ldsc_observed_scale_h2_se": 0.0146,
"ldsc_intercept_beta": 1.1013,
"ldsc_intercept_se": 0.009,
"ldsc_lambda_gc": 1.1319,
"ldsc_mean_chisq": 1.1744,
"ldsc_ratio": 0.5808
}
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 | TRUE |
| 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 | 50 | 0.9999938 | 3 | 58 | 0 | 8036377 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 43 | 0 | 16626 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 44 | 0 | 6017 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | AF | 8036590 | 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 | 8.655812e+00 | 5.759849e+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 | 7.875083e+07 | 5.638631e+07 | 3.0200e+02 | 3.236003e+07 | 6.927730e+07 | 1.145243e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.129700e-03 | 1.333870e-02 | -1.9070e-01 | -7.300000e-03 | -7.000000e-04 | 5.600000e-03 | 1.855000e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.086610e-02 | 5.986400e-03 | 5.2000e-03 | 6.300000e-03 | 8.300000e-03 | 1.390000e-02 | 3.840000e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.782928e-01 | 2.947813e-01 | 0.0000e+00 | 2.174999e-01 | 4.716002e-01 | 7.330000e-01 | 1.000000e+00 | ▇▇▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.782975e-01 | 2.947953e-01 | 0.0000e+00 | 2.175721e-01 | 4.719572e-01 | 7.330394e-01 | 1.000000e+00 | ▇▇▆▆▆ |
| numeric | AF_reference | 171044 | 0.9787168 | NA | NA | NA | NA | NA | NA | NA | 2.634243e-01 | 2.522301e-01 | 1.9970e-04 | 5.591050e-02 | 1.773160e-01 | 4.113420e-01 | 1.000000e+00 | ▇▃▂▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.792187e+04 | 4.733390e+03 | 3.7363e+04 | 5.595200e+04 | 6.057600e+04 | 6.130800e+04 | 6.130800e+04 | ▁▁▂▂▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 49298 | rs200943160 | T | C | 0.0086 | 0.0089 | 0.3347997 | 0.3338980 | NA | 0.7821490 | 39732 |
| 1 | 54676 | rs2462492 | C | T | 0.0006 | 0.0091 | 0.9496999 | 0.9474303 | NA | NA | 39732 |
| 1 | 86028 | rs114608975 | T | C | -0.0249 | 0.0152 | 0.1020000 | 0.1013888 | NA | 0.0277556 | 39000 |
| 1 | 91536 | rs6702460 | G | T | 0.0086 | 0.0093 | 0.3532002 | 0.3551058 | NA | 0.4207270 | 39732 |
| 1 | 234313 | rs8179466 | C | T | -0.0226 | 0.0204 | 0.2689998 | 0.2679296 | NA | NA | 39000 |
| 1 | 534192 | rs6680723 | C | T | 0.0055 | 0.0097 | 0.5677995 | 0.5707072 | NA | NA | 39732 |
| 1 | 546697 | rs12025928 | A | G | 0.0101 | 0.0143 | 0.4815995 | 0.4800055 | NA | NA | 39000 |
| 1 | 693731 | rs12238997 | A | G | -0.0028 | 0.0111 | 0.8023000 | 0.8008461 | NA | 0.1417730 | 39000 |
| 1 | 705882 | rs72631875 | G | A | 0.0193 | 0.0151 | 0.2009000 | 0.2011981 | NA | 0.0315495 | 39000 |
