no-intercept produces h2=4.84...

bulik / ldsc

LD Score Regression (LDSC)

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no-intercept produces h2=4.84... #35

Closed r03ert0 closed 9 years ago

r03ert0 commented 9 years ago

Hello, I'm analysing a quantitative trait (brain volume) in a population of unrelated subjects, controlled for population stratification, without genomic control. If I don't constraint the intercept, I obtain: h2=0.1743 (0.0527) but if I add the --no-intercept flag, then h2=4.8404 (0.0757) ! what can be the reason? thank you in advance!

bulik commented 9 years ago

Could you post the log file?

On Jun 23, 2015, at 6:05 PM, Roberto Toro notifications@github.com wrote:

Hello, I'm analysing a quantitative trait (brain volume) in a population of unrelated subjects, controlled for population stratification, without genomic control. If I don't constraint the intercept, I obtain: h2=0.1743 (0.0527) but if I add the --no-intercept flag, then h2=4.8404 (0.0757) ! what can be the reason? thank you in advance!

— Reply to this email directly or view it on GitHub.

r03ert0 commented 9 years ago

here it is:

LD Score Regression (LDSC)
Version 1.0.0
(C) 2014-2015 Brendan Bulik-Sullivan and Hilary Finucane
Broad Institute of MIT and Harvard / MIT Department of Mathematics
GNU General Public License v3

Options: --h2 ICV.sumstats.gz --ref-ld-chr LDSCORE/baseline. --out /Users/roberto/Desktop/ICV --no-intercept --w-ld-chr LDSCORE/weights.

Beginning analysis at Tue Jun 23 18:59:28 2015 Reading summary statistics from ICV.sumstats.gz ... Read summary statistics for 1068341 SNPs. Reading reference panel LD Score from LDSCORE/baseline.[1-22] ... Read reference panel LD Scores for 1189907 SNPs. Reading regression weight LD Score from LDSCORE/weights.[1-22] ... Read regression weight LD Scores for 1242190 SNPs. After merging with reference panel LD, 1066566 SNPs remain. After merging with regression SNP LD, 1063925 SNPs remain. Removed 0 SNPs with chi^2 > 80 (1063925 SNPs remain) Total Observed scale h2: 4.8408 (0.0757) Categories: base_0 Coding_UCSC_0 Coding_UCSC.extend.500_0 Conserved_LindbladToh_0 Conserved_LindbladToh.extend.500_0 CTCF_Hoffman_0 CTCF_Hoffman.extend.500_0 DGF_ENCODE_0 DGF_ENCODE.extend.500_0 DHS_peaks_Trynka_0 DHS_Trynka_0 DHS_Trynka.extend.500_0 Enhancer_Andersson_0 Enhancer_Andersson.extend.500_0 Enhancer_Hoffman_0 Enhancer_Hoffman.extend.500_0 FetalDHS_Trynka_0 FetalDHS_Trynka.extend.500_0 H3K27ac_Hnisz_0 H3K27ac_Hnisz.extend.500_0 H3K27ac_PGC2_0 H3K27ac_PGC2.extend.500_0 H3K4me1_peaks_Trynka_0 H3K4me1_Trynka_0 H3K4me1_Trynka.extend.500_0 H3K4me3_peaks_Trynka_0 H3K4me3_Trynka_0 H3K4me3_Trynka.extend.500_0 H3K9ac_peaks_Trynka_0 H3K9ac_Trynka_0 H3K9ac_Trynka.extend.500_0 Intron_UCSC_0 Intron_UCSC.extend.500_0 PromoterFlanking_Hoffman_0 PromoterFlanking_Hoffman.extend.500_0 Promoter_UCSC_0 Promoter_UCSC.extend.500_0 Repressed_Hoffman_0 Repressed_Hoffman.extend.500_0 SuperEnhancer_Hnisz_0 SuperEnhancer_Hnisz.extend.500_0 TFBS_ENCODE_0 TFBS_ENCODE.extend.500_0 Transcribed_Hoffman_0 Transcribed_Hoffman.extend.500_0 TSS_Hoffman_0 TSS_Hoffman.extend.500_0 UTR_3_UCSC_0 UTR_3_UCSC.extend.500_0 UTR_5_UCSC_0 UTR_5_UCSC.extend.500_0 WeakEnhancer_Hoffman_0 WeakEnhancer_Hoffman.extend.500_0 Observed scale h2: -1.3225 -0.0512 0.1766 0.3732 -0.0918 -0.2027 0.6231 -0.4405 0.9919 -0.1491 -0.1309 1.6781 -0.0649 0.1261 -0.0583 -0.4509 -0.0691 1.6653 0.8158 -0.9677 0.1593 -0.4617 0.3165 -1.0034 2.1976 0.0843 0.2893 -0.3945 0.1875 -0.8899 0.7366 -1.5568 1.4326 -0.1068 -0.0724 0.115 -0.0948 0.4398 0.1164 0.4274 -0.257 0.7446 -0.1407 -1.1031 0.8978 -0.1034 0.145 0.047 -0.0524 0.0414 -0.1579 0.1799 0.227 Observed scale h2 SE: 0.6792 0.0593 0.0981 0.0784 0.1786 0.0887 0.12 0.2334 0.3914 0.28 0.3406 0.4296 0.0384 0.056 0.1565 0.2525 0.2 0.2808 0.7109 0.7766 0.4399 0.4795 0.2398 0.5244 0.5317 0.1092 0.2069 0.2642 0.1088 0.2267 0.2697 1.8905 1.9415 0.0455 0.0684 0.1913 0.1988 0.4135 0.5323 1.0544 1.0665 0.2324 0.3375 0.274 0.5095 0.0842 0.1004 0.0431 0.0526 0.0253 0.0503 0.072 0.1564 Proportion of SNPs: 0.0886 0.0013 0.0057 0.0023 0.0295 0.0021 0.0063 0.0122 0.048 0.0099 0.0149 0.0442 0.0004 0.0017 0.0056 0.0136 0.0075 0.0252 0.0347 0.0374 0.0239 0.0298 0.0152 0.0378 0.054 0.0037 0.0118 0.0226 0.0034 0.0112 0.0204 0.0343 0.0352 0.0007 0.003 0.0028 0.0034 0.0409 0.0637 0.0149 0.0152 0.0117 0.0304 0.0306 0.0676 0.0016 0.0031 0.001 0.0024 0.0005 0.0025 0.0019 0.0079 Proportion of h2g: -0.2732 -0.0106 0.0365 0.0771 -0.019 -0.0419 0.1287 -0.091 0.2049 -0.0308 -0.027 0.3467 -0.0134 0.026 -0.012 -0.0932 -0.0143 0.344 0.1685 -0.1999 0.0329 -0.0954 0.0654 -0.2073 0.454 0.0174 0.0598 -0.0815 0.0387 -0.1838 0.1522 -0.3216 0.2959 -0.0221 -0.015 0.0238 -0.0196 0.0908 0.024 0.0883 -0.0531 0.1538 -0.0291 -0.2279 0.1855 -0.0214 0.0299 0.0097 -0.0108 0.0085 -0.0326 0.0372 0.0469 Enrichment: -3.0838 -8.1403 6.3791 33.3916 -0.6441 -19.8315 20.4461 -7.4657 4.2714 -3.1101 -1.8199 7.8455 -34.9244 15.4148 -2.1455 -6.8312 -1.902 13.625 4.8632 -5.3398 1.3781 -3.2036 4.3086 -5.4853 8.4123 4.7057 5.0607 -3.6004 11.2781 -16.4551 7.4493 -9.3693 8.4117 -29.5413 -5.0449 8.6061 -5.7226 2.2234 0.3775 5.9178 -3.492 13.1093 -0.9551 -7.4468 2.7437 -13.2383 9.7065 9.9235 -4.5408 17.7907 -13.2438 19.8895 5.9516 Coefficients: -2.2314e-07 -5.8902e-07 4.6158e-07 2.4162e-06 -4.6606e-08 -1.4350e-06 1.4795e-06 -5.4021e-07 3.0908e-07 -2.2504e-07 -1.3169e-07 5.6769e-07 -2.5271e-06 1.1154e-06 -1.5525e-07 -4.9430e-07 -1.3763e-07 9.8589e-07 3.5189e-07 -3.8638e-07 9.9721e-08 -2.3181e-07 3.1177e-07 -3.9691e-07 6.0871e-07 3.4050e-07 3.6619e-07 -2.6052e-07 8.1607e-07 -1.1907e-06 5.3902e-07 -6.7795e-07 6.0866e-07 -2.1376e-06 -3.6504e-07 6.2273e-07 -4.1408e-07 1.6088e-07 2.7316e-08 4.2821e-07 -2.5268e-07 9.4858e-07 -6.9110e-08 -5.3884e-07 1.9853e-07 -9.5790e-07 7.0235e-07 7.1805e-07 -3.2857e-07 1.2873e-06 -9.5831e-07 1.4392e-06 4.3065e-07 Coefficient SE: 1.1461e-07 6.8259e-07 2.5644e-07 5.0761e-07 9.0636e-08 6.2835e-07 2.8488e-07 2.8620e-07 1.2195e-07 4.2264e-07 3.4259e-07 1.4534e-07 1.4962e-06 4.9562e-07 4.1695e-07 2.7677e-07 3.9807e-07 1.6623e-07 3.0665e-07 3.1010e-07 2.7546e-07 2.4078e-07 2.3617e-07 2.0742e-07 1.4727e-07 4.4088e-07 2.6193e-07 1.7446e-07 4.7360e-07 3.0327e-07 1.9732e-07 8.2329e-07 8.2489e-07 9.1150e-07 3.4493e-07 1.0360e-06 8.6858e-07 1.5126e-07 1.2491e-07 1.0563e-06 1.0487e-06 2.9609e-07 1.6581e-07 1.3384e-07 1.1267e-07 7.8025e-07 4.8667e-07 6.5800e-07 3.2933e-07 7.8755e-07 3.0539e-07 5.7599e-07 2.9661e-07 Lambda GC: 1.0527 Mean Chi^2: 1.0576 Intercept: constrained to 1 Analysis finished at Tue Jun 23 19:00:29 2015 Total time elapsed: 1.0m:0.4s

