201028-tadaA-res

dataset

7131 autosomal protein-coding denovo mutations in case, including missense(MPC>=0), PTV(pLI >= 0) and synonymous.

mis(MPC >= 1) + PTV = 2220
Missense_Lowest(MPC<1) = 3155
syn = 1756

f3 = data.frame(RR = 36.14)

f3$logRR = -1
f3$lower_bound = -2.197207
f3$upper_bound = 0.1972072
f3$annota = "unaffected_scale_syn"
f3$exp = 1562
f3$obs = 1756
f3$oe_ratio = f3$obs/f3$exp
f3$logRR_paper = 0.119018
f3$RR_paper = 1.13
f3

A data.frame: 1 × 10
RR	logRR	lower_bound	upper_bound	annota	exp	obs	oe_ratio	logRR_paper	RR_paper
<dbl>	<dbl>	<dbl>	<dbl>	<chr>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>
36.14	3.58745	2.430291	4.74461	lof_pLI>=0.995	2	366	183	3.923169	50.56

1 2	f6=rbind(f5,s) f6

A data.frame: 4 × 12
RR	logRR	lower_bound	upper_bound	annota	exp	obs	oe_ratio	logRR_paper	RR_paper	n_DNM	n_proband
<dbl>	<dbl>	<dbl>	<dbl>	<chr>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>
0.3678795	-1.000000	-1.859598	-0.1404014	annovar_synonymous	1680	1756	1.045238	0.119018	1.13	7131	6430
8.0000000	2.079227	1.826094	2.3323600	missense_MPC>=2	220	354	1.609091	3.097837	22.15	7131	6430
36.1400000	3.587450	2.430291	4.7446100	lof_pLI>=0.995	2	366	183.000000	3.923169	50.56	7131	6430
0.3678794	-1.000000	-1.595831	-0.4041690	annovar_synonymous	503	0	0.000000	0.119018	1.13	2220	6430

dataset incorporated to derive 102 genes.

2220 denovo PTV and missense (MPC >=1)
29,783 case-control rare PTV

1) TADA & ASC2015, de novo variants only. 31 genes

2) TADA & ASC2018, de novo variants only. 65 genes

3) TADA$^+$ & ASC2018, de novo variants only. 89 genes

4) TADA$^+$ & ASC2018, de novo and case-control variants. 102 genes

using synonymous mutations count to normalize the count of a certain type of mutation.

$\lambda$ = $(X_{cs}/ X_{cn}) / (S_{cs}/ S_{cn})$

$\gamma$ = 1 + ($\lambda$ - 1)/$\pi$

s = (1755/6430/(591/2179)) ### burden of synonymous
s
pi = 0.05

gm = 1+(s-1)/pi 
gm

log(gm)

1.00631952064798

1.12639041295956

0.119018195163435

annota = c("gnomad.v2.1.1.all_lofs_snv (PTV average)",
"MPC_gt2 (MisB)",
"lofs_pLI_nlt_0.995",
"lofs_pLI_0.5_0.995",
"MPC_1-2 (MisA)",
 "synonymous")
logRR_paper = c(
1.949428,
3.097837,
3.923169,
1.922309,
1.430310,
0.119018)
rr = data.frame(annota,logRR_paper)
rr$RR_paper = round(exp(rr$logRR_paper),2)
rr

A data.frame: 6 × 3
annota	logRR_paper	RR_paper
<fct>	<dbl>	<dbl>
gnomad.v2.1.1.all_lofs_snv (PTV average)	1.949428	7.02
MPC_gt2 (MisB)	3.097837	22.15
lofs_pLI_nlt_0.995	3.923169	50.56
lofs_pLI_0.5_0.995	1.922309	6.84
MPC_1-2 (MisA)	1.430310	4.18
synonymous	0.119018	1.13

logRR = c(-1.000000,
4.156999,
5.083290,
3.405306,
2.967571,
-1.000000)

lower_bound = c(-16.798553,
3.788179,
4.190904,
3.224070,
2.836006,
-1.483602)

upper_bound = c(14.7985529,
4.5258196,
5.9756750,
3.5865425,
3.0991369,
-0.5163975)

df2220 = data.frame(logRR,lower_bound,upper_bound)
df2220$RR = exp(df2220$logRR)
df2220$annota = c("pLI_05_995",
                 "pLI_lt05",
                 "pLI_nlt_995",
                 "_MPC_gt2",
                 "MPC_1-2",
                 "MPC_0-1")
df2220.2 = df2220[,c(4,1,2,3,5)]
df2220.2

A data.frame: 6 × 5
RR	logRR	lower_bound	upper_bound	annota
<dbl>	<dbl>	<dbl>	<dbl>	<chr>
0.3678794	-1.000000	-16.798553	14.7985529	pLI_05_995
63.8795322	4.156999	3.788179	4.5258196	pLI_lt05
161.3038736	5.083290	4.190904	5.9756750	pLI_nlt_995
30.1235121	3.405306	3.224070	3.5865425	_MPC_gt2
19.4446312	2.967571	2.836006	3.0991369	MPC_1-2
0.3678794	-1.000000	-1.483602	-0.5163975	MPC_0-1

dataset used in previous tests

15,789 de novo variants from 6,430 probands and 2,179 unaffected children.