| 1 | 706368 | rs55727773 | A | G | -0.0051 | 0.0073 | 0.4829999 | 0.4847832 | NA | 0.2751600 | 39732 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51219006 | rs28729663 | G | A | -0.0036 | 0.0100 | 0.7205996 | 0.7188471 | NA | 0.2052720 | 42220 |
| 22 | 51219387 | rs9616832 | T | C | -0.0231 | 0.0131 | 0.0781196 | 0.0778400 | NA | 0.0654952 | 42220 |
| 22 | 51219704 | rs147475742 | G | A | -0.0103 | 0.0183 | 0.5725995 | 0.5735428 | NA | 0.0473243 | 39000 |
| 22 | 51221190 | rs369304721 | G | A | -0.0208 | 0.0157 | 0.1864000 | 0.1852240 | NA | NA | 39000 |
| 22 | 51221731 | rs115055839 | T | C | -0.0220 | 0.0132 | 0.0949795 | 0.0955807 | NA | 0.0625000 | 42220 |
| 22 | 51222100 | rs114553188 | G | T | 0.0063 | 0.0149 | 0.6735006 | 0.6724275 | NA | 0.0880591 | 41488 |
| 22 | 51223637 | rs375798137 | G | A | 0.0060 | 0.0150 | 0.6886999 | 0.6891565 | NA | 0.0788738 | 41488 |
| 22 | 51229805 | rs9616985 | T | C | -0.0219 | 0.0132 | 0.0963097 | 0.0970975 | NA | 0.0730831 | 42220 |
| 22 | 51232488 | rs376461333 | A | G | 0.0069 | 0.0303 | 0.8206000 | 0.8198618 | NA | NA | 39000 |
| 22 | 51237063 | rs3896457 | T | C | 0.0034 | 0.0076 | 0.6559006 | 0.6546091 | NA | 0.2050720 | 42220 |
bcf preview
1 49298 rs10399793 T C . PASS . ES:SE:LP:SS:ID 0.0086:0.0089:0.475215:39732:rs10399793
1 54676 rs2462492 C T . PASS . ES:SE:LP:SS:ID 0.0006:0.0091:0.0224136:39732:rs2462492
1 86028 rs114608975 T C . PASS . ES:SE:LP:SS:ID -0.0249:0.0152:0.9914:39000:rs114608975
1 91536 rs1251109649 G T . PASS . ES:SE:LP:SS:ID 0.0086:0.0093:0.451979:39732:rs1251109649
1 234313 rs8179466 C T . PASS . ES:SE:LP:SS:ID -0.0226:0.0204:0.570248:39000:rs8179466
1 534192 rs6680723 C T . PASS . ES:SE:LP:SS:ID 0.0055:0.0097:0.245805:39732:rs6680723
1 546697 rs12025928 A G . PASS . ES:SE:LP:SS:ID 0.0101:0.0143:0.317314:39000:rs12025928
1 693731 rs12238997 A G . PASS . ES:SE:LP:SS:ID -0.0028:0.0111:0.0956632:39000:rs12238997
1 705882 rs72631875 G A . PASS . ES:SE:LP:SS:ID 0.0193:0.0151:0.69702:39000:rs72631875
1 706368 rs963699400 A G . PASS . ES:SE:LP:SS:ID -0.0051:0.0073:0.316053:39732:rs963699400
1 714596 rs149887893 T C . PASS . ES:SE:LP:SS:ID -0.0282:0.0198:0.809108:39000:rs149887893
1 715265 rs12184267 C T . PASS . ES:SE:LP:SS:ID -0.0236:0.0195:0.644548:39000:rs12184267
1 715367 rs12184277 A G . PASS . ES:SE:LP:SS:ID -0.0214:0.0196:0.561616:39000:rs12184277
1 717485 rs12184279 C A . PASS . ES:SE:LP:SS:ID -0.0221:0.0196:0.586365:39000:rs12184279
1 720381 rs116801199 G T . PASS . ES:SE:LP:SS:ID -0.0224:0.0195:0.601366:39000:rs116801199
1 721290 rs12565286 G C . PASS . ES:SE:LP:SS:ID -0.0217:0.0196:0.573489:39000:rs12565286
1 722670 rs116030099 T C . PASS . ES:SE:LP:SS:ID 0.005:0.0125:0.163233:39000:rs116030099
1 723891 rs2977670 G C . PASS . ES:SE:LP:SS:ID 0.0263:0.0183:0.82333:39000:rs2977670
1 725060 rs1445661281 A T . PASS . ES:SE:LP:SS:ID 0.0029:0.0232:0.0459988:39000:rs1445661281