hilaryfinucane commented 9 years ago

Could you also post the log file from the analysis where the heritability estimate was smaller?

Also, what is your sample size?

Best,

Hilary

On Wed, Jun 24, 2015 at 11:50 AM, Roberto Toro notifications@github.com wrote:

here it is:

LD Score Regression (LDSC)

Version 1.0.0

(C) 2014-2015 Brendan Bulik-Sullivan and Hilary Finucane

Broad Institute of MIT and Harvard / MIT Department of Mathematics

GNU General Public License v3

Options: --h2 ICV.sumstats.gz --ref-ld-chr LDSCORE/baseline. --out /Users/roberto/Desktop/ICV --no-intercept --w-ld-chr LDSCORE/weights.

Beginning analysis at Tue Jun 23 18:59:28 2015 Reading summary statistics from ICV.sumstats.gz ... Read summary statistics for 1068341 SNPs. Reading reference panel LD Score from LDSCORE/baseline.[1-22] ... Read reference panel LD Scores for 1189907 SNPs. Reading regression weight LD Score from LDSCORE/weights.[1-22] ... Read regression weight LD Scores for 1242190 SNPs. After merging with reference panel LD, 1066566 SNPs remain. After merging with regression SNP LD, 1063925 SNPs remain. Removed 0 SNPs with chi^2 > 80 (1063925 SNPs remain) Total Observed scale h2: 4.8408 (0.0757) Categories: base_0 Coding_UCSC_0 Coding_UCSC.extend.500_0 Conserved_LindbladToh_0 Conserved_LindbladToh.extend.500_0 CTCF_Hoffman_0 CTCF_Hoffman.extend.500_0 DGF_ENCODE_0 DGF_ENCODE.extend.500_0 DHS_peaks_Trynka_0 DHS_Trynka_0 DHS_Trynka.extend.500_0 Enhancer_Andersson_0 Enhancer_Andersson.extend.500_0 Enhancer_Hoffman_0 Enhancer_Hoffman.extend.500_0 FetalDHS_Trynka_0 FetalDHS_Trynka.extend.500_0 H3K27ac_Hnisz_0 H3K27ac_Hnisz.extend.500_0 H3K27ac_PGC2_0 H3K27ac_PGC2.extend.500_0 H3K4me1_peaks_Trynka_0 H3K4me1_Trynka_0 H3K4me1_Trynka.extend.500_0 H3K4me3_peaks_Trynka_0 H3K4me3_Trynka_0 H3K4me3_Trynka.extend.500_0 H3K9ac_peaks_Trynka_0 H3K9ac_Trynka_0 H3K9ac_Trynka.extend.500_0 Intron_UCSC_0 Intron_UCSC.extend.500_0 PromoterFlanking_Hoffman_0 PromoterFlanking_Hoffman.extend.500_0 Promoter_UCSC_0 Promoter_UCSC.extend.500_0 Repressed_Hoffman_0 Repressed_Hoffman.extend.500_0 SuperEnhancer_Hnisz_0 SuperEnhancer_Hnisz.extend.500_0 TFBS_ENCODE_0 TFBS_ENCODE.extend.500_0 Transcribed_Hoffman_0 Transcribed_Hoffman.extend.500_0 TSS_Hoffman_0 TSS_Hoffman.extend.500_0 UTR_3_UCSC_0 UTR_3_UCSC.extend.500_0 UTR_5_UCSC_0 UTR_5_UCSC.extend.500_0 WeakEnhancer_Hoffman_0 WeakEnhancer_Hoffman.extend.500_0 Observed scale h2: -1.3225 -0.0512 0.1766 0.3732 -0.0918 -0.2027 0.6231 -0.4405 0.9919 -0.1491 -0.1309 1.6781 -0.0649 0.1261 -0.0583 -0.4509 -0.0691 1.6653 0.8158 -0.9677 0.1593 -0.4617 0.3165 -1.0034 2.1976 0.0843 0.2893 -0.3945 0.1875 -0.8899 0.7366 -1.5568 1.4326 -0.1068 -0.0724 0.115 -0.0948 0.4398 0.1164 0.4274 -0.257 0.7446 -0.1407 -1.1031 0.8978 -0.1034 0.145 0.047 -0.0524 0.0414 -0.1579 0.1799 0.227 Observed scale h2 SE: 0.6792 0.0593 0.0981 0.0784 0.1786 0.0887 0.12 0.2334 0.3914 0.28 0.3406 0.4296 0.0384 0.056 0.1565 0.2525 0.2 0.2808 0.7109 0.7766 0.4399 0.4795 0.2398 0.5244 0.5317 0.1092 0.2069 0.2642 0.1088 0.2267 0.2697 1.8905 1.9415 0.0455 0.0684 0.1913 0.1988 0.4135 0.5323 1.0544 1.0665 0.2324 0.3375 0.274 0.5095 0.0842 0.1004 0.0431 0.0526 0.0253 0.0503 0.072 0.1564 Proportion of SNPs: 0.0886 0.0013 0.0057 0.0023 0.0295 0.0021 0.0063 0.0122 0.048 0.0099 0.0149 0.0442 0.0004 0.0017 0.0056 0.0136 0.0075 0.0252 0.0347 0.0374 0.0239 0.0298 0.0152 0.0378 0.054 0.0037 0.0118 0.0226 0.0034 0.0112 0.0204 0.0343 0.0352 0.0007 0.003 0.0028 0.0034 0.0409 0.0637 0.0149 0.0152 0.0117 0.0304 0.0306 0.0676 0.0016 0.0031 0.001 0.0024 0.0005 0.0025 0.0019 0.0079 Proportion of h2g: -0.2732 -0.0106 0.0365 0.0771 -0.019 -0.0419 0.1287 -0.091 0.2049 -0.0308 -0.027 0.3467 -0.0134 0.026 -0.012 -0.0932 -0.0143 0.344 0.1685 -0.1999 0.0329 -0.0954 0.0654 -0.2073 0.454 0.0174 0.0598 -0.0815 0.0387 -0.1838 0.1522 -0.3216 0.2959 -0.0221 -0.015 0.0238 -0.0196 0.0908 0.024 0.0883 -0.0531 0.1538 -0.0291 -0.2279 0.1855 -0.0214 0.0299 0.0097 -0.0108 0.0085 -0.0326 0.0372 0.0469 Enrichment: -3.0838 -8.1403 6.3791 33.3916 -0.6441 -19.8315 20.4461 -7.4657 4.2714 -3.1101 -1.8199 7.8455 -34.9244 15.4148 -2.1455 -6.8312 -1.902 13.625 4.8632 -5.3398 1.3781 -3.2036 4.3086 -5.4853 8.4123 4.7057 5.0607 -3.6004 11.2781 -16.4551 7.4493 -9.3693 8.4117 -29.5413 -5.0449 8.6061 -5.7226 2.2234 0.3775 5.9178 -3.492 13.1093 -0.9551 -7.4468 2.7437 -13.2383 9.7065 9.9235 -4.5408 17.7907 -13.2438 19.8895 5.9516 Coefficients: -2.2314e-07 -5.8902e-07 4.6158e-07 2.4162e-06 -4.6606e-08 -1.4350e-06 1.4795e-06 -5.4021e-07 3.0908e-07 -2.2504e-07 -1.3169e-07 5.6769e-07 -2.5271e-06 1.1154e-06 -1.5525e-07 -4.9430e-07 -1.3763e-07 9.8589e-07 3.5189e-07 -3.8638e-07 9.9721e-08 -2.3181e-07 3.1177e-07 -3.9691e-07 6.0871e-07 3.4050e-07 3.6619e-07 -2.6052e-07 8.1607e-07 -1.1907e-06 5.3902e-07 -6.7795e-07 6.0866e-07 -2.1376e-06 -3.6504e-07 6.2273e-07 -4.1408e-07 1.6088e-07 2.7316e-08 4.2821e-07 -2.5268e-07 9.4858e-07 -6.9110e-08 -5.3884e-07 1.9853e-07 -9.5790e-07 7.0235e-07 7.1805e-07 -3.2857e-07 1.2873e-06 -9.5831e-07 1.4392e-06 4.3065e-07 Coefficient SE: 1.1461e-07 6.8259e-07 2.5644e-07 5.0761e-07 9.0636e-08 6.2835e-07 2.8488e-07 2.8620e-07 1.2195e-07 4.2264e-07 3.4259e-07 1.4534e-07 1.4962e-06 4.9562e-07 4.1695e-07 2.7677e-07 3.9807e-07 1.6623e-07 3.0665e-07 3.1010e-07 2.7546e-07 2.4078e-07 2.3617e-07 2.0742e-07 1.4727e-07 4.4088e-07 2.6193e-07 1.7446e-07 4.7360e-07 3.0327e-07 1.9732e-07 8.2329e-07 8.2489e-07 9.1150e-07 3.4493e-07 1.0360e-06 8.6858e-07 1.5126e-07 1.2491e-07 1.0563e-06 1.0487e-06 2.9609e-07 1.6581e-07 1.3384e-07 1.1267e-07 7.8025e-07 4.8667e-07 6.5800e-07 3.2933e-07 7.8755e-07 3.0539e-07 5.7599e-07 2.9661e-07 Lambda GC: 1.0527 Mean Chi^2: 1.0576 Intercept: constrained to 1 Analysis finished at Tue Jun 23 19:00:29 2015 Total time elapsed: 1.0m:0.4s

