BLANKA is a command line tool used to remove noise and blank background signals from mass spectrometry data.

This repo contains the publication version of BLANKA. For the current version please see https://github.com/gtluu/blanka_v1.

No installation is required for use of BLANKA. Simply download the scripts and place them in the desired directory. The config.ini file must be editted to include the path to a local installation of MSConvert before usage.

Python 2.7.15
argparse 1.3.0 or higher
pyteomics 3.5.1 or higher
numpy 1.15.4 or higher
pandas 0.24.0 0.23.4 or higher (the bug fix required is now a part of pandas 0.24.0) (must be released Nov 2018 or later - at the time of writing, Anaconda has the Aug 2018 release of pandas, and a newer release must be manually installed from Github or another repository)
subprocess
os
sys
multiprocessing
functools
copy

--sample : sample input directory with single or multiple files or sample .mzXML file
--control : LCQ/QTOF mode = control input file path with .mzXML file extension, DD mode = control sample spot name
--instrument : instrument/protocol used for experiment ('lcq', 'qtof', 'dd', or 'ims')\

--dd_template : dried droplet excel sheet with sample names (same template as IDBac) (required if instrument = 'dd')
--output : output directory for all generated files (default = sample directory)
--cpu : number of threads used (default = max-1)
--signal_noise_ratio : integer signal to noise ratio used for noise removal (default = 4)
--retention_time_tolerance : retention time tolerance range in seconds (default = 0.1 sec)
--precursor_mz_tolerance : absolute precursor m/z error tolerance in Da (default = 0.02 Da)
--peak_mz_tolerance : absolute precursor m/z error tolerance in Da (default = 0.02 Da)
--noise_removal_only : only perform noise removal (default = False)
--blank_removal_only : only perform blank removal (default = False)

Print usage information.
python blanka

Perform noise and blank removal on data actinomycetes.mzXML
python blanka --sample E:\lcms_data\actinomycetes.mzXML --control E:\lcms_data\media_control.mzXML --instrument lcq

Perform noise and blank removal on data found in E:\lcms_data and outputs data to E:\blanka_output
python blanka --sample E:\lcms_data --control E:\lcms_data\media_control.mzXML --output E:\blanka_output --instrument lcq

Perform noise and blank removal on data found in E:\lcms_data\sample using multiple control files found in E:\lcms_data\control
python blanka --sample E:\lcms_data\sample --control E:\lcms_data\control --output E:\blanka_output --instrument lcq

Convert .RAW data to .mzXML using MSConvert and perform noise and blank removal on actinomycetes.mzXML
python blanka --sample E:\lcms_data\actinomycetes.RAW --control E:\lcms_data\media_control.RAW --instrument lcq

Perform noise and blank removal on data actinomycetes.mzXML with custom retention time and precursor mz tolerance
python blanka --sample E:\lcms_data\actinomycetes.mzXML --control E:\lcms_data\media_control.mzXML --instrument lcq --retention_time_tolerance 0.5 --peak_mz_tolerance 0.1

Performs noise and blank removal on dried droplet maldi data using 'media_control' spots as control
python blanka --sample E:\maldi_data\ --control media_control --output E:\blanka_output --instrument dd

Performs blank removal only on dried droplet maldi data using 'media_control' spots as control
python blanka --sample E:\maldi_data\ --control media_control --output E:\blanka_output --instrument dd --blank_removal_only True