scholarly journals Correcting for cancer genome size and tumour cell content enables better estimation of copy number alterations from next-generation sequence data

2011 ◽  
Vol 28 (1) ◽  
pp. 40-47 ◽  
Author(s):  
Arief Gusnanto ◽  
Henry M. Wood ◽  
Yudi Pawitan ◽  
Pamela Rabbitts ◽  
Stefano Berri
Keyword(s):  
Genome Size ◽  
Tumour Cell ◽  
Copy Number ◽  
Sequence Data ◽  
Cancer Genome ◽  
Copy Number Alterations ◽  
Next Generation ◽  
Cell Content

scholarly journals Next-Generation Sequencing–Based Assessment of JAK2, PD-L1, and PD-L2 Copy Number Alterations at 9p24.1 in Breast Cancer

2019 ◽  
Vol 21 (2) ◽  
pp. 307-317 ◽  
Author(s):  
Sounak Gupta ◽  
Chad M. Vanderbilt ◽  
Paolo Cotzia ◽  
Javier A. Arias-Stella ◽  
Jason C. Chang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Next Generation Sequencing ◽  
Copy Number ◽  
Copy Number Alterations ◽  
Next Generation ◽  
Generation Sequencing

scholarly journals Stratifying tumour subtypes based on copy number alteration profiles using next-generation sequence data

2015 ◽  
Vol 31 (16) ◽  
pp. 2713-2720 ◽  
Author(s):  
Arief Gusnanto ◽  
Peter Tcherveniakov ◽  
Farag Shuweihdi ◽  
Manar Samman ◽  
Pamela Rabbitts ◽  
...  
Keyword(s):  
Copy Number ◽  
Copy Number Alteration ◽  
Sequence Data ◽  
Next Generation

scholarly journals Assessing Copy Number Alterations in Targeted, Amplicon-Based Next-Generation Sequencing Data

2015 ◽  
Vol 17 (1) ◽  
pp. 53-63 ◽  
Author(s):  
Catherine Grasso ◽  
Timothy Butler ◽  
Katherine Rhodes ◽  
Michael Quist ◽  
Tanaya L. Neff ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Copy Number ◽  
Next Generation Sequencing Data ◽  
Copy Number Alterations ◽  
Next Generation ◽  
Sequencing Data ◽  
Generation Sequencing

scholarly journals Measuring genome sizes using read-depth, k-mers, and flow cytometry: methodological comparisons in beetles (Coleoptera)

2019 ◽  
Author(s):  
James M. Pflug ◽  
Valerie Renee Holmes ◽  
Crystal Burrus ◽  
J. Spencer Johnston ◽  
David R. Maddison
Keyword(s):  
Flow Cytometry ◽  
Genome Size ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Repetitive Sequences ◽  
Single Copy ◽  
Read Depth ◽  
Test System ◽  
Estimation Methods ◽  
Next Generation

ABSTRACTMeasuring genome size across different species can yield important insights into evolution of the genome and allow for more informed decisions when designing next-generation genomic sequencing projects. New techniques for estimating genome size using shallow genomic sequence data have emerged which have the potential to augment our knowledge of genome sizes, yet these methods have only been used in a limited number of empirical studies. In this project, we compare estimation methods using next-generation sequencing (k-mer methods and average read depth of single-copy genes) to measurements from flow cytometry, the gold standard for genome size measures, using ground beetles (Carabidae) and other members of the beetle suborder Adephaga as our test system. We also present a new protocol for using read-depth of single-copy genes to estimate genome size. Additionally, we report flow cytometry measurements for five previously unmeasured carabid species, as well as 21 new draft genomes and six new draft transcriptomes across eight species of adephagan beetles. No single sequence-based method performed well on all species, and all tended to underestimate the genome sizes, although only slightly in most samples. For one species, Bembidion haplogonum, most sequence-based methods yielded estimates half the size suggested by flow cytometry. This discrepancy for k-mer methods can be explained by a large number of repetitive sequences, but we have no explanation for why read-depth methods yielded results that were also strikingly low.

scholarly journals Identification of copy number alterations in colon cancer from analysis of amplicon-based next generation sequencing data

Oncotarget ◽  
2018 ◽  
Vol 9 (29) ◽  
pp. 20409-20425 ◽  
Author(s):  
Duarte Mendes Oliveira ◽  
Gianluca Santamaria ◽  
Carmelo Laudanna ◽  
Simona Migliozzi ◽  
Pietro Zoppoli ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Next Generation Sequencing ◽  
Copy Number ◽  
Next Generation Sequencing Data ◽  
Copy Number Alterations ◽  
Next Generation ◽  
Sequencing Data ◽  
Generation Sequencing

scholarly journals Computational methods for detecting copy number variations in cancer genome using next generation sequencing: principles and challenges

Oncotarget ◽  
2013 ◽  
Vol 4 (11) ◽  
pp. 1868-1881 ◽  
Author(s):  
Biao Liu ◽  
Carl D. Morrison ◽  
Candace S. Johnson ◽  
Donald L. Trump ◽  
Maochun Qin ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Computational Methods ◽  
Copy Number ◽  
Copy Number Variations ◽  
Cancer Genome ◽  
Next Generation ◽  
Generation Sequencing
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