— Reply to this email directly or view it on GitHub https://github.com/bulik/ldsc/issues/35#issuecomment-114922487.

r03ert0 commented 9 years ago

Hi Hilary, here's the log of the run without constrained intercept. sample size: 11,373 subjects thank you! roberto (also, 'ratio' is very high for ICV, ~30%, however, I also obtain h2~4 for other phenotypes where ratio<20%)

LD Score Regression (LDSC)
Version 1.0.0
(C) 2014-2015 Brendan Bulik-Sullivan and Hilary Finucane
Broad Institute of MIT and Harvard / MIT Department of Mathematics
GNU General Public License v3

Options: --h2 ICV.sumstats.gz --ref-ld-chr LDSCORE/baseline. --out /Users/roberto/Desktop/ICV --w-ld-chr LDSCORE/weights.

Beginning analysis at Tue Jun 23 18:56:16 2015 Reading summary statistics from ICV.sumstats.gz ... Read summary statistics for 1068341 SNPs. Reading reference panel LD Score from LDSCORE/baseline.[1-22] ... Read reference panel LD Scores for 1189907 SNPs. Reading regression weight LD Score from LDSCORE/weights.[1-22] ... Read regression weight LD Scores for 1242190 SNPs. After merging with reference panel LD, 1066566 SNPs remain. After merging with regression SNP LD, 1063925 SNPs remain. Removed 0 SNPs with chi^2 > 80 (1063925 SNPs remain) Total Observed scale h2: 0.1743 (0.0527) Categories: base_0 Coding_UCSC_0 Coding_UCSC.extend.500_0 Conserved_LindbladToh_0 Conserved_LindbladToh.extend.500_0 CTCF_Hoffman_0 CTCF_Hoffman.extend.500_0 DGF_ENCODE_0 DGF_ENCODE.extend.500_0 DHS_peaks_Trynka_0 DHS_Trynka_0 DHS_Trynka.extend.500_0 Enhancer_Andersson_0 Enhancer_Andersson.extend.500_0 Enhancer_Hoffman_0 Enhancer_Hoffman.extend.500_0 FetalDHS_Trynka_0 FetalDHS_Trynka.extend.500_0 H3K27ac_Hnisz_0 H3K27ac_Hnisz.extend.500_0 H3K27ac_PGC2_0 H3K27ac_PGC2.extend.500_0 H3K4me1_peaks_Trynka_0 H3K4me1_Trynka_0 H3K4me1_Trynka.extend.500_0 H3K4me3_peaks_Trynka_0 H3K4me3_Trynka_0 H3K4me3_Trynka.extend.500_0 H3K9ac_peaks_Trynka_0 H3K9ac_Trynka_0 H3K9ac_Trynka.extend.500_0 Intron_UCSC_0 Intron_UCSC.extend.500_0 PromoterFlanking_Hoffman_0 PromoterFlanking_Hoffman.extend.500_0 Promoter_UCSC_0 Promoter_UCSC.extend.500_0 Repressed_Hoffman_0 Repressed_Hoffman.extend.500_0 SuperEnhancer_Hnisz_0 SuperEnhancer_Hnisz.extend.500_0 TFBS_ENCODE_0 TFBS_ENCODE.extend.500_0 Transcribed_Hoffman_0 Transcribed_Hoffman.extend.500_0 TSS_Hoffman_0 TSS_Hoffman.extend.500_0 UTR_3_UCSC_0 UTR_3_UCSC.extend.500_0 UTR_5_UCSC_0 UTR_5_UCSC.extend.500_0 WeakEnhancer_Hoffman_0 WeakEnhancer_Hoffman.extend.500_0 Observed scale h2: -0.1019 -0.0477 0.1277 0.1067 -0.0816 -0.1363 0.2713 -0.0062 0.3536 0.0616 -0.1858 0.1957 -0.0266 -0.0148 -0.0211 -0.2937 -0.173 -0.1533 0.1698 -0.2379 0.2707 -0.3084 0.2828 0.0225 -0.08 -0.1075 0.2689 -0.2008 0.0978 -0.3781 0.4716 0.7258 -0.7615 -0.0388 0.0513 0.0727 -0.0733 0.0459 0.0719 0.386 -0.3124 0.5836 -0.5835 0.126 -0.2301 0.0385 -0.0016 0.0104 -0.0499 0.0109 -0.0767 -0.0318 0.0649 Observed scale h2 SE: 0.2861 0.043 0.0669 0.0492 0.1028 0.0708 0.1019 0.1824 0.2843 0.2147 0.2671 0.3462 0.0304 0.0424 0.124 0.1894 0.1599 0.2311 0.625 0.6795 0.3655 0.3928 0.1959 0.372 0.3667 0.0833 0.1554 0.1771 0.0838 0.174 0.1983 1.279 1.307 0.0358 0.055 0.1469 