msms-compression 0.2.0

A tool for compressing MS/MS data

MS/MS Data Compression Package

Description

This Python package is designed for efficient compression of Mass Spectrometry (MS/MS) data. It is based on the MassComp algorithm, which is described in the following paper: https://doi.org/10.1186/s12859-019-2962-7

Version

0.2.0

Features

• Delta and Hex Encoding: Efficiently encodes m/z values and intensities to optimize the compression.
• Brotli Compression: Utilizes Brotli, a high-performance compression algorithm, offering superior compression ratios and speeds compared to gzip.

Installation

To install the MS/MS Data Compression package, run:

pip install msms-compression

Usage

The package includes the following main compressor classes:

• SpectrumCompressorUrl: Utilizes URL-safe Base64 encoding.
• SpectrumCompressor: Uses Base85 encoding.

• Note: The m/z values must be sorted in ascending order before compression, and contain only positive values.

Example:

from msms_compression import SpectrumCompressor

# Sample data
mz_values, intensity_values = [100.0, 101.0, 102.0], [10.0, 20.0, 30.0]

# Initialize the compressor
compressor = SpectrumCompressor()

# Compress data
compressed_data = compressor.compress(mz_values, intensity_values)
print("Compressed Data:", compressed_data)

# Decompress data
decompressed_mz, decompressed_intensity = compressor.decompress(compressed_data)
assert decompressed_mz == mz_values
assert decompressed_intensity == intensity_values

Compression Strategy Comparison

strategy	Compression Ratio	Compression Ratio Rank	URL Compression Ratio	URL Compression Ratio Rank	Compression Time	Compression Time Rank	Decompression Time	Decompression Time Rank
SpectrumCompressorLossy	5.952	1	5.023	1	0.030	3	0.008	1
SpectrumCompressor	3.890	2	3.299	5	0.054	5	0.009	3
SpectrumCompressorUrl	3.646	3	4.528	2	0.057	6	0.008	2
SpectrumCompressorGzip	3.148	4	2.658	6	0.026	2	0.009	5
SpectrumCompressorUrlGzip	2.951	5	3.665	3	0.024	1	0.009	4
SpectrumCompressorUrlLzstring	2.800	6	3.418	4	0.031	4	0.109	6

The lossy compression strategy converts each intensity to a 2 character hex string (which offers 256 unique values). This strategy is lossy, but offers the best compression ratio. M/Z values are losslessly compressed using delta encoding for all strategies, including lossy.