Validation of genotyping of gastrointestinal stromal tumor in Japan

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e21502-e21502
Author(s):  
T. Takahashi ◽  
T. Nishida ◽  
S. Sakurai ◽  
T. Kanda ◽  
A. Sawaki ◽  
...  
Keyword(s):  
Special Reference ◽  
Dna Extraction ◽  
Dna Sequence ◽  
Validation Study ◽  
Sequence Data ◽  
Extraction Methods ◽  
Reference Sequence ◽  
Sequencing Data ◽  
Dna Sequence Data ◽  
Pcr Method

e21502 Background: Most gastrointestinal stromal tumors (GIST) have activating mutations in the KIT or PDGFRA gene. Genotyping of GIST is important in Dx and Tx of GIST. Methods of genotyping using genomic DNA extracted from paraffin-embedded specimens are diverse and not standardized. We did validation study of genotyping using special reference to sequencing data obtained from cDNA from fresh GIST samples. Methods: Three DNA extraction methods (QIAamp, DEXPAT, or original) and four PCR methods (Ex Taq, AmpliTaq condition-1, AmpliTaq condition-2, or QIAGEN Tag) were compared using 20 paraffin-embedded specimens with special reference to sequencing data obtained from cDNA from corresponding 20 fresh GIST samples. After DNA extraction, KIT exon 9, 11, 13 and 17, and PDGFRA exon 12 and 18 were amplified by each PCR method using specific primers and directly sequenced. Results: In evaluation of PCR method, the protocol with Ex Taq showed 100% amplication of DNA and sequence agreement, the protocol with QIAGEN Tag 99%, and the protocol with AmpliTaq condition-2 86% agreement, and the protocol with AmpliTaq condition-1 showed much less amplication and higher disagreement. For the DNA extraction, the protocol with QIAamp showed best DNA extraction and its DNA sequence data were consistent with reference sequence in 98%, DNA sequence obtained using DEXPAT showed 33% consistency, and 89% of DNA sequence data obtained from an original method was agreed with reference data. Some modifications improved DNA amplication but inconsistent sequence data also increased probably due to miss-PCR. Conclusions: Each DNA extraction method had different quantity of DNA and four PCR methods showed different quality. Using this validation study, a standard genotyping method in Japan was established. No significant financial relationships to disclose.

scholarly journals Pattern Matching for DNA Sequencing Data Using Multiple Bloom Filters

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Maleeha Najam ◽  
Raihan Ur Rasool ◽  
Hafiz Farooq Ahmad ◽  
Usman Ashraf ◽  
Asad Waqar Malik
Keyword(s):  
Dna Sequencing ◽  
Dna Sequence ◽  
Pattern Matching ◽  
Dna Sequences ◽  
Sequence Data ◽  
Bloom Filters ◽  
Sequencing Data ◽  
Dna Sequence Data ◽  
Efficient Data ◽  
Improved Accuracy

Storing and processing of large DNA sequences has always been a major problem due to increasing volume of DNA sequence data. However, a number of solutions have been proposed but they require significant computation and memory. Therefore, an efficient storage and pattern matching solution is required for DNA sequencing data. Bloom filters (BFs) represent an efficient data structure, which is mostly used in the domain of bioinformatics for classification of DNA sequences. In this paper, we explore more dimensions where BFs can be used other than classification. A proposed solution is based on Multiple Bloom Filters (MBFs) that finds all the locations and number of repetitions of the specified pattern inside a DNA sequence. Both of these factors are extremely important in determining the type and intensity of any disease. This paper serves as a first effort towards optimizing the search for location and frequency of substrings in DNA sequences using MBFs. We expect that further optimizations in the proposed solution can bring remarkable results as this paper presents a proof of concept implementation for a given set of data using proposed MBFs technique. Performance evaluation shows improved accuracy and time efficiency of the proposed approach.

