Versatile and open software for comparing large genomes
By Stefan Kurtz, Adam M. Phillippy, Arthur L. Delcher, Michael E. Smoot, Martin Shumway, Corina Antonescu, Steven L. Salzberg. Genome Biology, 2004
5,300 citations recorded by the source corpus.
The newest version of MUMmer easily handles comparisons of large eukaryotic genomes at varying evolutionary distances, as demonstrated by applications to multiple genomes. Two new graphical viewing tools provide alternative ways to analyze genome alignments. The new system is the first version of MUMmer to be released as open-source software. This allows other developers to contribute to the code base and freely redistribute the code. The MUMmer sources are available at http://www.tigr.org/software/mummer.
Subfields: Molecular Biology, Plant Science
View Paper: https://www.semanticscholar.org/paper/6b781f595ad87bb6d50837e4d4c4984963490a6c
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In Molecular Biology
- Steven L. Salzberg
- Heng Li
- Adam M. Phillippy
- Sergey Koren
- Mihai Pop
- Michael C. Schatz
- Markus Göker
- Kathryn E. Holt
In Plant Science
- Guillaume Marçais
- Steven L. Salzberg
- Heng Li
- Sergey Koren
- Markus Göker
- Adam M. Phillippy
- Hans-Peter Klenk
- Mihai Pop
Citations in the corpus
- Circlator: automated circularization of genome assemblies using long sequencing reads (2015, methodology): “The contigs of the resulting SPAdes assembly are aligned to the original assembly using the nucmer program of MUMmer [16] with options --maxmatch --diagdiff 25 , and hits with identity of at least 95% are retained using delta-filter -i 95 .”
- High-throughput sequence alignment using Graphics Processing Units (2007, methodology): “In particular, all programs in the NUCmer suite of programs that use the output of mummer, including those that extend the exact alignment seeds to larger inexact alignments, can take advantage of the GPU paralellization [4-6].”
- Tracking Changes in SARS-CoV-2 Spike: Evidence that D614G Increases Infectivity of the COVID-19 Virus (2020, positive): “Hundreds of new SARS-CoV-2 sequences are added to GISAID each day, so we have automated steps to create daily working alignments (Kurtz et al., 2004; Figure S1).”
- Assembling the 20 Gb white spruce (Picea glauca) genome from whole-genome shotgun sequencing data (2013, background): “Assembly execution times are given in Supplementary Table S1.”
- SyMAP v3.4: a turnkey synteny system with application to plant genomes (2011, methodology): “SyMAP incorporates the MUMmer program (29) to compute the raw hits, which are clustered and filtered to form anchors, where a region may be in multiple anchors in order to detect duplications; the filtered anchors are input into the synteny algorithm, which is unchanged from version 1.”
- Real-time, portable genome sequencing for Ebola surveillance (2016, background): “England, Porton Down, Wiltshire SP4 0JG, UK (12)Friedrich-Loeffler-Institute, Greifswald, Germany (13)Spiez Laboratory, Spiez, Switzerland (14)Janssen-Cilag, Stockholm, Sweden (15)Public Health Agency of Canada, Winnipeg, Canada (16)Institut Pasteur Dakar, Dakar, Senegal (17)Laboratoire de Fièvres H”
- Propionibacterium acnes strain populations in the human skin microbiome associated with acne (2013, methodology): “Comparative genome analysis Seventy-one P. acnes genome sequences were compared using Nucmer (Kurtz et al., 2004).”
- Fast Statistical Alignment (2009, methodology): “FSA’s basic anchoring mode uses the fast suffix trie matching program MUMmer [16] to find candidate anchors and can find anchors in either nucleotide or protein space (by translating the sequence in all frames).”
- Genomic Analysis of the Necrotrophic Fungal Pathogens Sclerotinia sclerotiorum and Botrytis cinerea (2011, methodology): “Genome alignment and synteny Genome assemblies were aligned using MUMmer [139].”
- SeqAn An efficient, generic C++ library for sequence analysis (2008, methodology): “, Lagan [7], MUMmer [8], MGA [9], Mauve [10]).”
- Shining a Light on Dark Sequencing: Characterising Errors in Ion Torrent PGM Data (2013, methodology): “22 [21] (program ‘repeat-match’ with parameter –n 30) was used to identify regions of perfect match repeats within the reference genomes.”
- Performance of neural network basecalling tools for Oxford Nanopore sequencing (2019, methodology): “To classify consensus sequence errors by type, we aligned each assembly to the reference using NUCmer13 (v3.”