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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_41229_5QD.vcf.gz --id UKB-b:10070 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_41229_5QD.txt.gz --cohort_cases 1070 --cohort_controls 461940 --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": "2019-09-13T07:02:47.370443",
"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-10070/ukb-b-10070.vcf.gz; Date=Sun May 10 14:55:15 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-10070/UKB-b-10070_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10070/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/
Beginning analysis at Thu Oct 17 14:40:20 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10070/UKB-b-10070_data.vcf.gz ...
Read summary statistics for 1548282 SNPs.
Dropped 139 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, 400099 SNPs remain.
After merging with regression SNP LD, 400099 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0015 (0.0013)
Lambda GC: 1.0439
Mean Chi^2: 1.0347
Intercept: 1.0181 (0.0103)
Ratio: 0.5226 (0.2966)
Analysis finished at Thu Oct 17 14:40:44 2019
Total time elapsed: 24.54s
{
"af_correlation": 0.6047,
"inflation_factor": 1.0475,
"mean_EFFECT": 4.81e-07,
"n": "-Inf",
"n_snps": 9851866,
"n_clumped_hits": 0,
"n_p_sig": 0,
"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": 12384,
"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": 400099,
"ldsc_nsnp_merge_regression_ld": 400099,
"ldsc_observed_scale_h2_beta": 0.0015,
"ldsc_observed_scale_h2_se": 0.0013,
"ldsc_intercept_beta": 1.0181,
"ldsc_intercept_se": 0.0103,
"ldsc_lambda_gc": 1.0439,
"ldsc_mean_chisq": 1.0347,
"ldsc_ratio": 0.5216
}
name | value |
---|---|
af_correlation | TRUE |
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 | TRUE |
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 | 4 | 58 | 0 | 1548145 | 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 | 1548282 | 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 | 8.671224e+00 | 5.766713e+00 | 1.00000e+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 | 7.858220e+07 | 5.657206e+07 | 1.23330e+04 | 3.171313e+07 | 6.909922e+07 | 1.145749e+08 | 2.491722e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.000000e-07 | 1.042000e-04 | -4.97600e-04 | -7.070000e-05 | 1.000000e-07 | 7.080000e-05 | 7.067000e-04 | ▁▆▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.024000e-04 | 2.800000e-06 | 9.63000e-05 | 1.005000e-04 | 1.018000e-04 | 1.039000e-04 | 1.904000e-04 | ▇▁▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.939898e-01 | 2.901238e-01 | 1.70000e-06 | 2.399999e-01 | 4.899999e-01 | 7.499995e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.939886e-01 | 2.900943e-01 | 1.70000e-06 | 2.417881e-01 | 4.898033e-01 | 7.450115e-01 | 9.999990e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.810428e-01 | 9.924750e-02 | 3.27103e-01 | 3.937900e-01 | 4.715120e-01 | 5.631980e-01 | 6.728960e-01 | ▇▇▆▅▅ |
numeric | AF_reference | 12384 | 0.9920015 | NA | NA | NA | NA | NA | NA | NA | 4.595812e-01 | 1.468808e-01 | 1.99700e-04 | 3.494410e-01 | 4.532750e-01 | 5.646960e-01 | 1.000000e+00 | ▁▆▇▃▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 49298 | rs200943160 | T | C | 0.0000873 | 0.0001772 | 0.6200004 | 0.6224064 | 0.623765 | 0.782149 | NA |
1 | 54676 | rs2462492 | C | T | -0.0004839 | 0.0001756 | 0.0059000 | 0.0058557 | 0.400401 | NA | NA |
1 | 91536 | rs6702460 | G | T | 0.0000258 | 0.0001729 | 0.8800001 | 0.8813364 | 0.456846 | 0.420727 | NA |
1 | 706368 | rs55727773 | A | G | 0.0000189 | 0.0001226 | 0.8800001 | 0.8774550 | 0.515645 | 0.275160 | NA |
1 | 814495 | rs74461805 | C | A | 0.0001502 | 0.0001681 | 0.3700002 | 0.3714523 | 0.340396 | NA | NA |
1 | 840753 | rs4970382 | T | C | 0.0000512 | 0.0001019 | 0.6200004 | 0.6150837 | 0.400124 | 0.468850 | NA |
1 | 843405 | rs11516185 | A | G | 0.0000934 | 0.0001265 | 0.4600002 | 0.4599424 | 0.362606 | 0.375399 | NA |
1 | 850218 | rs6664536 | T | A | 0.0000766 | 0.0001016 | 0.4500005 | 0.4508201 | 0.590331 | 0.345248 | NA |
1 | 850371 | rs6679046 | G | T | 0.0000591 | 0.0001021 | 0.5600000 | 0.5625433 | 0.603723 | 0.508786 | NA |
1 | 850780 | rs6657440 | C | T | 0.0000653 | 0.0001021 | 0.5199996 | 0.5225387 | 0.603942 | 0.560304 | NA |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
22 | 51158499 | rs8136930 | T | G | -0.0000255 | 0.0001002 | 0.8000000 | 0.7992092 | 0.461636 | 0.544728 | NA |
22 | 51161019 | rs5770994 | C | T | 0.0000921 | 0.0000999 | 0.3599996 | 0.3563498 | 0.482204 | 0.425719 | NA |
22 | 51163039 | rs715584 | G | T | -0.0001341 | 0.0001015 | 0.1900002 | 0.1863577 | 0.426975 | 0.473642 | NA |
22 | 51164109 | rs5770995 | G | C | -0.0000597 | 0.0001008 | 0.5500004 | 0.5541947 | 0.452705 | 0.510982 | NA |
22 | 51164115 | rs5770996 | C | T | -0.0000174 | 0.0001008 | 0.8600001 | 0.8629499 | 0.456917 | 0.514776 | NA |
22 | 51174048 | rs9628245 | G | C | 0.0001332 | 0.0001139 | 0.2399999 | 0.2420602 | 0.380135 | 0.433107 | NA |
22 | 51186143 | rs2879914 | T | C | -0.0000436 | 0.0001073 | 0.6800001 | 0.6848787 | 0.381825 | 0.273363 | NA |
22 | 51186228 | rs3865766 | C | T | -0.0000855 | 0.0001046 | 0.4100001 | 0.4139173 | 0.451061 | 0.453275 | NA |
22 | 51197266 | rs61290853 | A | G | -0.0001656 | 0.0001080 | 0.1299999 | 0.1251029 | 0.386333 | 0.422923 | NA |
22 | 51212875 | rs2238837 | A | C | -0.0001267 | 0.0001152 | 0.2700001 | 0.2712334 | 0.331457 | 0.372404 | NA |
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