What is SPIKE ?¶
SPIKE a collaborative development for a FT-spectroscopy processing program.
This is the version 0.99.15 - January 2020
SPIKE is a program that allows the processing, the display and the analysis of data-sets obtained from various Fourier-Transform spectroscopies. The name stands for Spectrometry Processing Innovative KErnel.
It allows the processing of 1D and 2D FT spectroscopies, implementing Real, Complex and HyperComplex n-dimensionnal Fourier Transform, as well as many other functionalities.
It is written in python (tested in python 3.7 and in python 2.7 up to
version 0.99.10) and can be used as a set of tools, using for instance
jupyter notebook
as an interactive front-end.
To our knowledge, it is the first program freely available allowing the processing, display and analysis of 2D-FT-ICR (Fourier Transform Ion Cyclotron Resonance), as well as Orbitrap time domain data. processing.
It is still in very active development. Many features are missing, and many other while present, are not fully fixed. However, considering the amount of efforts already present in this code, we decided to make it available. We believe that even in this partial development stage, this program might prove useful for certain usages.
Citing SPIKE¶
If you happen to use SPIKE successfully please cite it, and refer to this site, as well as the following possible references :
first publication of the program itself - rejected from Anal. Chem. Reviewer 1 said “too much NMR”, Reviewer 2 said “too much MS”, !!
Chiron L., Coutouly M-A., Starck J-P., Rolando C., Delsuc M-A. SPIKE a Processing Software dedicated to Fourier Spectroscopies https://arxiv.org/abs/1608.06777 (2016)
first version of the python set-up on which the current SPIKE is partially based
Tramesel, D., Catherinot, V. & Delsuc, M.-A. Modeling of NMR processing, toward efficient unattended processing of NMR experiments. J Magn Reson 188, 56-67 (2007).
first version of the 2D FT-ICR-MS processing
van Agthoven, M. A., Chiron, L., Coutouly, M.-A., Delsuc, M.-A. & Rolando, C. Two-Dimensional ECD FT-ICR Mass Spectrometry of Peptides and Glycopeptides. Anal Chem 84, 5589-95 (2012).
presentation of the automation possibilities in NMR
Margueritte, L., Markov, P., Chiron, L., Starck, J.-P., Vonthron Sénécheau, C., Bourjot, M., & Delsuc, M.-A. (2018). Automatic differential analysis of NMR experiments in complex samples. Magn. Reson. Chem., 80(5), 1387. http://doi.org/10.1002/mrc.4683
ref 1) is a general purpose reference, the other ones are more specific.
SPIKE features¶
FT analysis of 1D data-sets
apodisation, phasing, modulus, …
Analysis of 2D data-sets
phase or amplitude modulation
complex or hyper-complex algebra
Robust processing
no limit in data-set size
parallel processing of the heaviest processing
on multi-core desktop using standard python ressources
on large clusters, using MPI library
High-Level features
noise reduction (filtering, Linear-Prediction, Cadzow, urQRd, sane, …)
automatic or manual baseline correction
NUS data processing
1D and 2D Peak-Picker
Plugin architecture
allow easy extension of the core program
reduces cross dependences
Complete spectral display using matplotlib or bokeh transparently
zoom, available in several units (depending on the spectroscopy : seconds, Hz, ppm, m/z, etc…)
store to png or pdf
interaction with the Jupyter Notebook environment
Handles the following Spectroscopies¶
NMR
1D and 2D are fully supported
DOSY
no nD yet
relaxation data in progress
FT-ICR
1D and 2DFT are fully supported
LC-MS in progress
Orbitrap
1D only (!)
other spectroscopies are being considered
Files can be imported from¶
NMR:
Bruker Topspin
NMRNoteBook
NPK - Gifa
SpinIt
FT-ICR:
Bruker Apex
Bruker Solarix
Orbitrap:
Thermofisher raw data
Other
csv and txt files
any data in memory in a
Numpy
buffer.
