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Welcome to RawHummus
Robust and reproducible data is essential to ensure high-quality
analytical results and is particularly important for large-scale
metabolomics studies where detector sensitivity drifts, retention time
and mass accuracy shifts frequently occur. Therefore, raw data need to
be inspected before data processing to detect measurement bias and
verify system consistency.
RawHummus is an R Shiny app designed for an automated raw data
quality control (QC) in metabolomics studies. It produces a
comprehensive QC report, which contains interactive plots and tables,
summary statistics and detailed explanations.
If you are using Thermo Q-Exactive series instrument, RawHummus also
allows visualizing the log files (they are usually stored at
C:\Xcalibur\system\Exactive\log folder), which contains
over 40 different instrument metrics, such as ambient temperature and
ambient humidity.
Installation
You need to have R and optionally RStudio Installed. You can download
them from this link.
Next you can run this code to install RawHummus.
install.packages('RawHummus')
Usage
Once RawHummus is installed. You can run the following code to start
the web app.
library(RawHummus)
run_app()
Workflow and Features
Figure 1. Overview of the main functions in
RawHummus
Table 1. Overview of quality metrics used in
RawHummus report
| Chromatogram |
|
|
|
TIC plot |
It is total ion current at each scan plotted as an intensity point
for each raw file. Overlaid TIC plot is used for rapid inspection of RT
and ion intensity fluctuations. |
|
Summed TIC bar plot |
It is summed TIC of all scans in a raw file. It is used to check
global ion intensity variations among raw files. |
|
TIC correlation analysis |
Pairwise Pearson correlation analysis of raw files. It is used to
evaluate chromatogram similarity, i.e., peak shape similarity and RT
shift. Pearson correlation coefficient above 0.85 indicates that the two
raw files are similar. |
|
Max. mass difference (ppm) |
It is maximum m/z variation among each selected mass feature across
all the raw files. It is used to evaluate the mass accuracy. If the max.
mass difference is over 5 ppm, this value will be highlighted in
red. |
| MS1 |
|
|
|
Max. RT difference (min) |
It is maximum retention time variation among each selected mass
feature across all the raw files. It used to evaluate RT shifts. If the
max. RT difference is over 1 min, this value will be highlighted in
red. |
|
Max. intensity fold change |
It is the maximum intensity fold change among each selected mass
feature across all the raw files. It is used to evaluate ion intensity
variation. If max. intensity fold change is over 1.5, this value will be
highlighted in red. |
|
Intensity CV (%) |
It is intensity coefficient of variance (or relative standard
deviation, RSD) of each selected mass feature across all the raw files.
It is used to evaluate intensity variation. If intensity CV is over 30%,
this value will be highlighted in red. |
| MS2 |
|
|
|
No. of MS2 events |
It is number of triggered MS/MS spectra per file. It is used to
evaluate MS2 event |
|
Precursor ion distribution across mass plot |
It is density plot of the precursor ion across mass range based on
the triggered MS/MS events. |
|
Precursor ion distribution across RT plot |
It is density plot of the precursor ion across RT range based on the
triggered MS/MS events. |
|
Cosine similarity of precursor ion distribution across mass |
It measures the similarity of precursor ion distribution across
mass. Cosine similarity score above 0.85 indicates that the precursor
distributions across mass are similar between two files. |
|
Cosine similarity of precursor ion distribution across RT |
It measures the similarity of precursor ion distribution across
mass. Cosine similarity score above 0.85 indicates that the precursor
distributions across RT are similar between two files. |
Data Preparation
RawHummus supports mzXML and mzML formats for analysis, meaning that
you need to convert your raw data into one of the format.
It’s pretty easy to convert your raw data to the required format.
MSConvert is recommended for data conversion. ProteoWizard msConvert can
be download from this link.
GNPS has provided a detailed explanation regarding file conversion.
You can read the instruction here
Note that: For Waters MSe data, the precursor ion
and fragments are stored in two files, and RawHummus will only evaluate
the precursor ion.
Demo Data
A list of demo files have been provided, including log files and raw
data files. Please use this link to
download the demo data.
Citation
If you find this shiny App usful, please consider citing it:
Dong, Y., Kazachkova, Y., Gou, M., Morgan, L., Wachsman, T., Gazit,
E. and Birkler, R.I.D., 2022. RawHummus: an R Shiny App for Automated
Raw Data Quality Control in Metabolomics. Bioinformatics.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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