ms-collect 0.0.3.1

A series of modules that provide easy storage/accesss to Mass Spec related Raw Data/Groupings of Data.

ms-collect

A series of modules that provide easy storage/accesss to Mass Spec related Raw Data / Groupings of Data.

Note this package is currently in BETA and is under active development. Moreover, the docs are a work in progress.

Installation

pip install ms-collect

Background

In regions of m/z and Retention Time, there exists various signals, features, and collections of data. This package aims to provide an interface for intuitively representing that data and providing actions/visualizations on said collections.

MS-1 3D Plot	MS-1 3D Spectrum

ms-collect, at its core, provides a base Collection interface to which entities extend from.

For instance, this package has named entities that represent MS Features and Isotopic Traces. But fundamentally they are just a collection of points where each point has 3 primary attributes: mass to charge (m/z), Retention Time, and Intensity/Abundance.

It is often quite useful to visualize what is going on in these regions. The figures above were generated using this package.

Usage

This section includes very basic usage, refer to the examples section for more details/advanced usage. Coming soon: Docs via sphynx.

# Import the package and modules of interest
from ms_collect.scope import Scope
from ms_collect.envelope import Envelope
from ms_collection.point import Point
from ms_collection.collection import Collection


# Define a scope from an m/z and Retention Time region
min_mz = 437.844
max_mz = 438.94
min_rt = 946.004
max_rt = 981.107

my_scope = Scope([min_mz, max_mz, min_rt, max_rt])

# Define an MS-1 Feature/Envelope From said region with a list of Points.
my_points = [...]
my_envelope = Envelope(scope=my_scope, points=my_points)

# Define a point with some m/z, Retention Time, and Intensity values
point = Point(mz=542.3, rt=800.0, intensity=3447661568.0

# Add this point to the envelope and perform some basic envelope collection operations
my_envelope.add_points([point])
my_envelope.avg_mz()
# -> 436.32
my_envelope.cumulative_intensity()
# -> 933484802048.0

# Determine the convex hull of this collection
convexhull = my_envelope.convex_hull()
ch.hull()
# -> [(437.8870316623645, 958.66042827198), (437.88703282730677, 956.1165142560001), (437.8870410510394, 952.112642559), (437.8870495438886, 948.82877457498), (437.887053517079, 948.0991699829999), (437.88705863613876, 947.368067583),(438.22419874976924, 957.5778559199999), (438.2229531181884, 960.11862664002), (437.88945990101047, 962.3162991049801), (437.8882413409473, 961.2199352969999)]

# For some visual tools you have access to things like:
# (methods below render figures via a matplotlib backbone)

some_pts = [..]
collection = Collection(points=some_pts)

collection.three_d() # -> plots the points in 3d space.
collection.spectrum() # -> displays these points in a 'spectrum' fashion
collection.three_d_spectrum() # -> displays a spectrum in a 3d orientation.

Upcoming features

• Visual utilities for the various types of collections.
• Optimizations on resource intensive class methods.
• Better import/export and IO related functionality.
• Converting a collection to a dataframe.
• Better Api doc experience.
• If you would like to see something here we are accepting feature requests! Please submit an issue or ping us!

Contribute

Please refer to CONTRIBUTE.md for instructions on on contributing.