Isospec

Hyperfast Isotopic Structure Calculator.

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What is IsoSpec?

IsoSpec is a fine structure isotopic calculator.

It has been presented in a paper in Analytical Chemistry in 2017.

Given a molecular formula and some probability threshold 0 < P < 1, it will provide you with the smallest possible set of isotopologues that are jointly P probable.

Using IsoSpec? Cite us!

If you have used IsoSpec in your research, please cite it in your publications.

IsoSpec: Hyperfast Fine Structure Calculator Mateusz K. Łącki, Michał Startek, Dirk Valkenborg, and Anna Gambin Analytical Chemistry 2017 89 (6), 3272-3277 DOI: 10.1021/acs.analchem.6b01459

More information on the paper is HERE

Example

Say, that you happen to be interested in the top 50% probable isotopologues of Bovine Insulin. We happen to know, that its molecular formula is C254H377N65O75S6.

In that case, IsoSpec would provide you with:

  mass probability 1H 2H 12C 13C 14N 15N 16O 17O 18O 32S 33S 34S 36S
1 5731.6075806688 0.1123023514 377 0 252 2 65 0 75 0 0 6 0 0 0
2 5732.6109355040 0.1028778936 377 0 251 3 65 0 75 0 0 6 0 0 0
3 5730.6042258336 0.0814037470 377 0 253 1 65 0 75 0 0 6 0 0 0
4 5733.6142903392 0.0704027660 377 0 250 4 65 0 75 0 0 6 0 0 0
5 5734.6176451744 0.0383896060 377 0 249 5 65 0 75 0 0 6 0 0 0
7 5733.6033765247 0.0301636876 377 0 252 2 65 0 75 0 0 5 0 1 0
6 5729.6008709984 0.0293871014 377 0 254 0 65 0 75 0 0 6 0 0 0
8 5734.6067313599 0.0276323390 377 0 251 3 65 0 75 0 0 5 0 1 0
9 5732.6046155640 0.0266824062 377 0 252 2 64 1 75 0 0 6 0 0 0

Now, how this could be of any use to you? Well, we did suppose you are rather into …

Mass Spectrometry

Say you hoped to know, if Bovine Insulin is present in the sample you analyzed with your mass spectrometer. How would you do that?

You would use our software to generate the isotopologues and then try to find them in the experimental spectrum.

How to install IsoSpec?

IsoSpec is written in C++ has bindings to Python (IsoSpecPy), R (IsoSpecR), and C.

Python

IMPORTANT: please note that the Python package is standalone, in the sense that it does not need the C/C++ library to be installed separately.

Requirements:

pip install IsoSpecPy

alternatively, you can download our package from here and then

cd IsoSpecPy
sudo python setup.py install

Again, clang++ is the preferred compiler and will be used if found by the setup script. If you want to override the behaviour (if you have clang++ installed, but still want to use g++) you will have to replace the last command with:

ISO_USE_DEFAULT_CXX=TRUE sudo python setup.py install

R

Requirements:

The package is hosted at CRAN. This means that it can be automatically downloaded. Just start an R console (or R studio) and run

    install.packages('IsoSpecR')

Then, follow the instructions. For Windows users, this will result in downloading a precompiled version of the package.

The package can be also directly downloaded from this page. If you use either Linux of Mac OSX, then simply:

  1. Download the package.
  2. Move to the folder containing the IsoSpecR folder.
  3. Run in terminal
	R CMD build IsoSpecR 
	R CMD INSTALL IsoSpecR_1.0.tar.gz  

All necessary packages should download automatically.

C/C++

Requirements:

Note: clang++ is the default (and preferred) compiler as it produces faster code (in our tests, the difference in speed is about 20%). If you’d like to use g++ instead, please edit the first line of IsoSpec++/Makefile appropriately.

Next, execute the following commands:

cd IsoSpec++
make

You may copy the resulting .so file to a convenient location. If you wish to develop software using this library, you will also have to place the header files (.hpp/.h) somewhere your C/C++ compiler can find them.

Here are some example sessions:

Python

# Calculates the isotopic distribution of water in several ways

from IsoSpecPy import IsoSpecPy
from math import exp

i = IsoSpecPy.IsoSpec.IsoFromFormula("H2O1", 0.9)

print "The isotopologue set containing at least 0.9 probability has", len(i), "element(s)"

confs = i.getConfs()

print "The first configuration has the following parameters:"
print "Mass:", confs[0][0]
print "log(probability):", confs[0][1] 
print "probability:", exp(confs[0][1])
print "Number of Protium atoms:", confs[0][2][0][0]
print "Number of Deuterium atoms", confs[0][2][0][1]
print "Number of O16 atoms:", confs[0][2][1][0]
print "Number of O17 atoms:", confs[0][2][1][1]
print "Number of O18 atoms:", confs[0][2][1][2]

print
print "Now what if both isotopes of hydrogen were equally probable, while prob. of O16 was 50%, O17 at 30% and O18 at 20%?"

hydrogen_probs = (0.5, 0.5)
oxygen_probs = (0.5, 0.3, 0.2)
hydrogen_masses = (1.00782503207, 2.0141017778)
oxygen_masses = (15.99491461956, 16.99913170, 17.9991610)
atom_counts = (2, 1)

i = IsoSpecPy.IsoSpec(atom_counts, (hydrogen_masses, oxygen_masses), (hydrogen_probs, oxygen_probs), 0.9)

print "The isotopologue set containing at least 0.9 probability has", len(i), "element(s)"

confs = i.getConfs()

print "The first configuration has the following parameters:"
print "Mass:", confs[0][0]
print "log-prob:", confs[0][1]
print "probability:", exp(confs[0][1])
print "Number of Protium atoms:", confs[0][2][0][0]
print "Number of Deuterium atoms", confs[0][2][0][1]
print "Number of O16 atoms:", confs[0][2][1][0]
print "Number of O17 atoms:", confs[0][2][1][1]
print "Number of O18 atoms:", confs[0][2][1][2]

