:: DESCRIPTION
QualComp is a lossy compression algorithm for the quality scores presented in a FASTQ file.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
BMC Bioinformatics. 2013 Jun 8;14:187. doi: 10.1186/1471-2105-14-187.
QualComp: a new lossy compressor for quality scores based on rate distortion theory.
Ochoa I1, Asnani H, Bharadia D, Chowdhury M, Weissman T, Yona G.
:: DESCRIPTION
libCSAM will contain several C++ codes for compress,decompress, and access each of the fields of any SAM format file.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2014 May 2.
Lossy compression of quality scores in genomic data.
Cánovas R1, Moffat A, Turpin A.
:: DESCRIPTION
HaMMLET is a fast Forward-Backward Gibbs sampler for Bayesian inference on Hidden Markov Models (HMM). It uses the Haar wavelet transform to dynamically compress the data based on the current variance sample in each iteration.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Fast Bayesian Inference of Copy Number Variants using Hidden Markov Models with Wavelet Compression.
Wiedenhoeft J, Brugel E, Schliep A.
PLoS Comput Biol. 2016 May 13;12(5):e1004871. doi: 10.1371/journal.pcbi.1004871.
:: DESCRIPTION
SNPack is a novel algorithm and file format for compressing and retrieving SNP data, specifically designed for large-scale association studies.
::DEVELOPER
SYSTEMS BIOLOGY AND BIOINFORMATICS GROUP
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2014 Jul 26. pii: btu495.
Compression and fast retrieval of SNP data.
Sambo F, Di Camillo B, Toffolo G, Cobelli C.
:: DESCRIPTION
DNA-COMPACT is a software of DNA COMpression based on a pattern-aware contextual modeling technique.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
PLoS One. 2013 Nov 25;8(11):e80377. doi: 10.1371/journal.pone.0080377. eCollection 2013.
DNA-COMPACT: DNA COMpression based on a pattern-aware contextual modeling technique.
Li P1, Wang S, Kim J, Xiong H, Ohno-Machado L, Jiang X.
:: DESCRIPTION
samcomp is a simple arithmetic coding based compressor for the SAM and BAM (DNA sequence alignment) file format.
::DEVELOPER
James K. Bonfield (jkb@sanger.ac.uk), Matt Mahoney
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bonfield JK, Mahoney MV (2013)
Compression of FASTQ and SAM Format Sequencing Data.
PLoS ONE 8(3): e59190. doi:10.1371/journal.pone.0059190
:: DESCRIPTION
LW-FQZip is a lossless light-weight reference-based compression tool for FASTQ data.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Light-weight reference-based compression of FASTQ data.
Zhang Y, Li L, Yang Y, Yang X, He S, Zhu Z.
BMC Bioinformatics. 2015 Jun 9;16(1):188. doi: 10.1186/s12859-015-0628-7.
:: DESCRIPTION
LFQC is a new lossless non-reference based fastq compression algorithm.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
LFQC: A lossless compression algorithm for FASTQ files.
Nicolae M, Pathak S, Rajasekaran S.
Bioinformatics. 2015 Jun 20. pii: btv384.
:: DESCRIPTION
Oculus is a bioinformatic algorithm designed to increase sequence alignment speed for redundant input. It acts as a wrapper around any existing alignment algorithm capable of producing SAM-formatted output.
::DEVELOPER
The Michigan Center for Translational Pathology
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
BMC Bioinformatics. 2012 Nov 13;13:297. doi: 10.1186/1471-2105-13-297.
Oculus: faster sequence alignment by streaming read compression.
Veeneman BA1, Iyer MK, Chinnaiyan AM.
:: DESCRIPTION
Kolmogorov is a multistep approach to classify and cluster Biological Sequences and Structures, via Compression.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
BMC Bioinformatics. 2007 Jul 13;8:252.
Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.
Ferragina P1, Giancarlo R, Greco V, Manzini G, Valiente G.
