Last updated: 2024-06-13

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Knit directory: multigroup_ctwas_analysis/

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Rmd	92a8e35	XSun	2024-06-13	update
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Overview

Traits

aFib, IBD, LDL, SBP, SCZ, WBC

details

Tissues

The independent tissues are selected by single tissue analysis

Omics

eQTL, sQTL, apaQTL weights are from Munro et al.

Settings

Weight processing:

PredictDB:

all the PredictDB are converted from FUSION weights

drop_strand_ambig = TRUE,
scale_by_ld_variance = F (FUSION converted weights)
load_predictdb_LD = F,

Parameter estimation and fine-mapping

niter_prefit = 5,
niter = 60,
L = 3,
group_prior_var_structure = “shared_type”,
maxSNP = 20000,
min_nonSNP_PIP = 0.5,

Memory requested

cpus-per-task=2
mem=200G

over 30h running time

Results

Results from multi-group analysis

The results are summarized by

Heritability contribution by contexts: we aggregate the PVE values by omics and tissues, making it easier to understand the distribution of PVE across different genetic contexts.
Combined PIP by omics: we aggregate the Susie PIPs by omics
Combined PIP by contexts: we aggregate the Susie PIPs by tissues, making it easier to understand the distribution of PIP across different genetic contexts.
Specific molecular traits of top genes: we creates a pie chart to visualize the proportion of genes classified into different categories based on their PIPs contributed by each genetics contexts. The categories are based on the proportion of each QTL type relative to the combined PIP value:

by eQTL: Number of genes where the ratio of eQTL to combined PIP is greater than 0.8.
by sQTL: Number of genes where the ratio of sQTL to combined PIP is greater than 0.8.
by apaQTL: Number of genes where the ratio of apaQTL to combined PIP is greater than 0.8.
by sQTL+apaQTL: Number of genes where the combined ratio of apaQTL and sQTL to combined PIP is greater than 0.8, but neither apaQTL nor sQTL individually exceed 0.8.
unspecified: Number of genes not classified into any of the above categories.

Comparing with earlier multi-group analysis results

We compared number of significant genes, overlapping genes. The earlier results are here: https://sq-96.github.io/multigroup_ctwas_analysis/multi_group_6traits_15weights_ukbb.html

Sigificant gene compare summary

	sig_gene_current	sig_gene_earlier	sig_gene_overlap	groupsize_eqtl_current	groupsize_eqtl_earlier	groupsize_sqtl_current	groupsize_sqtl_earlier	groupsize_apaqtl_current	groupsize_apaqtl_earlier
ibd	29	32	9	6034-5060-5880-5700-3931	9791-8784-9944-9984-8896	7198-5497-8911-6912-4261	24290-16109-28632-24379-19217	6789-4705-7036-5922-3955	1503-1973-1568-698-827
ldl	65	67	12	3194-5209-8951-4409-6977	8775-9749-10538-9433-10580	3194-5209-8951-4409-6977	18136-27105-30032-24941-25674	2700-4414-7076-3740-5950	1986-1578-636-575-1025
sbp	90	84	27	5903-5902-3412-3947-4095	10137 -10071-9201 -8977-9234	8224-8950-4089-4290-5206	27192 -28744-22553-19343-25955	6667-7076-3619-3970-4414	1980-1647-571-1003-703
scz	50	28	4	3936-3375-2540-4542-3386	8486-8397-8425-8675-8695	4270-4400-4247-5593-4960	18100-22295-24656-24890-22249	3951-3365-4225-4349-3729	1018-693-770-1056-1194
wbc	291	220	82	5078-5891-4790-6294-4088	8455-9589-9402-9943-8721	5530-8927-6490-9102-5185	15248-27095-25101-26876-24403	4700-7055-5281-7227-4409	1973-1479-1779-571-821

aFib

TO DO

IBD

Results from multi-group analysis

Version	Author	Date
9e83189	XSun	2024-06-13

Version	Author	Date
9e83189	XSun	2024-06-13

Version	Author	Date
9e83189	XSun	2024-06-13

Version	Author	Date
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[1] "Esophagus_Mucosa"           "Adipose_Subcutaneous"      
[3] "Whole_Blood"                "Heart_Left_Ventricle"      
[5] "Cells_Cultured_fibroblasts"

Version	Author	Date
9e83189	XSun	2024-06-13

Comparing with earlier weights

overlaps

[1] "current # of sig. genes = 29"

[1] "earlier # of sig. genes = 32"

[1] "# of overlap between them = 9"

Why earlier genes were not reported in current settings

In the table below, NA means: current weights do not have this gene. If combined_pip_current_weights >0.8, it means in current setting, this gene is not included in CS. combined_pip_current_weights < 0.8 means in current setting, the gene is filtered out by either credible set or combined_pip.