Advances in high throughput DNA sequence data compression

2016 ◽  
Vol 14 (03) ◽  
pp. 1630002 ◽  
Author(s):  
Muhammad Sardaraz ◽  
Muhammad Tahir ◽  
Ataul Aziz Ikram
Keyword(s):  
Data Compression ◽  
Dna Sequence ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Sequence Data ◽  
Sequencing Data ◽  
Research Directions ◽  
Compression Algorithms ◽  
Dna Sequence Data ◽  
Sequencing Technologies

Advances in high throughput sequencing technologies and reduction in cost of sequencing have led to exponential growth in high throughput DNA sequence data. This growth has posed challenges such as storage, retrieval, and transmission of sequencing data. Data compression is used to cope with these challenges. Various methods have been developed to compress genomic and sequencing data. In this article, we present a comprehensive review of compression methods for genome and reads compression. Algorithms are categorized as referential or reference free. Experimental results and comparative analysis of various methods for data compression are presented. Finally, key challenges and research directions in DNA sequence data compression are highlighted.

scholarly journals DNA sonification for public engagement in bioinformatics

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Heleen Plaisier ◽  
Thomas R. Meagher ◽  
Daniel Barker
Keyword(s):  
Dna Sequence ◽  
Public Engagement ◽  
Sequence Data ◽  
Sensory Perception ◽  
Data Representation ◽  
Sequence Information ◽  
Dna Sequence Data ◽  
Public Events ◽  
Dna Base ◽  
Alternative Means

Abstract Objective Visualisation methods, primarily color-coded representation of sequence data, have been a predominant means of representation of DNA data. Algorithmic conversion of DNA sequence data to sound—sonification—represents an alternative means of representation that uses a different range of human sensory perception. We propose that sonification has value for public engagement with DNA sequence information because it has potential to be entertaining as well as informative. We conduct preliminary work to explore the potential of DNA sequence sonification in public engagement with bioinformatics. We apply a simple sonification technique for DNA, in which each DNA base is represented by a specific note. Additionally, a beat may be added to indicate codon boundaries or for musical effect. We report a brief analysis from public engagement events we conducted that featured this method of sonification. Results We report on use of DNA sequence sonification at two public events. Sonification has potential in public engagement with bioinformatics, both as a means of data representation and as a means to attract audience to a drop-in stand. We also discuss further directions for research on integration of sonification into bioinformatics public engagement and education.

A new Liopeltis Fitzinger, 1843 (Squamata: Colubridae) from Pulau Tioman, Peninsular Malaysia

Zootaxa ◽  
2020 ◽  
Vol 4766 (3) ◽  
pp. 472-484
Author(s):  
HANNAH E. SOM ◽  
L. LEE GRISMER ◽  
PERRY L. JR. WOOD ◽  
EVAN S. H. QUAH ◽  
RAFE M. BROWN ◽  
...  
Keyword(s):  
Mitochondrial Dna ◽  
New Species ◽  
Dna Sequence ◽  
Rare Species ◽  
Sequence Data ◽  
Peninsular Malaysia ◽  
Tropical Asia ◽  
Dna Sequence Data ◽  
A New Species ◽  
Lines Of Evidence

Liopeltis is a genus of poorly known, infrequently sampled species of colubrid snakes in tropical Asia. We collected a specimen of Liopeltis from Pulau Tioman, Peninsular Malaysia, that superficially resembled L. philippina, a rare species that is endemic to the Palawan Pleistocene Aggregate Island Complex, western Philippines. We analyzed morphological and mitochondrial DNA sequence data from the Pulau Tioman specimen and found distinct differences to L. philippina and all other congeners. On the basis of these corroborated lines of evidence, the Pulau Tioman specimen is described as a new species, L. tiomanica sp. nov. The new species occurs in sympatry with L. tricolor on Pulau Tioman, and our description of L. tiomanica sp. nov. brings the number of endemic amphibians and reptiles on Pulau Tioman to 12. 

scholarly journals Self-organizing Clustering: Non-hierarchical Clustering for Large Scale DNA Sequence Data

2007 ◽  
Vol 3 ◽  
pp. 193-197 ◽  
Author(s):  
Kou Amano ◽  
Hiroaki Ichikawa ◽  
Hidemitsu Nakamura ◽  
Hisataka Numa ◽  
Kaoru Fukami-Kobayashi ◽  
...  
Keyword(s):  
Dna Sequence ◽  
Hierarchical Clustering ◽  
Large Scale ◽  
Sequence Data ◽  
Dna Sequence Data ◽  
Self Organizing
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