scholarly journals Reconstructing and counting genomic fragments through tagmentation-based haploid phasing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Patrick P. T. Leong ◽  
Aleksandar Mihajlović ◽  
Nadežda Bogdanović ◽  
Luka Breberina ◽  
Larry Xi

AbstractSingle-cell sequencing provides a new level of granularity in studying the heterogeneous nature of cancer cells. For some cancers, this heterogeneity is the result of copy number changes of genes within the cellular genomes. The ability to accurately determine such copy number changes is critical in tracing and understanding tumorigenesis. Current single-cell genome sequencing methodologies infer copy numbers based on statistical approaches followed by rounding decimal numbers to integer values. Such methodologies are sample dependent, have varying calling sensitivities which heavily depend on the sample’s ploidy and are sensitive to noise in sequencing data. In this paper we have demonstrated the concept of integer-counting by using a novel bioinformatic algorithm built on our library construction chemistry in order to detect the discrete nature of the genome.

2020 ◽  
Vol 27 (4) ◽  
pp. 565-598 ◽  
Author(s):  
Haoyun Lei ◽  
Bochuan Lyu ◽  
E. Michael Gertz ◽  
Alejandro A. Schäffer ◽  
Xulian Shi ◽  
...  

Cell Reports ◽  
2014 ◽  
Vol 8 (5) ◽  
pp. 1280-1289 ◽  
Author(s):  
Xuyu Cai ◽  
Gilad D. Evrony ◽  
Hillel S. Lehmann ◽  
Princess C. Elhosary ◽  
Bhaven K. Mehta ◽  
...  

2019 ◽  
Author(s):  
Zhenhua Yu ◽  
Fang Du ◽  
Xuehong Sun ◽  
Ao Li

Abstract Motivation Allele dropout (ADO) and unbalanced amplification of alleles are main technical issues of single-cell sequencing (SCS), and effectively emulating these issues is necessary for reliably benchmarking SCS-based bioinformatics tools. Unfortunately, currently available sequencing simulators are free of whole-genome amplification involved in SCS technique and therefore not suited for generating SCS datasets. We develop a new software package (SCSsim) that can efficiently simulate SCS datasets in a parallel fashion with minimal user intervention. SCSsim first constructs the genome sequence of single cell by mimicking a complement of genomic variations under user-controlled manner, and then amplifies the genome according to MALBAC technique and finally yields sequencing reads from the amplified products based on inferred sequencing profiles. Comprehensive evaluation in simulating different ADO rates, variation detection efficiency and genome coverage demonstrates that SCSsim is a very useful tool in mimicking single-cell sequencing data with high efficiency. Availability and implementation SCSsim is freely available at https://github.com/qasimyu/scssim. Supplementary information Supplementary data are available at Bioinformatics online.


Cell Reports ◽  
2015 ◽  
Vol 10 (4) ◽  
pp. 645 ◽  
Author(s):  
Xuyu Cai ◽  
Gilad D. Evrony ◽  
Hillel S. Lehmann ◽  
Princess C. Elhosary ◽  
Bhaven K. Mehta ◽  
...  

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