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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_101350.vcf.gz --id UKB-b:19806 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_101350.txt.gz --cohort_controls 64941 --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": "2019-09-13T15:42:07.141076",
"bcftools_viewVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
"bcftools_viewCommand": "view -T ^/mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19806/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19806/UKB-b-19806_raw.vcf.gz; Date=Thu Oct 17 12:38:12 2019",
"bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-19806/ukb-b-19806.vcf.gz; Date=Sat May 9 18:16:18 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-19806/UKB-b-19806_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19806/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/
Beginning analysis at Thu Oct 17 14:41:39 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19806/UKB-b-19806_data.vcf.gz ...
Read summary statistics for 8624955 SNPs.
Dropped 7372 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, 1285750 SNPs remain.
After merging with regression SNP LD, 1285750 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0005 (0.0065)
Lambda GC: 0.9932
Mean Chi^2: 0.9998
Intercept: 1.0004 (0.0061)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Thu Oct 17 14:43:21 2019
Total time elapsed: 1.0m:41.9s
{
"af_correlation": 0.9462,
"inflation_factor": 1,
"mean_EFFECT": -0,
"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": 83093,
"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": 1285750,
"ldsc_nsnp_merge_regression_ld": 1285750,
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": 1.0004,
"ldsc_intercept_se": 0.0061,
"ldsc_lambda_gc": 0.9932,
"ldsc_mean_chisq": 0.9998,
"ldsc_ratio": -2
}
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 | 1.000000 | 3 | 58 | 0 | 8617617 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
logical | N | 8624955 | 0.000000 | NA | NA | NA | NA | NA | NaN | : | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 8.650354e+00 | 5.760992e+00 | 1.0000000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
numeric | POS | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 7.876989e+07 | 5.637168e+07 | 828.0000000 | 3.238514e+07 | 6.929150e+07 | 1.145689e+08 | 2.492385e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | -1.740000e-05 | 7.811400e-03 | -0.0734403 | -3.273400e-03 | -3.880000e-05 | 3.184800e-03 | 9.669320e-02 | ▁▂▇▁▁ |
numeric | SE | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 6.465000e-03 | 4.413000e-03 | 0.0025677 | 3.023800e-03 | 4.458300e-03 | 8.739200e-03 | 4.426140e-02 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 5.007207e-01 | 2.889243e-01 | 0.0000001 | 2.500000e-01 | 5.000000e-01 | 7.499995e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 5.007202e-01 | 2.888979e-01 | 0.0000001 | 2.507113e-01 | 5.012926e-01 | 7.508161e-01 | 9.999998e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 2.291181e-01 | 2.594884e-01 | 0.0053900 | 2.519000e-02 | 1.138980e-01 | 3.626175e-01 | 9.946100e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 83093 | 0.990366 | NA | NA | NA | NA | NA | NA | NA | 2.288669e-01 | 2.514594e-01 | 0.0000000 | 2.316290e-02 | 1.303910e-01 | 3.596250e-01 | 1.000000e+00 | ▇▂▂▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 49298 | rs200943160 | T | C | -0.0046697 | 0.0047322 | 0.3200000 | 0.3237454 | 0.623813 | 0.7821490 | NA |
1 | 54676 | rs2462492 | C | T | -0.0016308 | 0.0047184 | 0.7300002 | 0.7296230 | 0.399145 | NA | NA |
1 | 86028 | rs114608975 | T | C | 0.0037496 | 0.0075107 | 0.6200004 | 0.6176152 | 0.103538 | 0.0277556 | NA |
1 | 91536 | rs6702460 | G | T | -0.0015817 | 0.0046409 | 0.7300002 | 0.7332415 | 0.455928 | 0.4207270 | NA |
1 | 234313 | rs8179466 | C | T | -0.0080881 | 0.0091774 | 0.3800004 | 0.3781554 | 0.074458 | NA | NA |
1 | 534192 | rs6680723 | C | T | 0.0053375 | 0.0052855 | 0.3100002 | 0.3125700 | 0.242064 | NA | NA |
1 | 546697 | rs12025928 | A | G | 0.0003709 | 0.0065590 | 0.9500000 | 0.9549052 | 0.912877 | NA | NA |
1 | 693731 | rs12238997 | A | G | 0.0006465 | 0.0044080 | 0.8800001 | 0.8833983 | 0.117291 | 0.1417730 | NA |
1 | 705882 | rs72631875 | G | A | -0.0050076 | 0.0064244 | 0.4400003 | 0.4357099 | 0.067691 | 0.0315495 | NA |
1 | 706368 | rs55727773 | A | G | 0.0002531 | 0.0032714 | 0.9400001 | 0.9383313 | 0.513307 | 0.2751600 | NA |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
22 | 51219006 | rs28729663 | G | A | 0.0009713 | 0.0039791 | 0.8100000 | 0.8071475 | 0.136297 | 0.2052720 | NA |
22 | 51219387 | rs9616832 | T | C | -0.0053998 | 0.0051863 | 0.2999998 | 0.2977958 | 0.071791 | 0.0654952 | NA |
22 | 51219704 | rs147475742 | G | A | -0.0053276 | 0.0068998 | 0.4400003 | 0.4400303 | 0.041180 | 0.0473243 | NA |
22 | 51221190 | rs369304721 | G | A | -0.0104126 | 0.0069482 | 0.1299999 | 0.1339742 | 0.048368 | NA | NA |
22 | 51221731 | rs115055839 | T | C | -0.0061542 | 0.0051875 | 0.2399999 | 0.2354836 | 0.071341 | 0.0625000 | NA |
22 | 51222100 | rs114553188 | G | T | 0.0106717 | 0.0060113 | 0.0759994 | 0.0758542 | 0.054840 | 0.0880591 | NA |
22 | 51223637 | rs375798137 | G | A | 0.0107761 | 0.0060427 | 0.0749998 | 0.0745338 | 0.054460 | 0.0788738 | NA |
22 | 51229805 | rs9616985 | T | C | -0.0067852 | 0.0052035 | 0.1900002 | 0.1922391 | 0.071246 | 0.0730831 | NA |
22 | 51232488 | rs376461333 | A | G | 0.0170690 | 0.0119853 | 0.1499999 | 0.1543998 | 0.020453 | NA | NA |
22 | 51237063 | rs3896457 | T | C | 0.0024955 | 0.0031412 | 0.4299995 | 0.4269399 | 0.298385 | 0.2050720 | NA |
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