MMP() - reviewed

[balima78]

1 parent

Join files candid.csv with hlaA, hlaB.

[entre parenteses rectos é dado o tipo das variáveis]

NOTA só calcula se os valores: cA1, cA2 in (hlaA); cB1, cB2 in (hlaB); cDR1, cDR2 in (hlaA);
mmp(data = candidatos, [data frame] freqs = (PT, ET), [character] cPRA = 0 - 100 [numeric value] )

• faz o join das frequencias alélicas para cada alelo

  • as colunas A1 e A2 de candidatos fazem join com a coluna A de hlaA; a coluna freq de hlaA é renomeada para a1 no join de A1 e para a2 no join de A2;
  • as colunas B1 e B2 de candidatos fazem join com a coluna B de hlaB; a coluna freq de hlaB é renomeada para b1 no join de B1 e para b2 no join de B2;
  • as colunas DR1 e DR2 de candidatos fazem join com a coluna DR de hlaDR; a coluna freq de hlaDR é renomeada para dr1 no join de DR1 e para dr2 no join de DR2

• calcula MMP0 = (a1+a2)^2 (b1+b2)^2 (dr1+dr2)^2

• calcula MMP2 = (((2(a1+a2)(1 - a1 - a2)) - a1^2 - a2^2 + SallA) / ((a1+a2)^2))

  • (((2(b1+b2)(1 - b1 - b2)) - b1^2 - b2^2 + SallB) / ((b1+b2)^2))
  • (((2(dr1+dr2)(1 - dr1 - dr2) ) - dr1^2 - dr2^2 + SallDR) / ((dr1+dr2)^2))

• calcula MMP1 = MMP0 * MMP2

• calcula MMP = 100 (1-(abo (1-cPRA/100) * (MMP0 + MMP1)))^1000

HLA frequencies from portuguese CEDACE donors (Lima, 2013)

hlaApt <- read.csv2("files/hlaA.csv") %>% [data.frame] mutate_at(vars(A),as.character) hlaBpt <- read.csv2("files/hlaB.csv") %>% [data.frame] mutate_at(vars(B),as.character) hlaDRpt <- read.csv2("files/hlaDR.csv") %>% [data.frame] mutate_at(vars(DR),as.character)

HLA frequencies from EuroTransplant (ETKAS and SP chapter 4 kidney)

hlaAet <- read.csv2("files/hlaAet.csv") %>% [data.frame] mutate_at(vars(A),as.character) hlaBet <- read.csv2("files/hlaBet.csv") %>% [data.frame] mutate_at(vars(B),as.character) hlaDRet <- read.csv2("files/hlaDRet.csv") %>% [data.frame] mutate_at(vars(DR),as.character)

ABO blood group frequencies from portuguese blood donors (Duran et al, 2007)

abo <- read.csv2("files/abo.csv") %>% [data.frame] mutate_at(vars(abo),as.character)

compute MMP from ETKAS

compute the sum of squared frequencies for each loci with PT frequencies

SallApt <-sum(hlaApt$freq^2) [numeric value] SallBpt <-sum(hlaBpt$freq^2) [numeric value] SallDRpt <-sum(hlaDRpt$freq^2) [numeric value]

compute the sum of squared frequencies for each loci with ET frequencies

SallAet <-sum((hlaAet %>% drop_na() %>% .$freq)^2) [numeric value] SallBet <-sum((hlaBet %>% drop_na() %>% .$freq)^2) [numeric value] SallDRet <-sum((hlaDRet %>% drop_na() %>% .$freq)^2) [numeric value]

[balima78]

function et_mmp() on et.R

we can close this issue!