results
Last updated: 2021-04-06
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Knit directory: funcFinemapping/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | ae12e8a | Jing Gu | 2021-04-06 | evaluate sequence constraints |
| html | 752cb39 | Jing Gu | 2021-04-05 | Build site. |
| html | f1c5950 | Jing Gu | 2021-04-05 | Build site. |
| html | d16a5e0 | Jing Gu | 2021-04-05 | Build site. |
| Rmd | 6f7214b | Jing Gu | 2021-04-05 | edit index page |
Fine-mapping with functional annotations as priors has shown improved results in identifying causal variants. This project is to evaluate the utility of novel annotation features and adopt ones that can improve fine mapping results.
Evaluation
GWAS summary statistics
Schizopherenia - Pardinas et al., 2018
- 40675 cases and 64643 controls
- CLOZUK sample + PGC sample (independent)
- 179 independent GWAS significant SNPs mapped to 145 independent loci
- SNPs were imputed using a combination of the 1KGPp3 and UK 10K datasets.
- SNPs were filtered by NFO > 0.6 and MAF > 0.01
- LD-score regression analysis: An LD reference was generated from 1KGPp3 after restricting this dataset to strictly unrelated individuals and retaining only markers with MAF > 0.01.
Features
- Sequence constraints:
- context-dependent tolerance scores(CDTS) in percentiles
- A score was computed for each 10bp bin in the genome.
- The lower the score is, the more intolerant to variation is the bin.
Procedures
- GWAS summary statistics was pre-processed to remove sex chromosomes, indels, ambiguous and duplicated SNPs.
- Currently, genotypes from 1kg European samples are used to compute LD between SNPs.
- SNPs in GWAS summary statistics were matched with the reference panel and assigned to in total 1687 independent LD blocks.
- Run TORUS to perform genome-wide enrichment analyses.
Results
All variants were catogrized into whether or not they occur in genomic bins with CDTS up to 1 percentile or 5 percentile.
Note: * The enrichment estimate is in its absolute value (not in the log form). 
| Version | Author | Date |
|---|---|---|
| d16a5e0 | Jing Gu | 2021-04-05 |
The enrichment estimate has a confience level above zero for both annotations. This shows SNPs associated with SCZ are on average ~ 1.5 fold enriched in genomic bins with up to 5 percentile of CDTS.
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_0.4.10 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
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[29] tidyselect_1.1.0 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_0.3.1 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