Usage¶
As a processing library¶
SPIKE is primary meant for being used as a library, code can as simple as :
from spike.File import Solarix
dd = Solarix.Import_1D('FTICR-Files/ESI_pos_Ubiquitin_000006.d') # Import create a basic SPIKE object
dd.hamming().zf(2).rfft().modulus() # we have a simple piped processing scheme
# here doing apodisation - zerofilling (doubling the size) - FT and modulus.
# calibration is imported from Bruker - advanced calibration is available
dd.unit = "m/z"
dd.display(zoom=(500,2000)) # display the spectrum for m/z ranging from 500 to 2000
dd.pp(threshold=1E7) # peak-pick the spectrum in this range
dd.centroid() # compute centroids
dd.display(zoom=(856.5, 858.5)) # and zoom on the isotopic peak
dd.display_peaks(zoom=(856.5, 858.5), peak_label=True)
interactive mode¶
SPIKE allows to process datasets interactively from an jupyter (IPython)
prompt, and is perfectly working in jupyter notebook
or even
jupyter lab
Look at the examples files (
eg_*.py
and*.ipynb
) for examples and some documentation. ( * not fully up to data * )display is performed using the
Matplotlib
library.large 2D-FT-ICR are handled in batch using the
processing.py
batch program, controlled by parameter file called*.mscf
The batch mode supports multiprocessing, both with MPI and natively on multi-core machines (still in-progress)
large 2D-FT-ICR are stored in a hierarchical format, easyly displayed with an interactive program.
data-sets are handled in the HDF5 standard file-format, which allows virtually unlimited file size ( tested up to 500 Gb ).
running stand-alone programs¶
processing.py and visu2D.py are two stand alone programs, written on the top of SPIKE. - processing.py allowing the efficient processing of FT-ICR 2D datasets, with no limit on the size of the final file Produces multi-resolution files
syntax :
python -m spike.processing param_file.mscf
How do I get SPIKE ?¶
SPIKE is written in pure Python, and relies on several external libraries. It is compatible and fully tested with python 3.7 (many parts are still compatible with python 2.7 but this is not tested)
dependencies¶
However it relies on mathematical libraries which should be installed independently.
matplotlib
numpy
scipy
tables
pandas
some plugins or extension require additional libraries (ipympl
,
MPI
, bokeh
, mayavi
, …)
installation¶
To get it, you can simply - rely on a scientific distribution such as Anaconda or Enthough - install the above python distributions yourself (tricky)
Then you can install it using pip:
pip install spike-py
Or, if you want to play with the code, and get the bleeding edge version.
hg clone
get the devel branch and keep it up-to-date(will be move to git soon)
python setup.py install
or, if you do not want to instal it permanently
python setup.py develop
using pip
pip install spike_py
History¶
SPIKE is originated from the Gifa program, developed by M-A Delsuc
and others in FORTRAN 77
since the late eighties. Gifa has known
several mutations, and finally ended as a partial rewrite called
NPK. The NPK program is based on
some of the original FORTRAN
code, wrapped in Java and Python, which
allows to control all the program possibilities from the Python level.
NPK is purely a computing kernel, with no graphical possibilities, and
has been used as a kernel embedded in the commercial program
NMRNoteBook, commercialized by NMRTEC.
However, NPK was showing many weaknesses, mostly due to the 32bits organization, and a poor file format. So, when a strong scientific environment became available in Python, a rewrite in pure Python was undertaken. To this initial project, called NPK-V2, many new functionalities were added, and mostly the capability to work in other spectroscopies than NMR.
At some point in 2014, we chose to fork NPK-V2 to SPIKE, and make it public.