0.154 0.2198 0.3235 0.8178 0.8312 0.1742 0.2457 0.1571 0.2766 0.0658 0.0759 0.0403 0.0396 0.0216 0.0377 0.0559 0.0981 Proportion of SNPs: 0.0886 0.0013 0.0057 0.0023 0.0295 0.0021 0.0063 0.0122 0.048 0.0099 0.0149 0.0442 0.0004 0.0017 0.0056 0.0136 0.0075 0.0252 0.0347 0.0374 0.0239 0.0298 0.0152 0.0378 0.054 0.0037 0.0118 0.0226 0.0034 0.0112 0.0204 0.0343 0.0352 0.0007 0.003 0.0028 0.0034 0.0409 0.0637 0.0149 0.0152 0.0117 0.0304 0.0306 0.0676 0.0016 0.0031 0.001 0.0024 0.0005 0.0025 0.0019 0.0079 Proportion of h2g: -0.5843 -0.2737 0.7326 0.6122 -0.4683 -0.7816 1.5562 -0.0354 2.0285 0.3533 -1.0659 1.1224 -0.1528 -0.0849 -0.1212 -1.6849 -0.9925 -0.8794 0.9743 -1.3647 1.5526 -1.7689 1.6222 0.1292 -0.4591 -0.6166 1.5424 -1.1517 0.5608 -2.1687 2.7054 4.1634 -4.3681 -0.2223 0.2945 0.4171 -0.4207 0.2631 0.4123 2.2143 -1.792 3.3475 -3.3473 0.7229 -1.3199 0.2209 -0.009 0.0595 -0.2863 0.0625 -0.4398 -0.1824 0.3721 Enrichment: -6.5956 -210.7377 128.0999 265.1679 -15.8969 -370.2442 247.2068 -2.9016 42.285 35.6804 -71.7216 25.4009 -397.769 -50.28 -21.605 -123.557 -132.1794 -34.8281 28.115 -36.4527 65.0384 -59.4223 106.8863 3.4191 -8.5072 -166.5447 130.6022 -50.8849 163.2844 -194.1202 132.441 121.2958 -124.16 -297.8092 99.3275 151.0758 -122.9295 6.4398 6.472 148.4129 -117.8779 285.2906 -110.016 23.6224 -19.5257 136.8614 -2.9197 60.7634 -120.0043 130.0739 -178.5434 -97.6117 47.218 Coefficients: -1.7187e-08 -5.4916e-07 3.3381e-07 6.9100e-07 -4.1425e-08 -9.6481e-07 6.4419e-07 -7.5612e-09 1.1019e-07 9.2979e-08 -1.8690e-07 6.6192e-08 -1.0365e-06 -1.3102e-07 -5.6300e-08 -3.2197e-07 -3.4444e-07 -9.0758e-08 7.3264e-08 -9.4991e-08 1.6948e-07 -1.5485e-07 2.7853e-07 8.9097e-09 -2.2169e-08 -4.3400e-07 3.4033e-07 -1.3260e-07 4.2550e-07 -5.0585e-07 3.4513e-07 3.1608e-07 -3.2355e-07 -7.7605e-07 2.5884e-07 3.9369e-07 -3.2034e-07 1.6781e-08 1.6865e-08 3.8675e-07 -3.0718e-07 7.4343e-07 -2.8669e-07 6.1557e-08 -5.0882e-08 3.5664e-07 -7.6084e-09 1.5834e-07 -3.1272e-07 3.3896e-07 -4.6526e-07 -2.5436e-07 1.2304e-07 Coefficient SE: 4.8268e-08 4.9468e-07 1.7489e-07 3.1840e-07 5.2170e-08 5.0154e-07 2.4193e-07 2.2372e-07 8.8580e-08 3.2415e-07 2.6869e-07 1.1712e-07 1.1838e-06 3.7496e-07 3.3034e-07 2.0758e-07 3.1836e-07 1.3681e-07 2.6961e-07 2.7131e-07 2.2888e-07 1.9725e-07 1.9291e-07 1.4714e-07 1.0157e-07 3.3631e-07 1.9666e-07 1.1699e-07 3.6457e-07 2.3277e-07 1.4513e-07 5.5699e-07 5.5531e-07 7.1628e-07 2.7743e-07 7.9559e-07 6.7264e-07 8.0424e-08 7.5921e-08 8.1931e-07 8.1724e-07 2.2196e-07 1.2069e-07 7.6765e-08 6.1171e-08 6.0979e-07 3.6773e-07 6.1534e-07 2.4824e-07 6.7338e-07 2.2868e-07 4.4752e-07 1.8598e-07 Lambda GC: 1.0527 Mean Chi^2: 1.0576 Intercept: 1.0175 (0.008) Ratio: 0.3036 (0.138) Analysis finished at Tue Jun 23 18:57:17 2015 Total time elapsed: 1.0m:0.6s

hilaryfinucane commented 9 years ago

Okay, a few more questions:

(1) It looks like you might be using an older version. Could you try git pull and check that that doesn't fix the problem? (2) Was there any custom array data in the dataset? (3) Could you run the analysis with --ref-ld-chr weights. instead of --ref-ld-chr baseline. and send me the log files with and w/o intercept?

