HBV分析
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https://www.frontiersin.org/articles/10.3389/fmicb.2020.616023/full
Comprehensive Analysis of Clinically Significant Hepatitis B Virus Mutations in Relation to Genotype, Subgenotype and Geographic Region
临床样本的突变分析
immune escape,
antiviral resistance
hepatocellular carcinoma (HCC)该文章提到了一些突变的临床意义
https://www.sciencedirect.com/science/article/abs/pii/S001650850901556X -
分型方法研究：
https://www.sciencedirect.com/science/article/pii/S1201971210024239https://onlinelibrary.wiley.com/doi/abs/10.1002/rmv.400
Hepatitis B virus genotypes: comparison of genotyping methods
https://journals.asm.org/doi/pdf/10.1128/cmr.00009-07
Molecular Testing in the Diagnosis and Management of
Chronic Hepatitis Bhttps://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-020-05269-z
Distribution of hepatitis B virus genotypes in the general population of Myanmar via nationwide studyhttps://www.ncbi.nlm.nih.gov/labs/pmc/articles/PMC4431363/
Sequence-based genotyping of hepatitis B virus in general population -
Illumina and Nanopore methods for whole genome sequencing of hepatitis B virus (HBV)
https://www.nature.com/articles/s41598-019-43524-9#Sec11 -
https://bmcinfectdis.biomedcentral.com/track/pdf/10.1186/s12879-017-2697-x.pdf
Molecular characterization of hepatitis B
virus in Vietnam
The Illumina fastq sequence files were assembled
using Genious 8.0.5, software package (Biomatters
Ltd, AK, New Zeland) utilizing a reference-based
mapping tool after primer sequence clipping (i.e. the
consensus sequence was obtained by mapping individual reads of each sample to a reference sequence).
Finally, screening of minor (sub-consensus) variants
was performed using the SNP detection tool available
in Geneious. A minimum variant frequency of 5% and
500-fold coverage were chosen as cut-off values. -
https://sci-hub.st/10.1007/978-1-4939-6700-1_17
Deep Sequencing of the Hepatitis B Virus Genome: Analysis
of Multiple Samples by Implementation of the Illumina
Platform
A BLASTN comparison analysis is performed between clean
reads and the HBV genomic reference sequence, to eliminate
non-HBV sequences (anything with similarity<70%). After
this filtering step, the average coverage of HBV sequence site
should be above 2600× (Fig. 1).
6. Shan entropy and Relative entropy calculations are carried out. -
Identification and Comparative Analysis of Hepatitis B Virus Genotype D/E Recombinants in Africa
https://stacks.cdc.gov/view/cdc/50437 -
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The Study of Hepatitis B Virus Using Bioinformatics
https://www.intechopen.com/chapters/50624 -
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https://www.niid.go.jp/niid/images/JJID/58/244.pdf
Analysis of genomic-length HBV sequences to determine genotype and subgenotype reference sequences -
https://www.sciencedirect.com/science/article/pii/S1567134821004846#bb0040
Analysis of entire hepatitis B virus genomes reveals reversion of mutations to wild type in natural infection, a 15 year follow-up study2.6. NGS data preprocessing and sample genotyping
Quality control and preprocessing of each sample's raw NGS short reads was performed by fastp v0.20.1 (Chen et al., 2018). The adapter sequences were removed and 15 bases of each read were trimmed from the 5’end. Any reads with an average quality score lower than 30, or length shorter than 50 nt, were filtered further. The remaining high quality reads from each sample were then mapped to a common reference sequence (accession no. X02763) using bowtie2 v2.3.4.1 (Langmead and Salzberg, 2012). After sorting and removing the duplications using Samtools v1.7 (Li et al., 2009), the consensus sequence was generated using CliqueSNV v1.5.3 (Knyazev et al., 2021). Consensus sequences of all samples were then multi-aligned with the reference sequences from HBVdb (Hayer et al., 2013) and three additional sequences, including FJ023664 of genotype I, AB486012 of genotype J, and AM117397 from Africa chimpanzees as the outgroup. A maximum-likelihood tree was then constructed using MEGA 7 (Kumar et al., 2016) and each sample was genotyped accordingly.这个文章里面做consensus序列的时候 用的是 cliqueSNV 该软件和samtools consensus 的对比需要研究下：
2.7. Haplotype construction and diversity analysis
分型完毕后 每个样本对应的参考序列就可以更具体 然后进行突变分析
bowtie2's very-sensitive-local 比对
Sambamba 去重
CliqueSNV haplotype reconstruction
haplotypes with a minimum abundance of 1% -
二代数据分析过程
对比分型
使用比对 直接将reads比对到参考基因组上 然后进行统计blast分型
使用blast直接和hdvdb进行对比查询（ncbi自己的分型工具对查询序列进行了分段 类似kmer 我们一般拿到的reads双端文件 感觉和这种分段很类似 可以直接查询 也不用组装了）ncbi宣称好处是可以找出“重组”过的病毒类型 即一个病毒由多个病毒拼接而成 这种情况很难和混合样本（一个样本有多个分型的感染）区分开
直接使用reads 来分型 可以参考这个文章
https://www.ncbi.nlm.nih.gov/labs/pmc/articles/PMC4382110/
进化树方式进行分型：
1.fastp ：质控和预处理
2.去接头（可选）
3.过滤：碱基质量
4.比对：bowtie2、bwa-mem 和通用株X02763
5.排序、去重：Samtools
6.生成一致性序列：CliqueSNV
7.多序列比对：和hdvdb数据库进行多序列比对（blast方法不需要这个步骤 由于病毒的变化很多 很可能在多序列比对时无法有效对齐）
8.构建进化树：MEGA 7 maximum-likelihood方法 该步骤就可以得到每个样本的分型构建单倍型 Haplotype construction
1.比对：和该样本的对应分型参考序列进行比对
bowtie2's very-sensitive-local
2.去重：Sambamba
3.构建单倍型：CliqueSNVdiversity analysis
香农商Shannon entropy (Sn)：
S = −pilnpi, where pi is the frequency of each haplotype in the viral quasispecies population
genetic diversity (D) ：MEGA X v10.1.8 genetic distance of the haplotypes
病毒进化率 viral evolutionary rates：MEGA 7 HKY substitution model 、BEAST v2.6.3、Tracer统计分析
SPSS突变分析
Samtools mpileup： -
https://www.rivm.nl/mpf/typingtool/hev/introduction
一个在线的hev的分型工具 有参考报告 -
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https://pubmed.ncbi.nlm.nih.gov/11230757/
Nomenclature for antiviral-resistant human hepatitis B virus mutations in the polymerase region
HBV耐药性突变的命名规则 rtL180M -
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https://jbiomedsci.biomedcentral.com/articles/10.1186/s12929-018-0442-4
Applications of next-generation sequencing analysis for the detection of hepatocellular carcinoma-associated hepatitis B virus mutations
这篇文章分析了HBV突变和肝癌的相关性
1.对于组装 文章提到有参组装更好 相对de novo 组装而言 毕竟illumina的reads比较短2.文章里面提到了一个sample-specific 参考序列、同基因型的参考序列、其他不兼容参考序列对假阳性的影响。
这个文章很水 没有提到生信是怎么做的 -
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