↓ Skip to main content

LymAnalyzer: a tool for comprehensive analysis of next generation sequencing data of T cell receptors and immunoglobulins

Overview of attention for article published in Nucleic Acids Research, October 2015
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 X users

Citations

dimensions_citation
45 Dimensions

Readers on

mendeley
116 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
LymAnalyzer: a tool for comprehensive analysis of next generation sequencing data of T cell receptors and immunoglobulins
Published in
Nucleic Acids Research, October 2015
DOI 10.1093/nar/gkv1016
Pubmed ID
Authors

Yaxuan Yu, Rhodri Ceredig, Cathal Seoighe

Abstract

The adaptive immune system includes populations of B and T cells capable of binding foreign epitopes via antigen specific receptors, called immunoglobulin (IG) for B cells and the T cell receptor (TCR) for T cells. In order to provide protection from a wide range of pathogens, these cells display highly diverse repertoires of IGs and TCRs. This is achieved through combinatorial rearrangement of multiple gene segments in addition, for B cells, to somatic hypermutation. Deep sequencing technologies have revolutionized analysis of the diversity of these repertoires; however, accurate TCR/IG diversity profiling requires specialist bioinformatics tools. Here we present LymAnalzyer, a software package that significantly improves the completeness and accuracy of TCR/IG profiling from deep sequence data and includes procedures to identify novel alleles of gene segments. On real and simulated data sets LymAnalyzer produces highly accurate and complete results. Although, to date we have applied it to TCR/IG data from human and mouse, it can be applied to data from any species for which an appropriate database of reference genes is available. Implemented in Java, it includes both a command line version and a graphical user interface and is freely available at https://sourceforge.net/projects/lymanalyzer/.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Netherlands 1 <1%
Korea, Republic of 1 <1%
Australia 1 <1%
Brazil 1 <1%
Canada 1 <1%
Belgium 1 <1%
United States 1 <1%
Unknown 108 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 39 34%
Student > Ph. D. Student 16 14%
Student > Master 10 9%
Professor 6 5%
Student > Postgraduate 6 5%
Other 19 16%
Unknown 20 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 28%
Biochemistry, Genetics and Molecular Biology 20 17%
Medicine and Dentistry 12 10%
Immunology and Microbiology 10 9%
Engineering 6 5%
Other 11 9%
Unknown 24 21%
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 09 October 2015.
All research outputs
#14,717,488
of 23,577,761 outputs
Outputs from Nucleic Acids Research
#21,658
of 26,681 outputs
Outputs of similar age
#146,248
of 279,587 outputs
Outputs of similar age from Nucleic Acids Research
#272
of 392 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 26,681 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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 279,587 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 392 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.