R

library(IsoSpecR)

# A water molecule:
water <- c(H=2,O=1)

# Desired joint probability p of the p-optimal set of isotopologues (90%): 
p <- .9

# The fancy representation of the results is on.
# ATTENTION: while turned on, the algorithm's time complexity is nlog(n) instead of linear.
res <- IsoSpecify( molecule=water, stopCondition=.99, fancy=TRUE )

print('The first configuration has the following parameters:')
print('Mass:');res$mass
print('log(probability):');res$logProb
print('probability:');res$prob
print('Number of Protium atoms:');res$H1
print('Number of Deuterium atoms:');res$H2
print('Number of O16 atoms:');res$O16
print('Number of O17 atoms:');res$O17
print('Number of O18 atoms:');res$O18

print("Now what if both isotopes of hydrogen were equally probable, while prob. of O16 was 50%, O17 at 30% and O18 at 20%?")
print('In R, we have to preper additional parameter for the algorithm: a data.frame containing the new isotopic ratios.')
modifiedIsotopes <- data.frame(
	element = c('H', 'H', 'O', 'O', 'O'),
	isotope = c('H1', 'H2', 'O16', 'O17', 'O18'),
	mass  	= c(1.00782503207, 2.0141017778,15.99491461956, 16.99913170, 17.9991610),
	abundance = c(0.5, 0.5,0.5, 0.3, 0.2)
)

modRes <- IsoSpecify( molecule=water, stopCondition=.99, fancy=TRUE, isotopes=modifiedIsotopes )

print('The number of configuration must be bigger, the probability being less concentrated on any isotope.')
modRes

C++


#include <iostream>
#include "../../IsoSpec++/isoSpec++.hpp"


int main()
{
    IsoSpec* iso = IsoSpec::IsoFromFormula("H2O1", 0.9);

    iso->processConfigurationsUntilCutoff();

    std::cout <<  "The isotopologue set containing at least 0.9 probability has " << iso->getNoVisitedConfs() << " element(s)" << std::endl;

    std::tuple<double*,double*,int*,int> product = iso->getCurrentProduct();

    double* masses = std::get<0>(product);
    double* logprobs = std::get<1>(product);
    int* configs = std::get<2>(product);

    std::cout << "The first configuration has the following parameters: " << std::endl;
    std::cout << "Mass: " << masses[0] << std::endl;
    std::cout << "log-prob: " << logprobs[0] << std::endl;
    std::cout << "probability: " << exp(logprobs[0]) << std::endl;

    // Successive isotopologues are ordered by the appearance in the formula of the element, then by nucleon number, and concatenated into one array
    std::cout << "Protium atoms: " << configs[0] << std::endl;
    std::cout << "Deuterium atoms " << configs[1] << std::endl;
    std::cout << "O16 atoms: " << configs[2] << std::endl;
    std::cout << "O17 atoms: " << configs[3] << std::endl;
    std::cout << "O18 atoms: " << configs[4] << std::endl;

    delete iso;
    delete masses;
    delete logprobs;
    delete configs;


    std::cout << "Now what if both isotopes of hydrogen were equally probable, while prob. of O16 was 50%, O17 at 30% and O18 at 20%?" << std::endl;

    const int elementNumber = 2;
    const int isotopeNumbers[2] = {2,3};

    const int atomCounts[2] = {2,1};


    const double hydrogen_masses[2] = {1.00782503207, 2.0141017778};
    const double oxygen_masses[3] = {15.99491461956, 16.99913170, 17.9991610};

    const double* isotope_masses[2] = {hydrogen_masses, oxygen_masses};

    const double hydrogen_probs[2] = {0.5, 0.5};
    const double oxygen_probs[3] = {0.5, 0.3, 0.2};

    const double* probs[2] = {hydrogen_probs, oxygen_probs};



    iso = new IsoSpecLayered(elementNumber, isotopeNumbers, atomCounts, isotope_masses, probs, 0.9);

    iso->processConfigurationsUntilCutoff();

    std::cout <<  "The isotopologue set containing at least 0.9 probability has " << iso->getNoVisitedConfs() << " element(s)" << std::endl;

    product = iso->getCurrentProduct();

    masses = std::get<0>(product);
    logprobs = std::get<1>(product);
    configs = std::get<2>(product);

    std::cout << "The first configuration has the following parameters: " << std::endl;
    std::cout << "Mass: " << masses[0] << std::endl;
    std::cout << "log-prob: " << logprobs[0] << std::endl;
    std::cout << "probability: " << exp(logprobs[0]) << std::endl;

    // Successive isotopologues are ordered by the appearance in the formula of the element, then by nucleon number, and concatenated into one array
    std::cout << "Protium atoms: " << configs[0] << std::endl;
    std::cout << "Deuterium atoms " << configs[1] << std::endl;
    std::cout << "O16 atoms: " << configs[2] << std::endl;
    std::cout << "O17 atoms: " << configs[3] << std::endl;
    std::cout << "O18 atoms: " << configs[4] << std::endl;

    delete iso;
    delete masses;
    delete logprobs;
    delete configs;
}

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