Thanks,

Hilary

On Wed, Jun 24, 2015 at 4:15 PM, Roberto Toro notifications@github.com wrote:

Hi Hilary, here's the log of the run without constrained intercept. sample size: 11,373 subjects thank you! roberto (also, 'ratio' is very high for ICV, ~30%, however, I also obtain h2~4 for

other phenotypes where ratio<20%)

LD Score Regression (LDSC)

Version 1.0.0

(C) 2014-2015 Brendan Bulik-Sullivan and Hilary Finucane

Broad Institute of MIT and Harvard / MIT Department of Mathematics

GNU General Public License v3

Options: --h2 ICV.sumstats.gz --ref-ld-chr LDSCORE/baseline. --out /Users/roberto/Desktop/ICV --w-ld-chr LDSCORE/weights.

Beginning analysis at Tue Jun 23 18:56:16 2015 Reading summary statistics from ICV.sumstats.gz ... Read summary statistics for 1068341 SNPs. Reading reference panel LD Score from LDSCORE/baseline.[1-22] ... Read reference panel LD Scores for 1189907 SNPs. Reading regression weight LD Score from LDSCORE/weights.[1-22] ... Read regression weight LD Scores for 1242190 SNPs. After merging with reference panel LD, 1066566 SNPs remain. After merging with regression SNP LD, 1063925 SNPs remain. Removed 0 SNPs with chi^2 > 80 (1063925 SNPs remain) Total Observed scale h2: 0.1743 (0.0527) Categories: base_0 Coding_UCSC_0 Coding_UCSC.extend.500_0 Conserved_LindbladToh_0 Conserved_LindbladToh.extend.500_0 CTCF_Hoffman_0 CTCF_Hoffman.extend.500_0 DGF_ENCODE_0 DGF_ENCODE.extend.500_0 DHS_peaks_Trynka_0 DHS_Trynka_0 DHS_Trynka.extend.500_0 Enhancer_Andersson_0 Enhancer_Andersson.extend.500_0 Enhancer_Hoffman_0 Enhancer_Hoffman.extend.500_0 FetalDHS_Trynka_0 FetalDHS_Trynka.extend.500_0 H3K27ac_Hnisz_0 H3K27ac_Hnisz.extend.500_0 H3K27ac_PGC2_0 H3K27ac_PGC2.extend.500_0 H3K4me1_peaks_Trynka_0 H3K4me1_Trynka_0 H3K4me1_Trynka.extend.500_0 H3K4me3_peaks_Trynka_0 H3K4me3_Trynka_0 H3K4me3_Trynka.extend.500_0 H3K9ac_peaks_Trynka_0 H3K9ac_Trynka_0 H3K9ac_Trynka.extend.500_0 Intron_UCSC_0 Intron_UCSC.extend.500_0 PromoterFlanking_Hoffman_0 PromoterFlanking_Hoffman.extend.500_0 Promoter_UCSC_0 Promoter_UCSC.extend.500_0 Repressed_Hoffman_0 Repressed_Hoffman.extend.500_0 SuperEnhancer_Hnisz_0 SuperEnhancer_Hnisz.extend.500_0 TFBS_ENCODE_0 TFBS_ENCODE.extend.500_0 Transcribed_Hoffman_0 Transcribed_Hoffman.extend.500_0 TSS_Hoffman_0 TSS_Hoffman.extend.500_0 UTR_3_UCSC_0 UTR_3_UCSC.extend.500_0 UTR_5_UCSC_0 UTR_5_UCSC.extend.500_0 WeakEnhancer_Hoffman_0 WeakEnhancer_Hoffman.extend.500_0 Observed scale h2: -0.1019 -0.0477 0.1277 0.1067 -0.0816 -0.1363 0.2713 -0.0062 0.3536 0.0616 -0.1858 0.1957 -0.0266 -0.0148 -0.0211 -0.2937 -0.173 -0.1533 0.1698 -0.2379 0.2707 -0.3084 0.2828 0.0225 -0.08 -0.1075 0.2689 -0.2008 0.0978 -0.3781 0.4716 0.7258 -0.7615 -0.0388 0.0513 0.0727 -0.0733 0.0459 0.0719 0.386 -0.3124 0.5836 -0.5835 0.126 -0.2301 0.0385 -0.0016 0.0104 -0.0499 0.0109 -0.0767 -0.0318 0.0649 Observed scale h2 SE: 0.2861 0.043 0.0669 0.0492 0.1028 0.0708 0.1019 0.1824 0.2843 0.2147 0.2671 0.3462 0.0304 0.0424 0.124 0.1894 0.1599 0.2311 0.625 0.6795 0.3655 0.3928 0.1959 0.372 0.3667 0.0833 0.1554 0.1771 0.0838 0.174 0.1983 1.279 1.307 0.0358 0.055 0.1469 0.154 0.2198 0.3235 0.8178 0.8312 0.1742 0.2457 0.1571 0.2766 0.0658 0.0759 0.0403 0.0396 0.0216 0.0377 0.0559 0.0981 Proportion of SNPs: 0.0886 0.0013 0.0057 0.0023 0.0295 0.0021 0.0063 0.0122 0.048 0.0099 0.0149 0.0442 0.0004 0.0017 0.0056 0.0136 0.0075 0.0252 0.0347 0.0374 0.0239 0.0298 0.0152 0.0378 0.054 0.0037 0.0118 0.0226 0.0034 0.0112 0.0204 0.0343 0.0352 0.0007 0.003 0.0028 0.0034 0.0409 0.0637 0.0149 0.0152 0.0117 0.0304 0.0306 0.0676 0.0016 0.0031 0.001 0.0024 0.0005 0.0025 0.0019 0.0079 Proportion of h2g: -0.5843 -0.2737 0.7326 0.6122 -0.4683 -0.7816 1.5562 -0.0354 2.0285 0.3533 -1.0659 1.1224 -0.1528 -0.0849 -0.1212 -1.6849 -0.9925 -0.8794 0.9743 -1.3647 1.5526 -1.7689 1.6222 0.1292 -0.4591 -0.6166 1.5424 -1.1517 0.5608 -2.1687 2.7054 4.1634 -4.3681 -0.2223 0.2945 0.4171 -0.4207 0.2631 0.4123 2.2143 -1.792 3.3475 -3.3473 0.7229 -1.3199 0.2209 -0.009 0.0595 -0.2863 0.0625 -0.4398 -0.1824 0.3721 Enrichment: -6.5956 -210.7377 128.0999 265.1679 -15.8969 -370.2442 247.2068 -2.9016 42.285 35.6804 -71.7216 25.4009 -397.769 -50.28 -21.605 -123.557 -132.1794 -34.8281 28.115 -36.4527 65.0384 -59.4223 106.8863 3.4191 -8.5072 -166.5447 130.6022 -50.8849 163.2844 -194.1202 132.441 121.2958 -124.16 -297.8092 99.3275 151.0758 -122.9295 6.4398 6.472 148.4129 -117.8779 285.2906 -110.016 23.6224 -19.5257 136.8614 -2.9197 60.7634 -120.0043 130.0739 -178.5434 -97.6117 47.218 Coefficients: -1.7187e-08 -5.4916e-07 3.3381e-07 6.9100e-07 -4.1425e-08 -9.6481e-07 6.4419e-07 -7.5612e-09 1.1019e-07 9.2979e-08 -1.8690e-07 6.6192e-08 -1.0365e-06 -1.3102e-07 -5.6300e-08 -3.2197e-07 -3.4444e-07 -9.0758e-08 7.3264e-08 -9.4991e-08 1.6948e-07 -1.5485e-07 2.7853e-07 8.9097e-09 -2.2169e-08 -4.3400e-07 3.4033e-07 -1.3260e-07 4.2550e-07 -5.0585e-07 3.4513e-07 3.1608e-07 -3.2355e-07 -7.7605e-07 2.5884e-07 3.9369e-07 -3.2034e-07 1.6781e-08 1.6865e-08 3.8675e-07 -3.0718e-07 7.4343e-07 -2.8669e-07 6.1557e-08 -5.0882e-08 3.5664e-07 -7.6084e-09 1.5834e-07 -3.1272e-07 3.3896e-07 -4.6526e-07 -2.5436e-07 1.2304e-07 Coefficient SE: 4.8268e-08 4.9468e-07 1.7489e-07 3.1840e-07 5.2170e-08 5.0154e-07 2.4193e-07 2.2372e-07 8.8580e-08 3.2415e-07 2.6869e-07 1.1712e-07 1.1838e-06 3.7496e-07 3.3034e-07 2.0758e-07 3.1836e-07 1.3681e-07 2.6961e-07 2.7131e-07 2.2888e-07 1.9725e-07 1.9291e-07 1.4714e-07 1.0157e-07 3.3631e-07 1.9666e-07 1.1699e-07 3.6457e-07 2.3277e-07 1.4513e-07 5.5699e-07 5.5531e-07 7.1628e-07 2.7743e-07 7.9559e-07 6.7264e-07 8.0424e-08 7.5921e-08 8.1931e-07 8.1724e-07 2.2196e-07 1.2069e-07 7.6765e-08 6.1171e-08 6.0979e-07 3.6773e-07 6.1534e-07 2.4824e-07 6.7338e-07 2.2868e-07 4.4752e-07 1.8598e-07 Lambda GC: 1.0527 Mean Chi^2: 1.0576 Intercept: 1.0175 (0.008) Ratio: 0.3036 (0.138) Analysis finished at Tue Jun 23 18:57:17 2015 Total time elapsed: 1.0m:0.6s

