Literature DB >> 31430053

Lossless Compression of Cytometric Data.

Anne E Bras1, Vincent H J van der Velden1.   

Abstract

Nowadays, most cytometrists apply lossless compression by storing their FCS files in ZIP archives. Unfortunately, ZIP only achieves modest space savings in cytometric data, due to DEFLATE being used as the underlying lossless compression algorithm (LCA). Presumably, other modern LCA can outperform DEFLATE, especially in terms of space savings. Twenty-one codecs (programs implementing LCA) were evaluated in 167,131 publicly available FCS files. Within floating-point data, as produced by modern instruments, most favorable compression ratios (CRs) were achieved by ZPAQ (median 0.469), BCM (median 0.523), and LZMA (median 0.545). In comparison, the DEFLATE-based codecs only achieved median CR of 0.728 under the most optimal conditions. By default, ZIP offers nine compression level (CL) settings, where lower ZIP-CL optimizes for time efficiency, while higher ZIP-CL optimizes for space efficiency. Interestingly, the third ZIP-CL already resulted in near optimal CR in 90% of the files with floating-point data, as produced by digital cytometers. LZMA is well established, widely supported, and actively maintained (in sharp contrast to ZPAQ and BCM) and therefore arguably the most attractive alternative for ZIP. Within floating-point data, by shifting from ZIP (under optimal conditions) to LZMA (at default settings), the median CR can be improved by 25%. Based on our results, cytometrists can benefit from state-of-the-art compression by choosing the appropriate codec for their situation. Our results are likely to speed-up the adaptation of modern codecs, as CR around 0.5 were beyond all expectations, and such space savings will benefit the field of cytometry.
© 2019 International Society for Advancement of Cytometry. © 2019 International Society for Advancement of Cytometry.

Entities:  

Keywords:  acs files; deflate; fcs files; floating-point data; integer data; lossless compression; lzma; zip

Mesh:

Year:  2019        PMID: 31430053     DOI: 10.1002/cyto.a.23879

Source DB:  PubMed          Journal:  Cytometry A        ISSN: 1552-4922            Impact factor:   4.355


  3 in total

1.  Robust FCS Parsing: Exploring 211,359 Public Files.

Authors:  Anne E Bras; Vincent H J van der Velden
Journal:  Cytometry A       Date:  2020-07-15       Impact factor: 4.355

2.  Values of Contrast-Enhanced Ultrasound in Classification and Diagnosis of Common Bile Duct and Superficial Organ Lesions under Compression Algorithm.

Authors:  Yezhao Li; Caihong Zhao; Minpei Qin; Xia Zhang; Haizhen Liao; Haiqing Su
Journal:  J Healthc Eng       Date:  2021-09-29       Impact factor: 2.682

3.  Effect of decompression and online transmission on the dimensional changes of .stl files generated by intra-oral scanning.

Authors:  Juliano Martins Bueno; Carolina Guarniéri Gouveia; Mayara Barbosa Viandelli Mundim; Ademir Franco; José Luiz Cintra Junqueira; Monikelly do Carmo Chagas Nascimento
Journal:  PLoS One       Date:  2022-09-15       Impact factor: 3.752

  3 in total

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