README.md

In Linda24bc/VariantsIdentifier: Automaitically Identification of Hb variants

Variants Identifier

Automaitically Identification of Hb variants

Installation

Install from GitHub:

Introduction

• Identify the Hb variants by comparing the experimental data in the database
• Original database contains the theoretical diagnostic ions of Hb variants been tested by mass spectrometry so far

Prerequisite 1: Install packages

• library(dplyr)
• library(tidyverse)
• library(knitr)

Prerequisite 2:load SubDatabase and Variant.Identifier function

The R apckage is avaiable in Github. Example data are avaiable in Input folder and expected output data are in Output data.

Step 1. Input the database including the diagnostic ions of Hb varints and use MS1 data to narrow down the database - subset the database

1.1 Input the original database

HbDatabase <- read_csv("Hb Variants_OriginalDatabase.csv")

1.2 Use the MS1 data to narrow down the database, if the mass shift is about -0.93 Da, then the Mshift is -0.93 Da and the error tolerence is 0.06 Da. Thoese two values are changable and depend on the accuracy of deconvolution.

ref <- SubDatabase(HbDatabase, Mshift= -0.93, error_Da_L=-0.05, error_Da_R=0.06)

Step 2. Input the deconvolve MS2 results

The list should contain two columns, Exp_m/z vs Exp_Intensity)

exp <- read_csv("expt mass_AC.csv")

Step 3. Search the experimental results in the subset database with Variant Identifier

Run the function Variants.Identifier, the ppm_error range is changable and depends on the accuracy of the MS2 data. View the result list and get the identification.

ID.results <- Variants.Identifier(ref, exp, ppm_error_start=-2, ppm_error_end=5)

Step 4. Output the results in .csv

write.csv(ID.results, "ID_HbAE_1.csv", row.names = FALSE)

Linda24bc/VariantsIdentifier documentation built on Sept. 5, 2021, 2:16 p.m.