— Reply to this email directly or view it on GitHub https://github.com/bulik/ldsc/issues/35#issuecomment-114997499.

r03ert0 commented 9 years ago

(1) updating to the most recent version seems to solve it :D Now I get "Total Observed scale h2: 0.2545 (0.0326)" with intercept constrained, and "h2: 0.1743 (0.0527)" without intercept constrained. (2) no (3) running the analysis with --ref-ld-chr weights. throws an error:

Beginning analysis at Thu Jun 25 21:10:41 2015 Reading summary statistics from ICV.sumstats.gz ... Read summary statistics for 1068341 SNPs. Reading reference panel LD Score from /Applications/_Geno/LDSCORE/weights.[1-22] ... Read reference panel LD Scores for 1242190 SNPs. Traceback (most recent call last): File "/Applications/_Geno/ldsc/ldsc.py", line 630, in sumstats.estimate_h2(args, log) File "/Applications/_Geno/ldsc/ldscore/sumstats.py", line 260, in estimate_h2 args, log, args.h2) File "/Applications/_Geno/ldsc/ldscore/sumstats.py", line 239, in _read_ld_sumstats M_annot = _read_M(args, log, n_annot) File "/Applications/_Geno/ldsc/ldscore/sumstats.py", line 116, in _read_M _splitp(args.ref_ld_chr), _N_CHR, common=(not args.not_M_5_50)) File "/Applications/_Geno/ldsc/ldscore/parse.py", line 167, in M_fromlist return np.hstack([M(fh, num, N, common) for fh in flist]) File "/Applications/_Geno/ldsc/ldscore/parse.py", line 158, in M x = np.sum([parsefunc(sub_chr(fh, i) + suffix) for i in xrange(1, num + 1)], axis=0) File "/Applications/_Geno/ldsc/ldscore/parse.py", line 152, in parsefunc = lambda y: [float(z) for z in open(y, 'r').readline().split()] IOError: [Errno 2] No such file or directory: '/Applications/_Geno/LDSCORE/weights.1.l2.M_5_50'

I don't have any file called "weights.1.l2.M_5_50" in my LDSCORE directory. Should I get a newer version of the weights as well?

thank you for your help!!

best, roberto

On Thu, Jun 25, 2015 at 7:23 PM, hilaryfinucane notifications@github.com wrote:

Okay, a few more questions:

(1) It looks like you might be using an older version. Could you try git pull and check that that doesn't fix the problem? (2) Was there any custom array data in the dataset? (3) Could you run the analysis with --ref-ld-chr weights. instead of --ref-ld-chr baseline. and send me the log files with and w/o intercept?

