README.md

In Linda24bc/PredictDiag: predict diagnostic product ions for Hb variants

PredictDiag

predict diagnostic product ions for Hb variants

Installation

Install from GitHub:

Introduction

• This procedure can predict the diagnostic ions of Hb beta variants that have been experimentally teseted by refering to the product ions of Hb A beta.
• The output list from step 5 can be combined with the original databse in Variants Identifier as the updated database for sereaching.

Prerequisite 1: Install packages

• install.packages("seqinr")
• library(seqinr)
• library(dplyr)
• library(tidyr)
• library(tidyverse)
• library(data.table)

Prerequisite 2.1: Load monomz and PredictDiag function

The R apckage is avaiable in Github.

monomz(sequence, fragments = "by") # for cz ions, define fragments as "cz"

PredictDiag(Hbvarinats)

Prerequisite 2.2: Input the list of residue numbers of possible diagnostic ions for each AA in the Hb beta

diag <- read_csv("finddiag.csv")

Prerequisite 2.3: Input list of reference product ions for HbA beta

HbA.B <- read_csv("ref mass list_pro_1.csv") %>% select(-c(Ref_Mass, Ref_rel_abun, Variant))

Step 1: Input the sequennces of HbA beta and Hb beta variants

Mutiple sequences of variants sequences can be included in one .fasta file, the sequences should have the N-terminal Met while the comparision results exclude the N-ternimal Met.

Hbvariants <- read.fasta(file = "Hbvariants.fasta", seqtype = "AA",as.string = FALSE)

HbAB <- read.fasta(file = "HbA.fasta", seqtype = "AA",as.string = FALSE)

Step 2: Predict the diagnostic ions by running the function

PD.result <- PredictDiag(Hbvarinats)

Step 3:Output results in .csv file

write.csv(PD.result, "PredictDiag_new.csv", row.names = FALSE)

Linda24bc/PredictDiag documentation built on Sept. 8, 2021, 10:18 a.m.