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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_20003_1140909786.vcf.gz --id UKB-b:17681 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20003_1140909786.txt.gz --cohort_cases 4209 --cohort_controls 458724 --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": "2019-09-13T04:26:28.018705",
"bcftools_viewVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
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"bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-17681/ukb-b-17681.vcf.gz; Date=Sun May 10 03:24:54 2020"
}
*********************************************************************
* 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-17681/UKB-b-17681_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17681/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/
Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17681/UKB-b-17681_data.vcf.gz ...
Read summary statistics for 4624542 SNPs.
Dropped 1115 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, 1060583 SNPs remain.
After merging with regression SNP LD, 1060583 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0046 (0.0011)
Lambda GC: 1.0361
Mean Chi^2: 1.0388
Intercept: 0.9938 (0.0082)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:41:15 2019
Total time elapsed: 56.51s
{
"af_correlation": 0.8967,
"inflation_factor": 1.0475,
"mean_EFFECT": -6.7251e-07,
"n": "-Inf",
"n_snps": 9851866,
"n_clumped_hits": 2,
"n_p_sig": 419,
"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": 38731,
"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": 1060583,
"ldsc_nsnp_merge_regression_ld": 1060583,
"ldsc_observed_scale_h2_beta": 0.0046,
"ldsc_observed_scale_h2_se": 0.0011,
"ldsc_intercept_beta": 0.9938,
"ldsc_intercept_se": 0.0082,
"ldsc_lambda_gc": 1.0361,
"ldsc_mean_chisq": 1.0388,
"ldsc_ratio": -0.1598
}
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 |
General metrics
af_correlation
: Correlation coefficient between AF
and AF_reference
.inflation_factor
(lambda
): Genomic inflation factor.mean_EFFECT
: Mean of EFFECT
size.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 below 5e-8
.n_mono
: Number of monomorphic (MAF == 1
or MAF == 0
) SNPs.n_ns
: Number of SNPs with nonsense values:
A, C, G or T
.< 0
or > 1
.<= 0
or = Infinity
).< 0
or > 1
.n_mac
: Number of cases where MAC
(\(2 \times N \times MAF\)) is less than 6
.is_snpid_unique
: true
if the combination of ID
REF
ALT
is unique and therefore no duplication in snpid.n_miss_<*>
: Number of NA
observations 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 expect ratio_se_n
to 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.
ratio_diff
: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff
and the mean of diff2
(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.
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.
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.
r2 metrics
Sum of variance explained, calculated from the clumped top hits sample.
r2_sum<*>
: r2
statistics under various assumptions
1
: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).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
: NOT is_snpid_unique
.mean_EFFECT_nonfinite
: mean(EFFECT)
is NA
, NaN
, or Inf
.mean_EFFECT_05
: abs(mean(EFFECT))
> 0.5.mean_EFFECT_01
: abs(mean(EFFECT))
> 0.1.mean_chisq
: ldsc_mean_chisq
> 1.3 or ldsc_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<*>
> 0.5Plots
