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Norgal: extraction and de novo assembly of mitochondrial DNA from whole-genome sequencing data

Overview of attention for article published in BMC Bioinformatics, November 2017
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  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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Title
Norgal: extraction and de novo assembly of mitochondrial DNA from whole-genome sequencing data
Published in
BMC Bioinformatics, November 2017
DOI 10.1186/s12859-017-1927-y
Pubmed ID
Authors

Kosai Al-Nakeeb, Thomas Nordahl Petersen, Thomas Sicheritz-Pontén

Abstract

Whole-genome sequencing (WGS) projects provide short read nucleotide sequences from nuclear and possibly organelle DNA depending on the source of origin. Mitochondrial DNA is present in animals and fungi, while plants contain DNA from both mitochondria and chloroplasts. Current techniques for separating organelle reads from nuclear reads in WGS data require full reference or partial seed sequences for assembling. Norgal (de Novo ORGAneLle extractor) avoids this requirement by identifying a high frequency subset of k-mers that are predominantly of mitochondrial origin and performing a de novo assembly on a subset of reads that contains these k-mers. The method was applied to WGS data from a panda, brown algae seaweed, butterfly and filamentous fungus. We were able to extract full circular mitochondrial genomes and obtained sequence identities to the reference sequences in the range from 98.5 to 99.5%. We also assembled the chloroplasts of grape vines and cucumbers using Norgal together with seed-based de novo assemblers. Norgal is a pipeline that can extract and assemble full or partial mitochondrial and chloroplast genomes from WGS short reads without prior knowledge. The program is available at: https://bitbucket.org/kosaidtu/norgal .

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 126 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 126 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 21%
Researcher 27 21%
Student > Bachelor 18 14%
Student > Master 18 14%
Student > Doctoral Student 5 4%
Other 9 7%
Unknown 22 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 48 38%
Biochemistry, Genetics and Molecular Biology 30 24%
Computer Science 9 7%
Engineering 5 4%
Environmental Science 2 2%
Other 3 2%
Unknown 29 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 January 2023.
All research outputs
#6,641,433
of 25,081,505 outputs
Outputs from BMC Bioinformatics
#2,301
of 7,644 outputs
Outputs of similar age
#120,426
of 449,979 outputs
Outputs of similar age from BMC Bioinformatics
#37
of 150 outputs
Altmetric has tracked 25,081,505 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 7,644 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 69% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 449,979 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 150 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.