Thanks,

Hilary

hilaryfinucane commented 9 years ago

Ah oops, I forgot I hadn't included those files. If things are working now, I'd just skip that extra debug step.

Best,

Hilary

On Thu, Jun 25, 2015 at 3:13 PM, Roberto Toro notifications@github.com wrote:

(1) updating to the most recent version seems to solve it :D Now I get "Total Observed scale h2: 0.2545 (0.0326)" with intercept constrained, and "h2: 0.1743 (0.0527)" without intercept constrained. (2) no (3) running the analysis with --ref-ld-chr weights. throws an error:

Beginning analysis at Thu Jun 25 21:10:41 2015 Reading summary statistics from ICV.sumstats.gz ... Read summary statistics for 1068341 SNPs. Reading reference panel LD Score from /Applications/_Geno/LDSCORE/weights.[1-22] ... Read reference panel LD Scores for 1242190 SNPs. Traceback (most recent call last): File "/Applications/_Geno/ldsc/ldsc.py", line 630, in sumstats.estimate_h2(args, log) File "/Applications/_Geno/ldsc/ldscore/sumstats.py", line 260, in estimate_h2 args, log, args.h2) File "/Applications/_Geno/ldsc/ldscore/sumstats.py", line 239, in _read_ld_sumstats M_annot = _read_M(args, log, n_annot) File "/Applications/_Geno/ldsc/ldscore/sumstats.py", line 116, in _read_M _splitp(args.ref_ld_chr), _N_CHR, common=(not args.not_M_5_50)) File "/Applications/_Geno/ldsc/ldscore/parse.py", line 167, in M_fromlist return np.hstack([M(fh, num, N, common) for fh in flist]) File "/Applications/_Geno/ldsc/ldscore/parse.py", line 158, in M x = np.sum([parsefunc(sub_chr(fh, i) + suffix) for i in xrange(1, num + 1)], axis=0) File "/Applications/_Geno/ldsc/ldscore/parse.py", line 152, in parsefunc = lambda y: [float(z) for z in open(y, 'r').readline().split()] IOError: [Errno 2] No such file or directory: '/Applications/_Geno/LDSCORE/weights.1.l2.M_5_50'

I don't have any file called "weights.1.l2.M_5_50" in my LDSCORE directory. Should I get a newer version of the weights as well?

thank you for your help!!

best, roberto

On Thu, Jun 25, 2015 at 7:23 PM, hilaryfinucane notifications@github.com wrote:

Okay, a few more questions:

(1) It looks like you might be using an older version. Could you try git pull and check that that doesn't fix the problem? (2) Was there any custom array data in the dataset? (3) Could you run the analysis with --ref-ld-chr weights. instead of --ref-ld-chr baseline. and send me the log files with and w/o intercept?

Thanks,

Hilary

— Reply to this email directly or view it on GitHub https://github.com/bulik/ldsc/issues/35#issuecomment-115367191.

r03ert0 commented 9 years ago

great! thank you

On Thu, Jun 25, 2015 at 9:14 PM, hilaryfinucane notifications@github.com wrote:

Ah oops, I forgot I hadn't included those files. If things are working now, I'd just skip that extra debug step.

Best,

Hilary

On Thu, Jun 25, 2015 at 3:13 PM, Roberto Toro notifications@github.com wrote:

(1) updating to the most recent version seems to solve it :D Now I get "Total Observed scale h2: 0.2545 (0.0326)" with intercept constrained, and "h2: 0.1743 (0.0527)" without intercept constrained. (2) no (3) running the analysis with --ref-ld-chr weights. throws an error:

Beginning analysis at Thu Jun 25 21:10:41 2015 Reading summary statistics from ICV.sumstats.gz ... Read summary statistics for 1068341 SNPs. Reading reference panel LD Score from /Applications/_Geno/LDSCORE/weights.[1-22] ... Read reference panel LD Scores for 1242190 SNPs. Traceback (most recent call last): File "/Applications/_Geno/ldsc/ldsc.py", line 630, in sumstats.estimate_h2(args, log) File "/Applications/_Geno/ldsc/ldscore/sumstats.py", line 260, in estimate_h2 args, log, args.h2) File "/Applications/_Geno/ldsc/ldscore/sumstats.py", line 239, in _read_ld_sumstats M_annot = _read_M(args, log, n_annot) File "/Applications/_Geno/ldsc/ldscore/sumstats.py", line 116, in _read_M _splitp(args.ref_ld_chr), _N_CHR, common=(not args.not_M_5_50)) File "/Applications/_Geno/ldsc/ldscore/parse.py", line 167, in M_fromlist return np.hstack([M(fh, num, N, common) for fh in flist]) File "/Applications/_Geno/ldsc/ldscore/parse.py", line 158, in M x = np.sum([parsefunc(sub_chr(fh, i) + suffix) for i in xrange(1, num + 1)], axis=0) File "/Applications/_Geno/ldsc/ldscore/parse.py", line 152, in parsefunc = lambda y: [float(z) for z in open(y, 'r').readline().split()] IOError: [Errno 2] No such file or directory: '/Applications/_Geno/LDSCORE/weights.1.l2.M_5_50'

I don't have any file called "weights.1.l2.M_5_50" in my LDSCORE directory. Should I get a newer version of the weights as well?

thank you for your help!!

best, roberto

On Thu, Jun 25, 2015 at 7:23 PM, hilaryfinucane < notifications@github.com> wrote:

Okay, a few more questions:

(1) It looks like you might be using an older version. Could you try git pull and check that that doesn't fix the problem? (2) Was there any custom array data in the dataset? (3) Could you run the analysis with --ref-ld-chr weights. instead of --ref-ld-chr baseline. and send me the log files with and w/o intercept?

Thanks,

Hilary

— Reply to this email directly or view it on GitHub https://github.com/bulik/ldsc/issues/35#issuecomment-115367191.

— Reply to this email directly or view it on GitHub https://github.com/bulik/ldsc/issues/35#issuecomment-115367495.