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Equivalent Indels – Ambiguous Functional Classes and Redundancy in Databases

Overview of attention for article published in PLOS ONE, May 2013
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Article details
Title
Equivalent Indels – Ambiguous Functional Classes and Redundancy in Databases
Published in
PLOS ONE, May 2013
DOI 10.1371/journal.pone.0062803
Pubmed ID
Authors
Abstract

There is considerable interest in studying sequenced variations. However, while the positions of substitutions are uniquely identifiable by sequence alignment, the location of insertions and deletions still poses problems. Each insertion and deletion causes a change of sequence. Yet, due to low complexity or repetitive sequence structures, the same indel can sometimes be annotated in different ways. Two indels which differ in allele sequence and position can be one and the same, i.e. the alternative sequence of the whole chromosome is identical in both cases and, therefore, the two deletions are biologically equivalent. In such a case, it is impossible to identify the exact position of an indel merely based on sequence alignment. Thus, variation entries in a mutation database are not necessarily uniquely defined. We prove the existence of a contiguous region around an indel in which all deletions of the same length are biologically identical. Databases often show only one of several possible locations for a given variation. Furthermore, different data base entries can represent equivalent variation events. We identified 1,045,590 such problematic entries of insertions and deletions out of 5,860,408 indel entries in the current human database of Ensembl. Equivalent indels are found in sequence regions of different functions like exons, introns or 5' and 3' UTRs. One and the same variation can be assigned to several different functional classifications of which only one is correct. We implemented an algorithm that determines for each indel database entry its complete set of equivalent indels which is uniquely characterized by the indel itself and a given interval of the reference sequence.

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The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 1 6%
Germany 1 6%
Unknown 15 88%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 4 24%
Student > Master 3 18%
Other 2 12%
Student > Ph. D. Student 2 12%
Student > Doctoral Student 1 6%
Other 2 12%
Unknown 3 18%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 35%
Agricultural and Biological Sciences 6 35%
Computer Science 1 6%
Medicine and Dentistry 1 6%
Unknown 3 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 27 May 2013.
All research outputs
#24,087,238
of 34,359,530 outputs
Outputs from PLOS ONE
#150,682
of 224,516 outputs
Outputs of similar age
#165,247
of 237,596 outputs
Outputs of similar age from PLOS ONE
#3,661
of 5,327 outputs
Altmetric has tracked 34,359,530 research outputs across all sources so far. This one is in the 28th percentile – i.e., 28% of other outputs scored the same or lower than it.
So far Altmetric has tracked 224,516 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.2. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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We're also able to compare this research output to 5,327 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.