1 726794 rs28454925 C G . PASS . ES:SE:LP:SS:ID -0.0252:0.0195:0.708409:39000:rs28454925
1 729632 rs116720794 C T . PASS . ES:SE:LP:SS:ID -0.0268:0.0194:0.7734:39000:rs116720794
1 729679 rs4951859 C G . PASS . ES:SE:LP:SS:ID 0.0076:0.0098:0.35635:39732:rs4951859
1 730087 rs148120343 T C . PASS . ES:SE:LP:SS:ID 0.0017:0.0158:0.0394817:39000:rs148120343
1 731718 rs58276399 T C . PASS . ES:SE:LP:SS:ID -0.0029:0.011:0.102648:39000:rs58276399
1 734349 rs141242758 T C . PASS . ES:SE:LP:SS:ID -0.0032:0.011:0.114526:39000:rs141242758
1 736289 rs1254887344 T A . PASS . ES:SE:LP:SS:ID -0.0066:0.0106:0.273599:39732:rs1254887344
1 752478 rs146277091 G A . PASS . ES:SE:LP:SS:ID -0.0324:0.0195:1.01873:39000:rs146277091
1 752566 rs3094315 G A . PASS . ES:SE:LP:SS:ID 0.0108:0.0095:0.595508:42220:rs3094315
1 752721 rs3131972 A G . PASS . ES:SE:LP:SS:ID 0.0109:0.0095:0.601539:42220:rs3131972
1 753405 rs3115860 C A . PASS . ES:SE:LP:SS:ID 0.0093:0.0102:0.444664:41488:rs3115860
1 753541 rs1388595942 G A . PASS . ES:SE:LP:SS:ID -0.0095:0.0103:0.450261:41488:rs1388595942
1 754063 rs12184312 G T . PASS . ES:SE:LP:SS:ID -0.0306:0.0196:0.929962:39000:rs12184312
1 754105 rs12184325 C T . PASS . ES:SE:LP:SS:ID -0.0297:0.0196:0.890759:39000:rs12184325
1 754182 rs3131969 A G . PASS . ES:SE:LP:SS:ID 0.0094:0.0102:0.451856:41488:rs3131969
1 754192 rs3131968 A G . PASS . ES:SE:LP:SS:ID 0.0094:0.0102:0.450997:41488:rs3131968
1 754211 rs12184313 G A . PASS . ES:SE:LP:SS:ID -0.031:0.0195:0.94962:39000:rs12184313
1 754334 rs3131967 T C . PASS . ES:SE:LP:SS:ID 0.0095:0.0102:0.457922:41488:rs3131967
1 754503 rs3115859 G A . PASS . ES:SE:LP:SS:ID 0.0112:0.0094:0.629672:42220:rs3115859
1 754629 rs10454459 A G . PASS . ES:SE:LP:SS:ID -0.0294:0.0195:0.880744:39000:rs10454459
1 754964 rs3131966 C T . PASS . ES:SE:LP:SS:ID 0.0114:0.0094:0.647817:42220:rs3131966
1 755775 rs3131965 A G . PASS . ES:SE:LP:SS:ID 0.0107:0.0094:0.592439:42220:rs3131965
1 755890 rs1280367067 A T . PASS . ES:SE:LP:SS:ID 0.0087:0.0102:0.403293:41488:rs1280367067
1 756604 rs3131962 A G . PASS . ES:SE:LP:SS:ID 0.008:0.0102:0.363612:41488:rs3131962
1 757640 rs3115853 G A . PASS . ES:SE:LP:SS:ID 0.0091:0.0101:0.434506:41488:rs3115853
1 757734 rs1557551770 C T . PASS . ES:SE:LP:SS:ID 0.0084:0.0102:0.388808:41488:rs1557551770
1 757936 rs1360886751 C A . PASS . ES:SE:LP:SS:ID 0.0084:0.0102:0.388808:41488:rs1360886751
1 758144 rs3131956 A G . PASS . ES:SE:LP:SS:ID 0.0086:0.0102:0.399681:41488:rs3131956
1 758626 rs3131954 C T . PASS . ES:SE:LP:SS:ID 0.0088:0.0102:0.413638:41488:rs3131954
1 759036 rs114525117 G A . PASS . ES:SE:LP:SS:ID -0.0284:0.0196:0.834459:39000:rs114525117
1 760912 rs1048488 C T . PASS . ES:SE:LP:SS:ID 0.0122:0.0094:0.715344:42220:rs1048488