Last updated: 2021-09-01

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Knit directory: funcFinemapping/

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Partitioned-LDSC

Technical details

  1. HapMap3 SNPs (~1.2M): used as a proxy for well imputed SNPs and the regression SNPs in LDSC. They were generated by the international HapMap project on a collection of 1301 samples from a variaty of human populations.[https://www.sanger.ac.uk/resources/downloads/human/hapmap3.html]

  2. Reference panel SNPs (~9M): the set of 1000G SNPs with MAF > 5% in ~500 Euproean samples

  3. LDSC inputs/outputs:

  • .M/.l2.M_5_50: The .M file contains the total number of SNPs; the .l2.M_5_50 file contains the number of SNPs with minor allele frequency above 5%. By default, ldsc uses common SNPs (MAF > 5%) to estimate per SNP heritability, which is different for rare variants.

  • freqfile/w-ld-chr: computed on European of Phase 3 of 1kg Genomes

  • Regression weights: used to correct for non-independence and heteroskedasticity among the \(\chi^2\) statistics.

  • Regression coefficients: Quoted from the website that "They measure the additional contribution of one annotation to the model and are interpretable for both binary and continuous annotations"

  1. GC correction:

Baseline annotations:
DHS, H3K4me1, H3K4me3, and H3K9ac - peaks w/o flanking regions Coding, Conserved, CTCF, DGF
FANTOM5-Enhancer, Enhancer, Fetal_DHS, H3K27ac
Intron, PromoterFlanking, Promoter, Repressed, Super-enhancer, TFBS, Transcribed TSS
3-prime UTR, 5-prime UTR, Weak Enhancer

Schizophrenia

NeuronalATAC+SpliceAI+baselineLD

Version Author Date
05f73e9 Jing Gu 2021-09-01

Across traits

per-standardized-annotation effect sizes

\(\tau_{c}^{*}\) is defined as the additive change in per-SNP heritability associated with a 1 s.d. increase in the value of the annotation.

Version Author Date
0032b8c Jing Gu 2021-09-01
05f73e9 Jing Gu 2021-09-01

Heritability Enrichment across traits and annotations

Version Author Date
0032b8c Jing Gu 2021-09-01

More details below. \(\tau\) measures the contribution of SNPs near prioritized genes to per SNP heritability after controlling for the baseline annotations. To make \(\tau\) comparable across traits, we normalized \(\tau\) by the average per-SNP heritability for each trait and refer to this quantity as normalized \(\tau\).


sessionInfo()
R version 4.0.4 (2021-02-15)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.3.13-el7-x86_64/lib/libopenblas_haswellp-r0.3.13.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] ggplot2_3.3.3   workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.6        highr_0.8         pillar_1.5.0      compiler_4.0.4   
 [5] bslib_0.2.4       later_1.1.0.1     jquerylib_0.1.3   git2r_0.28.0     
 [9] tools_4.0.4       digest_0.6.27     jsonlite_1.7.2    evaluate_0.14    
[13] lifecycle_1.0.0   tibble_3.0.6      gtable_0.3.0      pkgconfig_2.0.3  
[17] rlang_0.4.11      DBI_1.1.1         yaml_2.2.1        xfun_0.21        
[21] withr_2.4.1       dplyr_1.0.4       stringr_1.4.0     knitr_1.31       
[25] generics_0.1.0    fs_1.5.0          vctrs_0.3.8       sass_0.3.1       
[29] tidyselect_1.1.1  rprojroot_2.0.2   grid_4.0.4        glue_1.4.2       
[33] R6_2.5.0          fansi_0.4.2       rmarkdown_2.7     farver_2.0.3     
[37] purrr_0.3.4       magrittr_2.0.1    whisker_0.4       scales_1.1.1     
[41] promises_1.2.0.1  ellipsis_0.3.2    htmltools_0.5.1.1 assertthat_0.2.1 
[45] colorspace_2.0-0  httpuv_1.5.5      labeling_0.4.2    utf8_1.1.4       
[49] stringi_1.5.3     munsell_0.5.0     crayon_1.4.1