[1] "8 were not included (NAs) because they are not in the weight files"

[1] "1 were not included (combined_pip > 0.8) because they are not in CS"

[1] "14 were not included (combined_pip < 0.8) because of the low combined PIPs"

Why current genes were not reported in earlier settings

In the table below, NA means: earlier weights do not have this gene. If combined_pip_current_weights >0.8, it means in earlier setting, this gene is not included in CS. combined_pip_earlier_weights < 0.8 means in earlier setting, the gene is filtered out by either credible set or combined_pip.

[1] "3 were not included (NAs) because they are not in the weight files"

[1] "0 were not included (combined_pip > 0.8) because they are not in CS"

[1] "17 were not included (combined_pip < 0.8) because of the low combined PIPs"

LDL

Results from multi-group analysis

Version	Author	Date
92a8e35	XSun	2024-06-13
9e83189	XSun	2024-06-13

Version	Author	Date
92a8e35	XSun	2024-06-13
9e83189	XSun	2024-06-13

Version	Author	Date
92a8e35	XSun	2024-06-13
9e83189	XSun	2024-06-13

Version	Author	Date
92a8e35	XSun	2024-06-13
9e83189	XSun	2024-06-13

[1] "Esophagus_Mucosa"     "Adipose_Subcutaneous" "Liver"               
[4] "Adrenal_Gland"        "Spleen"

Version	Author	Date
92a8e35	XSun	2024-06-13
9e83189	XSun	2024-06-13

Comparing with earlier weights

overlaps

[1] "current # of sig. genes = 65"

[1] "earlier # of sig. genes = 67"

[1] "# of overlap between them = 12"

Why earlier genes were not reported in current settings

[1] "23 were not included (NAs) because they are not in the weight files"

[1] "2 were not included (combined_pip > 0.8) because they are not in CS"

[1] "30 were not included (combined_pip < 0.8) because of the low combined PIPs"

Why current genes were not reported in earlier settings

[1] "7 were not included (NAs) because they are not in the weight files"

[1] "0 were not included (combined_pip > 0.8) because they are not in CS"

[1] "46 were not included (combined_pip < 0.8) because of the low combined PIPs"

SBP

Results from multi-group analysis

Version	Author	Date
92a8e35	XSun	2024-06-13

Version	Author	Date
92a8e35	XSun	2024-06-13

Version	Author	Date
92a8e35	XSun	2024-06-13

Version	Author	Date
92a8e35	XSun	2024-06-13

[1] "Artery_Tibial"        "Heart_Left_Ventricle" "Spleen"              
[4] "Adipose_Subcutaneous" "Brain_Cortex"

Version	Author	Date
92a8e35	XSun	2024-06-13

Comparing with earlier weights

overlaps

[1] "current # of sig. genes = 90"

[1] "earlier # of sig. genes = 84"

[1] "# of overlap between them = 27"

Why earlier genes were not reported in current settings

[1] "17 were not included (NAs) because they are not in the weight files"

[1] "2 were not included (combined_pip > 0.8) because they are not in CS"

[1] "38 were not included (combined_pip < 0.8) because of the low combined PIPs"

Why current genes were not reported in earlier settings

[1] "10 were not included (NAs) because they are not in the weight files"

[1] "2 were not included (combined_pip > 0.8) because they are not in CS"

[1] "51 were not included (combined_pip < 0.8) because of the low combined PIPs"

