Vipie: web pipeline for parallel characterization of viral populations from multiple NGS samples

Background

Next generation sequencing (NGS) technology allows laboratories to investigate virome composition in clinical and environmental samples in a culture-independent way. There is a need for bioinformatic tools capable of parallel processing of virome sequencing data by exactly identical methods: this is especially important in studies of multifactorial diseases, or in parallel comparison of laboratory protocols.

 

https://sourceforge.net/projects/vipie/

Utilities / Create consensus sequence from a BAM file

Utilities / Create consensus sequence from a BAM file

Description

Given an indexed BAM file and corresponding reference genome (in fasta format), this tool constructs a consensus sequence based on the alignment.

Parameters

None

Details

This tool uses SAMtools, bcftools and vcfutils.pl script to create a consensus sequence for the given alignment file. The actual command line executed is:

  samtools mpileup -uf reference.fa aligment.bam | bcftools view -cg - | vcfutils vcf2fq  

Note that the input BAM file must be sorted before it can be used by this tool.

Output

Output is a fasta f[……]

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fasta to nexus for beast

http://sequenceconversion.bugaco.com/converter/biology/sequences/fasta_to_nexus.php

 

 

端口绑定 将服务器IP 与本机接口连接

(base) zyshen@wyq-P310:~$ ssh -NfL localhost:8082:localhost:8082 zyshen@10.10.1.64

端口绑定  将服务器IP 与本机接口连接 就可以浏览服务器上的网页了

Good software

multiqc   ranger    ployly

https://github.com/MultiQC

https://github.com/ranger/ranger

https://zhuanlan.zhihu.com/p/34369349

安装ssr代理客户端 linux

安装electron-ssr

下载地址github.com/erguotou520/,选择dep格式。双击安装。

  1. 在启动器中启动electorn-ssr,选择自动下载ssr

  1. 编辑服务器

编辑服务器地址、混淆方式等。

ssr://MTI3LjAuMC4xOjgzODg6YXV0aF9jaGFpbl9hOmNoYWNoYTIwLWlldGY6cGxhaW46TUEvPw (二维码自动识别)

  1. 设置系统代理

以上手动和自动选择一个即可,(这一步不设置,貌似也没问题,进行下一步设置就好了)。

安装配置switchyomega

现在代理已经生效了,上面的链接可以点开了,安装好以后,在chrome右上角找到它,右键选项进入配置。

情景模式选proxy,代理服务器地址127.0.0.1端口1080,下面的统统同默认,记得一定要点应用选项!

6、操作完成

Correlation tests, correlation matrix, and corresponding visualization methods in R (forward)

https://rstudio-pubs-static.s3.amazonaws.com/240657_5157ff98e8204c358b2118fa69162e18.html

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R drawing png with high resolution

可重复的示例:

the_plot <- function()
{
  x <- seq(0, 1, length.out = 100)
  y <- pbeta(x, 1, 10)
  plot(
    x,
    y,
    xlab = "False Positive Rate",
    ylab = "Average true positive rate",
    type = "l"
  )
}

 

png(
  "test.png",
  width     = 3.25,
  height    = 3.25,
  units     = "in",
  res       = 1200,
  pointsize = 4
)
par(
  mar      = c(5, 5, 2, 2),
  xaxs     = "i",
  yaxs     = "i",
  cex.axis = 2,
  cex.lab  = 2
)
the_plot()
dev.off()

当然,更好的解决方案是放弃这种基本的图形和使用一个系统,将处理你的分辨率缩放。例如,

library(ggplot2)

ggplot_alternative <- function()
{[......]

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Correlation analysis (zhuantie)

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Data Binning and Plotting

In statistics, data binning is a way to categorize a number of continuous values into a smaller number of buckets (bins). Each bucket defines an numerical interval. For example, if there is a variable about house-based education levels which are measured by continuous values ranged between 0 and 19, data binning will place each value into one bucket if the value falls into the interval that the bucket covers. This post shows data binning in R as well as visualizing the bins.

The dataset contains 32038 observations for mean education level per house. Load the data into R.

data <- read.[......]

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