scholarly journals VarSifter: Visualizing and analyzing exome-scale sequence variation data on a desktop computer

2011 ◽  
Vol 28 (4) ◽  
pp. 599-600 ◽  
Author(s):  
Jamie K. Teer ◽  
Eric D. Green ◽  
James C. Mullikin ◽  
Leslie G. Biesecker
Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1127 ◽  
Author(s):  
Malinverni ◽  
Barducci

Extracting structural information from sequence co-variation has become a common computational biology practice in the recent years, mainly due to the availability of large sequence alignments of protein families. However, identifying features that are specific to sub-classes and not shared by all members of the family using sequence-based approaches has remained an elusive problem. We here present a coevolutionary-based method to differentially analyze subfamily specific structural features by a continuous sequence reweighting (SR) approach. We introduce the underlying principles and test its predictive capabilities on the Response Regulator family, whose subfamilies have been previously shown to display distinct, specific homo-dimerization patterns. Our results show that this reweighting scheme is effective in assigning structural features known a priori to subfamilies, even when sequence data is relatively scarce. Furthermore, sequence reweighting allows assessing if individual structural contacts pertain to specific subfamilies and it thus paves the way for the identification specificity-determining contacts from sequence variation data.


Data in Brief ◽  
2019 ◽  
Vol 24 ◽  
pp. 103532 ◽  
Author(s):  
Badrul Munir Md-Zain ◽  
Aqilah Abdul-Aziz ◽  
Nor Rahman Aifat ◽  
Nur Syafika Mohd-Yusof ◽  
Nadiatur Akmar Zulkifli ◽  
...  

2013 ◽  
Vol 48 (3) ◽  
pp. 206 ◽  
Author(s):  
Ja Young Seo ◽  
Mi-Ae Jang ◽  
Hee-Jung Kim ◽  
Ki-O Lee ◽  
Sun-Hee Kim ◽  
...  

Author(s):  
Michael Watkins ◽  
Wendy Kohlmann ◽  
Therese Berry ◽  
Neetha Sama ◽  
Cathryn Koptiuch ◽  
...  

While there are several public repositories of biological sequence variation data and associated annotations, there is little open-source tooling designed specifically for the upkeep of local collections of variant data. Many clinics curate and maintain such local collections and are burdened by frequent changes in the representation of those variants and evolving interpretations of clinical significance. A dictionary of genetic variants from the Huntsman Cancer Institute was analyzed over a period of two years and used to inform the development of LocalVar. This tool is institution-agnostic and uses publicly available ClinVar files to provide the following functionality: auto-complete search bar to pre-empt duplicate entries; single or bulk new variant record entry; auto-detection and merge suggestions for duplicate variant records; auto-detection and merge suggestions for variant records with HGVS expressions that are marked as synonyms in ClinVar; asynchronous suggestion of HGVS expression or variant interpretation updates; history tracking of additions, merges, updates, or other manual edits made to variant records; and the easy export of the collection (.csv), edit history (.json), or HGVS synonym bins (.json).


2014 ◽  
Vol 43 (D1) ◽  
pp. D87-D91 ◽  
Author(s):  
Ayako Suzuki ◽  
Hiroyuki Wakaguri ◽  
Riu Yamashita ◽  
Shin Kawano ◽  
Katsuya Tsuchihara ◽  
...  

2013 ◽  
Vol 35 (6) ◽  
pp. 685-694
Author(s):  
Ting-Zhang WANG ◽  
Gao SHAN ◽  
Jian-Hong XU ◽  
Qing-Zhong XUE

2009 ◽  
Author(s):  
Robert J. Pleban ◽  
Jennifer S. Tucker ◽  
Vanessa Johnson Katie /Gunther ◽  
Thomas R. Graves

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