Sentence examples for cell sequencing methods from inspiring English sources

An alternative approach is to use single cell sequencing methods [ 11- 14], which have the capability of fully resolving admixtures of genetically distinct clones.

Furthermore, the relevance of single cell sequencing methods in the diagnostic arena is still unclear since sequencing data derived from single cells do not provide any direct information on the remaining tumor cell population.

These questions are better addressed using single-cell sequencing methods, because they can provide a fuller picture of the extent of genomic heterogeneity in the primary tumor.

Until single-cell sequencing methods mature or disruptive technologies for bulk sequencing with very long reads emerge, inferences as performed here will be necessary.

Single-cell sequencing methods such as SNS provide an unprecedented view of the genomic diversity within tumors and provide the means to detect and analyze the genomes of rare cancer cells.

While single-cell sequencing methods using WGA are currently limited to low coverage of the human genome (approximately 6%), emerging third-generation sequencing technologies such as that developed by Pacific Biosystems (Lacey, WA, USA) [ 93] may greatly improve coverage through single-molecule sequencing, by requiring lower amounts of input DNA.

To perform our analyses, we first devised and validated a high-throughput whole-genome single-cell sequencing method using two lymphoblastoid cell line single cells.

Further, we established a single-cell sequencing method that opens the way for detailed analyses of a variety of tumor types, including those with high genetic complex between patients.

Recently, Hou et al (2012) developed a high-throughput single-cell sequencing method for sequencing the cancer genome with high accuracy at the nucleotide level to facilitate the analysis of tumour evolution in cancers.

Recently, single cell epigenomic sequencing studies are on the rise with the application of new single cell epigenomic sequencing methods.

In this review, we present an overview of the state-of-the-art single-cell DNA sequencing methods, technical errors that are inherent in the resulting large-scale datasets, and computational methods to overcome these errors.