Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

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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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10852/UKB-b-10852_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10852/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-10852/UKB-b-10852_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 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, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0015 (0.001)
Lambda GC: 1.0154
Mean Chi^2: 0.9845
Intercept: 0.9979 (0.0068)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Thu Oct 17 14:42:06 2019
Total time elapsed: 1.0m:47.84s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 0.8255,
    "mean_EFFECT": 7.1225e-09,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 120,
    "n_p_sig": 3040,
    "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": 184849,
    "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": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 0.9979,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.0154,
    "ldsc_mean_chisq": 0.9845,
    "ldsc_ratio": 0.1355
}

Flags

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 TRUE
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 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 SNPs
  • n_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:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 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.
    • \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
    • \({z}_j = \frac{\beta_j}{{se}_j}\),
    • 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 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.
    • \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
    • \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
  • 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<*>: 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 > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_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 0 1.0000000 3 58 0 9837196 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 9851866 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 8.622825e+00 5.748290e+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 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 0.000000e+00 6.810000e-05 -0.0029838 -1.380000e-05 5.800000e-06 4.570000e-05 2.144400e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.940000e-05 4.680000e-05 0.0000138 1.690000e-05 2.840000e-05 6.550000e-05 7.269000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 5.135076e-01 2.715269e-01 0.0000000 2.999998e-01 5.400003e-01 7.400005e-01 1.000000e+00 ▆▆▇▇▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 5.135071e-01 2.715035e-01 0.0000000 2.954297e-01 5.351501e-01 7.379140e-01 9.999996e-01 ▆▆▇▇▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035078e-01 2.568609e-01 0.0009990 1.316900e-02 7.791400e-02 3.164530e-01 9.990010e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-01 1.000000e+00 ▇▂▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C -6.09e-05 2.54e-05 0.0170000 0.0166223 0.623767 0.7821490 NA
1 54676 rs2462492 C T 2.52e-05 2.52e-05 0.3200000 0.3172011 0.400401 NA NA
1 86028 rs114608975 T C 6.28e-05 4.03e-05 0.1199999 0.1188670 0.103555 0.0277556 NA
1 91536 rs6702460 G T -1.64e-05 2.48e-05 0.5099998 0.5087358 0.456847 0.4207270 NA
1 234313 rs8179466 C T 7.00e-06 4.89e-05 0.8900000 0.8855997 0.074507 NA NA
1 534192 rs6680723 C T -1.20e-05 2.83e-05 0.6700003 0.6719045 0.240957 NA NA
1 546697 rs12025928 A G -4.39e-05 3.54e-05 0.2099999 0.2142193 0.913476 NA NA
1 693731 rs12238997 A G -2.11e-05 2.38e-05 0.3700002 0.3745744 0.116328 0.1417730 NA
1 705882 rs72631875 G A 3.82e-05 3.48e-05 0.2700001 0.2720155 0.067288 0.0315495 NA
1 706368 rs55727773 A G 3.12e-05 1.76e-05 0.0759994 0.0757653 0.515644 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 4.44e-05 0.0000369 0.2300001 0.2294553 0.041955 0.0473243 NA
22 51219766 rs182321900 C T 5.25e-05 0.0001720 0.7600007 0.7600855 0.001938 NA NA
22 51220146 rs868950473 C T 5.29e-05 0.0001704 0.7600007 0.7562272 0.001987 NA NA
22 51221190 rs369304721 G A 3.36e-05 0.0000369 0.3599996 0.3617654 0.049732 NA NA
22 51221731 rs115055839 T C 3.53e-05 0.0000276 0.2000000 0.2006037 0.073237 0.0625000 NA
22 51222100 rs114553188 G T 8.50e-06 0.0000325 0.7899998 0.7941412 0.054460 0.0880591 NA
22 51223637 rs375798137 G A 8.20e-06 0.0000326 0.8000000 0.8020310 0.054089 0.0788738 NA
22 51229805 rs9616985 T C 3.54e-05 0.0000277 0.2000000 0.2003642 0.073072 0.0730831 NA
22 51232488 rs376461333 A G 7.36e-05 0.0000652 0.2599998 0.2590078 0.020042 NA NA
22 51237063 rs3896457 T C -1.11e-05 0.0000169 0.5099998 0.5125108 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623767 ES:SE:LP:AF:ID  -6.09277e-05:2.544e-05:1.76955:0.623767:rs10399793
