scholarly journals Simultaneous human platelet antigen genotyping and detection of novel single nucleotide polymorphisms by targeted next-generation sequencing

Transfusion ◽  
2017 ◽  
Vol 57 (6) ◽  
pp. 1497-1504 ◽  
Author(s):  
Sue Davey ◽  
Cristina Navarrete ◽  
Colin Brown
Gene Reports ◽  
2017 ◽  
Vol 6 ◽  
pp. 81-86 ◽  
Author(s):  
Kiran Dashrath Rasal ◽  
Vemlawada Chakrapani ◽  
Amrendra Kumar Pandey ◽  
Avinash Rambhau Rasal ◽  
Jitendra K. Sundaray ◽  
...  

2018 ◽  
Author(s):  
Shashidhar Ravishankar ◽  
Sarah E. Schmedes ◽  
Dhruviben S. Patel ◽  
Mateusz Plucinski ◽  
Venkatachalam Udhayakumar ◽  
...  

AbstractRapid advancements in next-generation sequencing (NGS) technologies have led to the development of numerous bioinformatics tools and pipelines. As these tools vary in their output function and complexity and some are not well-standardized, it is harder to choose a suitable pipeline to identify variants in NGS data. Here, we present NeST (NGS-analysis Toolkit), a modular consensus-based variant calling framework. NeST uses a combination of variant callers to overcome potential biases of an individual method used alone. NeST consists of four modules, that integrate open-source bioinformatics tools, a custom Variant Calling Format (VCF) parser and a summarization utility, that generate high-quality consensus variant calls. NeST was validated using targeted-amplicon deep sequencing data from 245 Plasmodium falciparum isolates to identify single-nucleotide polymorphisms conferring drug resistance. The results were verified using Sanger sequencing data for the same dataset in a supporting publication [28]. NeST offers a user-friendly pipeline for variant calling with standardized outputs and minimal computational demands for easy deployment for use with various organisms and applications.


2017 ◽  
Author(s):  
Claire Marchal ◽  
Takayo Sasaki ◽  
Daniel Vera ◽  
Korey Wilson ◽  
Jiao Sima ◽  
...  

ABSTRACTCycling cells duplicate their DNA content during S phase, following a defined program called replication timing (RT). Early and late replicating regions differ in terms of mutation rates, transcriptional activity, chromatin marks and sub-nuclear position. Moreover, RT is regulated during development and is altered in disease. Exploring mechanisms linking RT to other cellular processes in normal and diseased cells will be facilitated by rapid and robust methods with which to measure RT genome wide. Here, we describe a rapid, robust and relatively inexpensive protocol to analyze genome-wide RT by next-generation sequencing (NGS). This protocol yields highly reproducible results across laboratories and platforms. We also provide computational pipelines for analysis, parsing phased genomes using single nucleotide polymorphisms (SNP) for analyzing RT allelic asynchrony, and for direct comparison to Repli-chip data obtained by analyzing nascent DNA by microarrays.


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