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 | 4623436 | 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 | 4624542 | 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 | 8.663015e+00 | 5.766246e+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 | 7.856367e+07 | 5.671489e+07 | 828.0000000 | 3.176621e+07 | 6.888304e+07 | 1.146736e+08 | 2.492385e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -7.000000e-07 | 2.549000e-04 | -0.0017282 | -1.659000e-04 | -9.000000e-07 | 1.630000e-04 | 2.209800e-03 | ▁▃▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.446000e-04 | 4.590000e-05 | 0.0001904 | 2.053000e-04 | 2.288000e-04 | 2.748000e-04 | 6.963000e-04 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.928691e-01 | 2.902135e-01 | 0.0000000 | 2.399999e-01 | 4.899999e-01 | 7.400005e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.928729e-01 | 2.901873e-01 | 0.0000000 | 2.410499e-01 | 4.901095e-01 | 7.438692e-01 | 9.999998e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.676870e-01 | 2.301177e-01 | 0.0831560 | 1.685290e-01 | 3.086490e-01 | 5.319450e-01 | 9.168440e-01 | ▇▅▃▂▂ |
numeric | AF_reference | 38731 | 0.9916249 | NA | NA | NA | NA | NA | NA | NA | 3.595403e-01 | 2.290770e-01 | 0.0000000 | 1.705270e-01 | 3.089060e-01 | 5.209660e-01 | 1.000000e+00 | ▇▇▅▃▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 49298 | rs200943160 | T | C | -0.0002556 | 0.0003504 | 0.4700002 | 0.4656237 | 0.623763 | 0.7821490 | NA |
1 | 54676 | rs2462492 | C | T | 0.0002382 | 0.0003471 | 0.4899999 | 0.4926385 | 0.400401 | NA | NA |
1 | 86028 | rs114608975 | T | C | 0.0001168 | 0.0005550 | 0.8300000 | 0.8333770 | 0.103556 | 0.0277556 | NA |
1 | 91536 | rs6702460 | G | T | 0.0001539 | 0.0003418 | 0.6499995 | 0.6524039 | 0.456851 | 0.4207270 | NA |
1 | 534192 | rs6680723 | C | T | 0.0009192 | 0.0003904 | 0.0189998 | 0.0185463 | 0.240960 | NA | NA |
1 | 546697 | rs12025928 | A | G | 0.0003102 | 0.0004871 | 0.5199996 | 0.5241964 | 0.913473 | NA | NA |
1 | 693731 | rs12238997 | A | G | 0.0002221 | 0.0003272 | 0.5000000 | 0.4972712 | 0.116325 | 0.1417730 | NA |
1 | 706368 | rs55727773 | A | G | 0.0000670 | 0.0002424 | 0.7800007 | 0.7820737 | 0.515650 | 0.2751600 | NA |
1 | 722670 | rs116030099 | T | C | -0.0006564 | 0.0003999 | 0.1000000 | 0.1006785 | 0.101199 | 0.0413339 | NA |
1 | 729679 | rs4951859 | C | G | -0.0002000 | 0.0002835 | 0.4799997 | 0.4804747 | 0.843212 | 0.6399760 | NA |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
22 | 51198027 | rs34939255 | A | G | 0.0001780 | 0.0002417 | 0.4600002 | 0.4613952 | 0.254557 | 0.0984425 | NA |
22 | 51208537 | rs72619593 | G | A | 0.0001556 | 0.0003231 | 0.6300007 | 0.6300060 | 0.120739 | 0.1142170 | NA |
22 | 51210289 | rs112565862 | C | T | -0.0001400 | 0.0003218 | 0.6600001 | 0.6635934 | 0.129955 | 0.1018370 | NA |
22 | 51211106 | rs9628250 | T | C | 0.0000640 | 0.0002396 | 0.7899998 | 0.7895459 | 0.271547 | 0.1671330 | NA |
22 | 51211392 | rs3888396 | T | C | -0.0001233 | 0.0003189 | 0.6999999 | 0.6990713 | 0.132635 | 0.1641370 | NA |
22 | 51212875 | rs2238837 | A | C | -0.0000495 | 0.0002277 | 0.8300000 | 0.8280326 | 0.331455 | 0.3724040 | NA |
22 | 51213613 | rs34726907 | C | T | -0.0000052 | 0.0003000 | 0.9900000 | 0.9861239 | 0.127816 | 0.1727240 | NA |
22 | 51216564 | rs9616970 | T | C | 0.0000177 | 0.0002987 | 0.9500000 | 0.9527785 | 0.128330 | 0.1563500 | NA |
22 | 51219006 | rs28729663 | G | A | 0.0000831 | 0.0002924 | 0.7800007 | 0.7762799 | 0.137953 | 0.2052720 | NA |
22 | 51237063 | rs3896457 | T | C | -0.0000522 | 0.0002331 | 0.8200001 | 0.8228492 | 0.297971 | 0.2050720 | NA |
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