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How to carry out targeted sequencing of CNV analysis brief introduction, many novices are not very clear about this, in order to help you solve this problem, the following editor will explain for you in detail, people with this need can come to learn, I hope you can gain something.

Compared with the whole genome, the whole exon group only sequenced the exon region, which is more cost-effective. The whole exon uses a specific chip to capture exon regions for sequencing, which is further extended on the basis of this idea. If we only focus on some genes related to disease or specific phenotype, we only need to sequence these regions.

By means of PCR or chip capture, the reads of the target region of interest is enriched and then sequenced, which is target sequencing, also known as target resequencing, taget-NGS,tg-NGS, etc. Among them, for a specific disease or phenotype, the relevant candidate genes are grouped together, and only these genes are sequenced, which is commonly known as panel sequencing.

Objective Regional targeting sequencing is more economical and efficient, which can achieve 500 to 1000X or even higher sequencing depth, which is helpful to find rare variations and mine disease-related genes, which is widely used in clinical research. At present, there are relatively few related tools for mining CNV through targeted sequencing.

The listed CNV tools for tg-NGS sequencing are as follows

WES is also a kind of targeted sequencing, so the tools for WES are also evaluated, and the final list of tools for evaluation is as follows

ExomeCNV

ExomeCopy

CONTRA

ExomeDepth

CONIFER

CANOES

CODEX

CLAMMS

CoNVaDING

DECoN

CNVkit

SeqCNV

All the tools are based on the distribution of read depth to predict CNV. Using the simulation data of the average sequencing depth of 300X, the test results are as follows.

An and B represent sensitivity and specificity respectively. Different colors represent the number of control samples. It can be seen that DECoN, exomeDepth and exomeCNV are among the best.

The false negative rate of different software is evaluated, and the results are shown in the following figure.

It can be seen that the false negative rate of DECoN is the lowest in all cases. Considering that each software has its own limitations, synthesize the results of a variety of software for analysis, the number of the best software combinations are summarized as follows

The biggest challenge of the second generation sequencing CNV detection is the uneven distribution of sequencing depth caused by various system errors, GC content, repetition sequence, capture efficiency, PCR bias and so on. The first is to model and correct the system error by considering various factors, and the second is to reduce the influence of system error by comparing the experimental samples with the control samples.

For targeted sequencing, there are too many factors affecting the sequencing depth distribution, so it is difficult to have an optimal model to correct the system error, so comparing samples is a more mainstream algorithm.

Overall, the effect of DECoN software in this evaluation is the best, sensitivity and specificity are the best, followed by ExomeDepth and ExomeCNV. For CNV identification of panel sequencing, these three softwares are recommended.

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