scholarly journals Big data from small samples: Informatics of next-generation sequencing in cytopathology

2016 ◽  
Vol 125 (4) ◽  
pp. 236-244 ◽  
Author(s):  
Sinchita Roy-Chowdhuri ◽  
Somak Roy ◽  
Sara E. Monaco ◽  
Mark J. Routbort ◽  
Liron Pantanowitz
Biotechnology ◽  
2019 ◽  
pp. 804-837
Author(s):  
Hithesh Kumar ◽  
Vivek Chandramohan ◽  
Smrithy M. Simon ◽  
Rahul Yadav ◽  
Shashi Kumar

In this chapter, the complete overview and application of Big Data analysis in the field of health care industries, Clinical Informatics, Personalized Medicine and Bioinformatics is provided. The major tools and databases used for the Big Data analysis are discussed in this chapter. The development of sequencing machines has led to the fast and effective ways of generating DNA, RNA, Whole Genome data, Transcriptomics data, etc. available in our hands in just a matter of hours. The complete Next Generation Sequencing (NGS) huge data analysis work flow for the medicinal plants are discussed in the chapter. This chapter serves as an introduction to the big data analysis in Next Generation Sequencing and concludes with a summary of the topics of the remaining chapters of this book.


2016 ◽  
Vol 9 (2) ◽  
pp. 119-149 ◽  
Author(s):  
Rashmi Tripathi ◽  
Pawan Sharma ◽  
Pavan Chakraborty ◽  
Pritish Kumar Varadwaj

Author(s):  
Hithesh Kumar ◽  
Vivek Chandramohan ◽  
Smrithy M. Simon ◽  
Rahul Yadav ◽  
Shashi Kumar

In this chapter, the complete overview and application of Big Data analysis in the field of health care industries, Clinical Informatics, Personalized Medicine and Bioinformatics is provided. The major tools and databases used for the Big Data analysis are discussed in this chapter. The development of sequencing machines has led to the fast and effective ways of generating DNA, RNA, Whole Genome data, Transcriptomics data, etc. available in our hands in just a matter of hours. The complete Next Generation Sequencing (NGS) huge data analysis work flow for the medicinal plants are discussed in the chapter. This chapter serves as an introduction to the big data analysis in Next Generation Sequencing and concludes with a summary of the topics of the remaining chapters of this book.


2014 ◽  
Vol 139 (4) ◽  
pp. 508-517 ◽  
Author(s):  
Birgitte B. Simen ◽  
Lina Yin ◽  
Chirayu P. Goswami ◽  
Kathleen O. Davis ◽  
Renu Bajaj ◽  
...  

Context Next-generation sequencing allows for high-throughput processing and sensitive variant detection in multiple genes from small samples. For many diseases, including cancer, a comprehensive mutational profile of a targeted list of genes can be used to simultaneously inform patient care, establish eligibility for ongoing clinical trials, and further research. Objective To validate a pan-cancer, next-generation–sequencing assay for use in the clinical laboratory. Design DNA was extracted from 68 clinical specimens (formalin-fixed, paraffin-embedded; fine-needle aspirates; peripheral blood; or bone marrow) and 5 normal controls. Sixty-four DNA samples (94%; 64 of 68) were successfully processed with the TruSeq Amplicon Cancer Panel (Illumina Inc, San Diego, California) and sequenced in 4 sequencing runs. The data were analyzed at 4 different filter settings for sequencing coverage and variant frequency cutoff. Results Libraries created from 40 specimens could be successfully sequenced in a single run and still yield sufficient coverage for robust data analysis of individual samples. Sensitivity for mutation detection down to 5% was demonstrated using dilutions of clinical specimens and control samples. The test was highly repeatable and reproducible and showed 100% concordance with clinically validated Sanger sequencing results. Comparison to an alternate next-generation sequencing technology was performed by also processing 9 of the specimens with the AmpliSeq Cancer Hotspot Panel (version 2; Life Technologies, Grand Island, New York). Thirty of the 31 (97%) TruSeq-detected variants covered by the designs of both panels were confirmed. Conclusion A sensitive, high-throughput, pan-cancer mutation panel for sequencing of cancer hot-spot mutations in 42 genes was validated for routine use in clinical testing.


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