0907_tadaA_res_modify

all separate estimation

setwd("/storage11_7T/fuy/TADA-A/annotation")
a = readRDS(paste0("/storage11_7T/fuy/TADA-A/annotation/2020-08-28","_all_RR.rds"))
b = readRDS("denovo_df.rds")
d = rbind(a,b)
e = d[order(-d$relative_risk),]
e$idx = 1:nrow(e)
e

A data.frame: 22 × 5
	logRR	lower_bound	upper_bound	annota	idx
	<dbl>	<dbl>	<dbl>	<chr>	<int>
51	3.1078241	1.6900099	4.5256384	pLI_nlt_995.gnomad.v2.1.1.all_lofs	6
41	2.2739992	1.6665827	2.8814158	pLI_lt05.gnomad.v2.1.1.all_lofs	7
22	2.2615612	1.6800949	2.8430276	gnomad.v2.1.1.all_lofs	8
14	2.1166764	-0.2095761	4.4429289	pLI_nlt_09.gnomad.v2.1.1.all_lofs	9
2	1.8723460	1.6331143	2.1115778	annova_lof	10
7	1.8200768	1.5566559	2.0834977	MPC_gt2	11
6	1.4764815	1.2682661	1.6846969	spidex_lt10	12
3	1.3286583	1.0802172	1.5770995	coding_constraint_regions_gt90	13
4	1.2019536	1.0027889	1.4011183	MVP_all_rare_missense_pathogen_gt_7	14
9	1.1630679	-1.2117190	3.5378548	CLIPdb005	15
5	1.0677442	0.7807190	1.3547694	primateAI_exome_mutation_pathogen_gt_80	16
21	0.8484629	0.7036579	0.9932679	annova_mis_lof	17
8	0.1276963	-1.7924259	2.0478185	ribosnitch01	18
31	-1.0000000	-9.9236275	7.9236275	pLI_05_995.gnomad.v2.1.1.all_lofs	19
11	-1.0000000	-1.6844744	-0.3155256	annova_syn	20
1	-1.0000000	-1.7410982	-0.2589018	annov_missense	21
12	-1.0000000	-5.8501671	3.8501672	RBP01	22
12	0.7688921	0.08826144	1.449523	RADAR_RBP.top5%	23

pLI

pLI is from pLI.gnomad.v2.1.1.lof_metrics.by_gene
lof snv is from pLI.gnomad.v2.1.1.lof.snv.bed

1	e2[c(2,5,15,3),]

A data.frame: 4 × 5
	relative_risk	lower_bound	upper_bournd	annota	idx
	<dbl>	<dbl>	<dbl>	<chr>	<int>
51	3.107824	1.6900099	4.525638	pLI_nlt_995	2
14	2.116676	-0.2095761	4.442929	pLI_nlt_09	5
31	-1.000000	-9.9236275	7.923628	pLI_05_995	15
41	2.273999	1.6665827	2.881416	pLI_lt05	3

lof and missense

1	e2[c(4,6,13,17),]

A data.frame: 4 × 5
	relative_risk	lower_bound	upper_bournd	annota	idx
	<dbl>	<dbl>	<dbl>	<chr>	<int>
22	2.2615612	1.6800949	2.8430276	gnomad.v2.1.1.all_lofs	4
2	1.8723460	1.6331143	2.1115778	annova_lof	6
21	0.8484629	0.7036579	0.9932679	annova_mis_lof	13
1	-1.0000000	-1.7410982	-0.2589018	annov_missense	17

PTV

1	e2[c(11,14,18),]

A data.frame: 3 × 5
	relative_risk	lower_bound	upper_bournd	annota	idx
	<dbl>	<dbl>	<dbl>	<chr>	<int>
9	1.1630679	-1.211719	3.537855	CLIPdb005	11
8	0.1276963	-1.792426	2.047818	ribosnitch01	14
12	-1.0000000	-5.850167	3.850167	RBP01	18