In ArshiaMahmoodi/DrawAlignR: Visualizes Aligned Ms2 Chromatograms

knitr::opts_chunk$set(echo = TRUE)

Introduction

DrawAlignR is an R package for the visualization of ms2 chromatograms with support for multi run experiments and proteins with post- translational modifications.

Data preparation

Raw chromatogram data should be in the .mzML file format and organized into a folder titled 'mzml' For the provided example data set, in the mzml folder: chludwig_K150309_010_SW_1_2.chrom.mzML chludwig_K150309_011_SW_1_1point5.chrom.mzML chludwig_K150309_012_SW_1_1.chrom.mzML chludwig_K150309_013_SW_0.chrom.mzML

For simple Chromatogram plotting (without alignment), a .pqp library folder is required and can be uploaded directly to the app. In the working example, psgs.pqp is found in extdata/PQP Library.

For plotting with alignment, the database .osw file is required and must be organized into a folder titled osw, in the same working directory as the 'mzml' folder. This directory can be set within the app, but defaults to extdata. For the provided example data set, GR.merged.osw must be downloaded from DropBox and placed within the osw folder (This is since it exceeds githubs 2gb limit)

Simple Chromatogram Plotting

Note, plotting may take up to 2 minutes per mzML selected

Initially, choose a chromatogram file. A minimum of 1 .mzML chromatogram must be selected but multiple files are supported. For the working example, select 1-4 of the provided .mzML files via the apps "Choose a Chromatogram File"

Similairly, a .pqp file must be uploaded in similair fashion. For the working example, select psgs.pqp.

A full peptide name must be given. This can be any peptide within the data set. By default, ANS(UniMod:21)SPTTNIDHLK(UniMod:259) is selected

Since this peptide can have multiple charge states, with different chromatograms, the peptide charge must be specified. By default, for the example peptide charge +2 and +3 are found in the data set.

A chromatogram will then be plotted for the desired peptide for each mzML run selected. The user can elect to view 1 or all of these plots simultaneous by adjusting the number of plots in the app, up to a maximum of 10.

Plotting Multiple plots

The plots are interactive and can be adjusted individually. Additionally, hovering over a particular transition highlights it and gives exact retention time, intensity and ID.

Alignment

Note, plotting and alignment my take up to 3 minutes per mzML selectd

Before plotting with alignment, ensure all inputs are set for regular chromatogram plotting above, and that the file organaization in Data preparation is followed.

In addition to the above, ensure the working directory in the app is set to the location of the mzml and osw folders. By default it looks in inst/extdata as this is where the folders are on installation.

Ensure 2 or more mzML files are selected and presented. Alignment works in a pairwise fashion, if fewer than two chromatograms are supplied, it will be plotted regularly.

Select a reference run for alignment. In the working example, chludwig_K150309_013_SW_0 is selected. It is recommended that for this example this not be changed as it is the highest concentration run and would provided most accurate alignment. Since alignment is conducted in a one against all fashion, this run will be aligned against all other runs.

Tick the "Plot aligned" checkbox to commence alignment and plotting.

Observing the first two aligned chromatograms, for runs 10 and 11 against run 13.

Observing the reference chromatogram, 13, against run 12:

Additionally, individual transitions can be selected/de selected from a particular aligned chromatogram to observe them.

Looking at a single or a few particular transitions:

Sample out of app session for simple plotting

          chrom_input <- "../inst/extdata/mzml/chludwig_K150309_013_SW_0.chrom.mzML"
          lib_input <- "../inst/extdata/PQP library/psgs.pqp"
          peptide <- "ANS(UniMod:21)SPTTNIDHLK(UniMod:259)"
          lib <- getPepLibData_(lib_input, peptide_id = '')
          g.out <- getXIC(graphic_obj = ggplot(), chromatogram_file = chrom_input,
                          df_lib = lib, mod = peptide, Isoform_Target_Charge = 2)
          plotly::ggplotly(g.out$graphic_obj, dynamicTicks = TRUE)