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Single-cell sequencing examines the nucleic acid sequence information from individual cells with optimized next-generation sequencing technologies, providing a higher resolution of cellular differences and a better understanding of the function of an individual cell in the context of its microenvironment. [1]
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Logarithmic coverage plot for the single-cell sequencing data for E. coli genome. [14] SPAdes was designed to overcome the problems associated with the assembly of single cell data as follows: [2] 1. Non-uniform coverage. SPAdes utilizes multisized de Bruijn graph which allows employing different values of k.
This single cell shows the process of the central dogma of molecular biology, which are all steps researchers are interested to quantify (DNA, RNA, and Protein).. In cell biology, single-cell analysis and subcellular analysis [1] refer to the study of genomics, transcriptomics, proteomics, metabolomics, and cell–cell interactions at the level of an individual cell, as opposed to more ...
A list of more than 100 different single cell sequencing (omics) methods have been published. [1] The large majority of methods are paired with short-read sequencing technologies, although some of them are compatible with long read sequencing.
Two methods for single-cell ATAC-seq [8]. ATAC-seq stands for Assay for Transposase-Accessible Chromatin with high throughput sequencing. [9] It is a technique used in molecular biology to identify accessible DNA regions, equivalent to DNase I hypersensitive sites. [9]
Next-generation sequencing technology is performed resulting in about 100 bp single-end reads. Raw sequence data are filtered and aligned to a reference genome using usually Burrows–Wheeler alignment tool (BWA) or Bowtie 2. The next step is to identify SNPs from aligned tags and score all discovered SNPs for various coverage, depth and ...
As a result of the aforementioned properties of single-cell transcriptomic data, batch correction methods developed for bulk sequencing data were observed to perform poorly. Consequently, researchers developed statistical methods to correct for batch effects that are robust to the properties of single-cell transcriptomic data to integrate data ...