SCZ

Results from multi-group analysis

Version	Author	Date
92a8e35	XSun	2024-06-13

Version	Author	Date
92a8e35	XSun	2024-06-13

Version	Author	Date
92a8e35	XSun	2024-06-13

Version	Author	Date
92a8e35	XSun	2024-06-13

[1] "Heart_Left_Ventricle" "Adrenal_Gland"        "Brain_Cerebellum"    
[4] "Stomach"              "Artery_Coronary"

Version	Author	Date
92a8e35	XSun	2024-06-13

Comparing with earlier weights

overlaps

[1] "current # of sig. genes = 50"

[1] "earlier # of sig. genes = 28"

[1] "# of overlap between them = 4"

Why earlier genes were not reported in current settings

[1] "13 were not included (NAs) because they are not in the weight files"

[1] "1 were not included (combined_pip > 0.8) because they are not in CS"

[1] "10 were not included (combined_pip < 0.8) because of the low combined PIPs"

Why current genes were not reported in earlier settings

[1] "8 were not included (NAs) because they are not in the weight files"

[1] "3 were not included (combined_pip > 0.8) because they are not in CS"

[1] "35 were not included (combined_pip < 0.8) because of the low combined PIPs"

WBC

Results from multi-group analysis

Version	Author	Date
92a8e35	XSun	2024-06-13

Version	Author	Date
92a8e35	XSun	2024-06-13

Version	Author	Date
92a8e35	XSun	2024-06-13

Version	Author	Date
92a8e35	XSun	2024-06-13

[1] "Whole_Blood"                "Skin_Sun_Exposed_Lower_leg"
[3] "Adipose_Subcutaneous"       "Artery_Aorta"              
[5] "Spleen"

Version	Author	Date
92a8e35	XSun	2024-06-13

Comparing with earlier weights

overlaps

[1] "current # of sig. genes = 291"

[1] "earlier # of sig. genes = 220"

[1] "# of overlap between them = 82"

Why earlier genes were not reported in current settings

[1] "49 were not included (NAs) because they are not in the weight files"

[1] "5 were not included (combined_pip > 0.8) because they are not in CS"

[1] "84 were not included (combined_pip < 0.8) because of the low combined PIPs"

Why current genes were not reported in earlier settings

[1] "26 were not included (NAs) because they are not in the weight files"

[1] "13 were not included (combined_pip > 0.8) because they are not in CS"

[1] "170 were not included (combined_pip < 0.8) because of the low combined PIPs"

sessionInfo()

R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

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

locale:
[1] C

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

other attached packages:
 [1] gridExtra_2.3      RColorBrewer_1.1-3 forcats_0.5.1      stringr_1.5.1     
 [5] dplyr_1.1.4        purrr_1.0.2        readr_2.1.2        tidyr_1.3.0       
 [9] tibble_3.2.1       ggplot2_3.5.1      tidyverse_1.3.1    data.table_1.14.2 
[13] ctwas_0.2.30      