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1   91536   rs6702460   G   T   .   PASS    AF=0.456847 ES:SE:LP:AF:ID  -1.63982e-05:2.48154e-05:0.29243:0.456847:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074507 ES:SE:LP:AF:ID  7.03973e-06:4.89297e-05:0.05061:0.074507:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240957 ES:SE:LP:AF:ID  -1.20055e-05:2.83459e-05:0.173925:0.240957:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913476 ES:SE:LP:AF:ID  -4.39225e-05:3.5363e-05:0.677781:0.913476:rs12025928
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1   706368  rs12029736  A   G   .   PASS    AF=0.515644 ES:SE:LP:AF:ID  3.12481e-05:1.75966e-05:1.11919:0.515644:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033008 ES:SE:LP:AF:ID  -1.77729e-05:4.43593e-05:0.161151:0.033008:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036624 ES:SE:LP:AF:ID  -1.31851e-05:4.02937e-05:0.130768:0.036624:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03674  ES:SE:LP:AF:ID  -1.30545e-05:4.01412e-05:0.124939:0.03674:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036439 ES:SE:LP:AF:ID  -7.74714e-06:4.04309e-05:0.0705811:0.036439:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016409 ES:SE:LP:AF:ID  -7.35203e-05:6.22514e-05:0.619789:0.016409:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03698  ES:SE:LP:AF:ID  -1.30024e-05:3.9982e-05:0.124939:0.03698:rs116801199
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1   724849  rs12126395  C   A   .   PASS    AF=0.031449 ES:SE:LP:AF:ID  -0.000105725:6.97688e-05:0.886057:0.031449:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053255 ES:SE:LP:AF:ID  -9.99318e-05:5.54991e-05:1.14267:0.053255:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036593 ES:SE:LP:AF:ID  -1.35206e-05:4.01036e-05:0.130768:0.036593:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03691  ES:SE:LP:AF:ID  -1.29251e-05:3.97385e-05:0.130768:0.03691:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843204 ES:SE:LP:AF:ID  2.67303e-05:2.05864e-05:0.721246:0.843204:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055912 ES:SE:LP:AF:ID  -5.49822e-05:3.33327e-05:1.00436:0.055912:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122311 ES:SE:LP:AF:ID  -2.70728e-05:2.25336e-05:0.638272:0.122311:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025711 ES:SE:LP:AF:ID  3.08492e-05:5.54302e-05:0.236572:0.025711:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121553 ES:SE:LP:AF:ID  -2.73245e-05:2.25431e-05:0.638272:0.121553:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132334 ES:SE:LP:AF:ID  -2.38696e-05:2.22185e-05:0.552842:0.132334:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011133 ES:SE:LP:AF:ID  2.64867e-05:8.07869e-05:0.130768:0.011133:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005698 ES:SE:LP:AF:ID  -0.000141667:0.000104298:0.769551:0.005698:rs61770167
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1   746189  rs139221807 A   G   .   PASS    AF=0.001031 ES:SE:LP:AF:ID  6.82139e-05:0.00028685:0.091515:0.001031:rs139221807
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1   752566  rs3094315   G   A   .   PASS    AF=0.838945 ES:SE:LP:AF:ID  2.44588e-05:1.99366e-05:0.657577:0.838945:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838574 ES:SE:LP:AF:ID  2.43052e-05:1.99151e-05:0.657577:0.838574:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869776 ES:SE:LP:AF:ID  2.19135e-05:2.13696e-05:0.508638:0.869776:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129875 ES:SE:LP:AF:ID  -2.21589e-05:2.14134e-05:0.522879:0.129875:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037336 ES:SE:LP:AF:ID  -1.14048e-05:3.86695e-05:0.113509:0.037336:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037579 ES:SE:LP:AF:ID  -1.10418e-05:3.84252e-05:0.113509:0.037579:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869118 ES:SE:LP:AF:ID  2.15565e-05:2.13277e-05:0.508638:0.869118:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869216 ES:SE:LP:AF:ID  1.20358e-05:2.13362e-05:0.244125:0.869216:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037537 ES:SE:LP:AF:ID  -1.10847e-05:3.85914e-05:0.113509:0.037537:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869121 ES:SE:LP:AF:ID  2.15565e-05:2.13273e-05:0.508638:0.869121:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005121 ES:SE:LP:AF:ID  5.66811e-05:0.000109514:0.221849:0.005121:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005087 ES:SE:LP:AF:ID  5.65718e-05:0.000109801:0.21467:0.005087:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838027 ES:SE:LP:AF:ID  2.3957e-05:1.98598e-05:0.638272:0.838027:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03755  ES:SE:LP:AF:ID  -1.11022e-05:3.86459e-05:0.113509:0.03755:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838658 ES:SE:LP:AF:ID  2.41271e-05:1.99156e-05:0.638272:0.838658:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013772 ES:SE:LP:AF:ID  -0.000179708:6.9522e-05:2.01323:0.013772:rs181660517