Developing for SPIKE¶
SPIKE is an open-source program, this means that external
contributions are welcomed. If you believe your improvement is useful
for other people, please submit a pull request
. Note that pull
request should be associated to the devel
branch. This branch is
devoted to new features not fully tested yet and still susceptible of
changes, while the default
branch is meant for stable code.
plugins¶
If you consider adding some new feature, it is probably a good idea to
implement it as a plugin. The code contains already quite a few plugins,
some are quite sophisticated - see Peaks.py
for instance which
implements a 1D and 2D peak picker, as well as a centroid evaluation and
a full listing capability.
You can check also fastclean.py
for a very simple plugin, or
wavelet.py
for a plugin relying on an external library which has to
be installed.
Some Good Practice¶
Spike contains many tools, most of the basic function for data interaction are found in the
NPKData.py
master file; utilities are also scattered in theutil
module. Use then, life will be easier for the users.Please write tests, even for the plugins ! We use standard python
unittest
, so nothing fancy. All the tests are run automatically every night (code isTests.py
), so it will detect rapidly all potential problem.push your pull requests to the
devel
branch -default
is for the stable releases.
Organisation of the Code¶
The main program is NPKData.py
, which defines NPKData object on
which everything is built.
Spectroscopies are defined in the NMR.py
, FTICR.py
and
Orbitrap.py
code, which sub class NPKData.
Many programs contain routines tests (in an object unittest) that also
serve as an example of use. The code goes through extensive tests daily,
using the unittest
Python library. However, many tests rely on a set
of tests data-sets which is more than 1Go large, and not distributed
here.
Main programs :¶
a small description of the files:
NPKData.py the main library, allows all processing for any kind of experiments (1D, 2D and 3D) to be used as a library, in a stand-alone program or in IPython interactive session
NMR.py The NPKData library adapted to NMR processing
FTICR.py an extension of NPKData for processing FT-ICR datasets (1D and 2D)
Orbitrap.py an extension of NPKData for processing Orbitrap datasets (1D)
processing.py a stand alone program, written on the top of FTICR.py, allowing the efficient processing of FT-ICR 2D datasets, with no limit on the size of the final file Produces multi-resolution files syntax :
python -m spike.processing param_file.mscf
Directories¶
Algo contains algorithms to process data-sets (MaxEnt, Laplace, etc…) not everything active !
Display a small utility to choose either for regular Matplotlib display of fake no-effect display (for tests)
File Importers for various file format for spectrometry, as well as the HDF5 SPIKE native format.
plugins Tools automatically plugged in NPK kernel : display utilities, urQRd algorithm and various other tools.
Miscellaneous “en vrac”
util set of low-level tools used all over in the code
v1 a library implementing a partial compatibility with the NPKV_V1 program
SPIKE_usage_eg example of Python programs using the various libraries available
example of configuration files
process_eg.mscf
test.mscf
and various utilities
NPKConfigParser.py reads .mscf files
NPKError.py generates error msg
QC.py Quality Check
Tests.py runs all tests
dev_setup.py rolls a new version
version.py defines version number
_init_.py defines library
rcpylint
To_Do_list.txt
QC.txt
Release.txt
Authors and Licence¶
Current Active authors for SPIKE are:
Marc-André Delsuc
madelsuc -at- unistra.fr
Laura Duciel
laura.duciel -at- casc4de.eu
Previous authors:
Christian Rolando
christian.rolando -at- univ-lille1.fr
Lionel Chiron
Lionel.Chiron -at- casc4de.eu
Petar Markov
petar.markov -at- igbmc.fr
Marie-Aude Coutouly .
Marie-Aude.COUTOULY - at- datastorm.fr
Covered code is provided under this license on an “as is” basis, without warranty of any kind, either expressed or implied, including, without limitation, warranties that the covered code is free of defects. The entire risk as to the quality and performance of the covered code is with you. Should any covered code prove defective in any respect, you (not the initial developer or any other contributor) assume the cost of any necessary servicing, repair or correction.
Downloading code and datasets from this page signifies acceptance of the hereunder License Agreement. The code distributed here is covered under the CeCILL license : http://www.cecill.info/index.en.html