loaded via a namespace (and not attached):
  [1] readxl_1.4.0                backports_1.4.1            
  [3] workflowr_1.7.0             BiocFileCache_2.4.0        
  [5] plyr_1.8.7                  lazyeval_0.2.2             
  [7] crosstalk_1.2.0             BiocParallel_1.30.3        
  [9] GenomeInfoDb_1.39.9         LDlinkR_1.2.3              
 [11] digest_0.6.29               foreach_1.5.2              
 [13] ensembldb_2.20.2            htmltools_0.5.2            
 [15] fansi_1.0.3                 magrittr_2.0.3             
 [17] memoise_2.0.1               doParallel_1.0.17          
 [19] tzdb_0.4.0                  Biostrings_2.64.0          
 [21] modelr_0.1.8                matrixStats_0.62.0         
 [23] locuszoomr_0.2.1            prettyunits_1.1.1          
 [25] colorspace_2.0-3            blob_1.2.3                 
 [27] rvest_1.0.2                 rappdirs_0.3.3             
 [29] ggrepel_0.9.1               haven_2.5.0                
 [31] xfun_0.41                   crayon_1.5.1               
 [33] RCurl_1.98-1.7              jsonlite_1.8.0             
 [35] zoo_1.8-10                  iterators_1.0.14           
 [37] glue_1.6.2                  gtable_0.3.0               
 [39] zlibbioc_1.42.0             XVector_0.36.0             
 [41] DelayedArray_0.22.0         BiocGenerics_0.42.0        
 [43] scales_1.3.0                DBI_1.2.2                  
 [45] Rcpp_1.0.8.3                viridisLite_0.4.0          
 [47] progress_1.2.2              bit_4.0.4                  
 [49] DT_0.22                     stats4_4.2.0               
 [51] htmlwidgets_1.5.4           httr_1.4.3                 
 [53] ellipsis_0.3.2              pkgconfig_2.0.3            
 [55] XML_3.99-0.14               farver_2.1.0               
 [57] sass_0.4.1                  dbplyr_2.1.1               
 [59] utf8_1.2.2                  tidyselect_1.2.0           
 [61] labeling_0.4.2              rlang_1.1.2                
 [63] later_1.3.0                 AnnotationDbi_1.58.0       
 [65] munsell_0.5.0               pgenlibr_0.3.3             
 [67] cellranger_1.1.0            tools_4.2.0                
 [69] cachem_1.0.6                cli_3.6.1                  
 [71] generics_0.1.2              RSQLite_2.3.1              
 [73] broom_0.8.0                 evaluate_0.15              
 [75] fastmap_1.1.0               yaml_2.3.5                 
 [77] knitr_1.39                  bit64_4.0.5                
 [79] fs_1.5.2                    KEGGREST_1.36.3            
 [81] AnnotationFilter_1.20.0     whisker_0.4                
 [83] xml2_1.3.3                  biomaRt_2.54.1             
 [85] compiler_4.2.0              rstudioapi_0.13            
 [87] plotly_4.10.0               filelock_1.0.2             
 [89] curl_4.3.2                  png_0.1-7                  
 [91] reprex_2.0.1                bslib_0.3.1                
 [93] stringi_1.7.6               highr_0.9                  
 [95] GenomicFeatures_1.48.3      lattice_0.20-45            
 [97] ProtGenerics_1.28.0         Matrix_1.5-3               
 [99] vctrs_0.6.5                 pillar_1.9.0               
[101] lifecycle_1.0.4             jquerylib_0.1.4            
[103] cowplot_1.1.1               bitops_1.0-7               
[105] irlba_2.3.5                 httpuv_1.6.5               
[107] rtracklayer_1.56.0          GenomicRanges_1.48.0       
[109] R6_2.5.1                    BiocIO_1.6.0               
[111] promises_1.2.0.1            IRanges_2.30.0             
[113] codetools_0.2-18            assertthat_0.2.1           
[115] SummarizedExperiment_1.26.1 rprojroot_2.0.3            
[117] rjson_0.2.21                withr_2.5.0                
[119] GenomicAlignments_1.32.0    Rsamtools_2.12.0           
[121] S4Vectors_0.34.0            GenomeInfoDbData_1.2.8     
[123] parallel_4.2.0              hms_1.1.1                  
[125] grid_4.2.0                  gggrid_0.2-0               
[127] rmarkdown_2.25              MatrixGenerics_1.8.0       
[129] logging_0.10-108            git2r_0.30.1               
[131] mixsqp_0.3-43               Biobase_2.56.0             
[133] lubridate_1.8.0             restfulr_0.0.14

6 Traits, 5 tissues, eQTL + sQTL + apaQTL – compute ukbb LD, weights are from Munro et al

XSun

2024-05-27

Overview

Traits

Tissues

Omics

Settings

Results

Sigificant gene compare summary

aFib

IBD

Results from multi-group analysis

Comparing with earlier weights

overlaps

Why earlier genes were not reported in current settings

Why current genes were not reported in earlier settings

LDL

Results from multi-group analysis

Comparing with earlier weights

overlaps

Why earlier genes were not reported in current settings

Why current genes were not reported in earlier settings

SBP

Results from multi-group analysis

Comparing with earlier weights

overlaps

Why earlier genes were not reported in current settings

Why current genes were not reported in earlier settings

SCZ

Results from multi-group analysis

Comparing with earlier weights

overlaps

Why earlier genes were not reported in current settings

Why current genes were not reported in earlier settings

WBC

Results from multi-group analysis

Comparing with earlier weights

overlaps

Why earlier genes were not reported in current settings

Why current genes were not reported in earlier settings