GitHub - LeiYang-Fish/copyseparator: Assembling Long Gene Copies from Short Read Data (original) (raw)

Notes on the version

This is the latest version - v.1.2.0. Links to older versions can be found below:

https://github.com/LeiYang-Fish/copyseparator-v1.1.0-old-version

https://github.com/LeiYang-Fish/copyseparator-v1.0.0-old-version

How to install copyseparator?

install.packages("copyseparator")

How copyseparator works?

Please check the text and figures in the folder "Copyseparator introduction".

What is the input file format for sep_assem and copy_separate?

The input file is a fasta file contains thousands of short reads that have been mapped to a reference. Reads that are not directly mapped to the reference and the reference itself need to be removed after mapping.

copy_separate can only handle one file each run, sep_assem, however, will process all the fasta files in the working directory. Do not put any unrelated fasta files in the working directory.

Example on how to run copyseparator

https://github.com/LeiYang-Fish/copyseparator_more_examples

Due to the size limitation (25M) imposed by GitHub, only one example is provided in the above folder.

What can copyseparator do?

Separate and assemble two or more gene copies from short-read Next-Generation Sequencing data for polyploids, gene families, mixed/contaminated samples etc.

How many gene copies can copyseparator separate?

Two or more. However, it works better when there is fewer (e.g. two) gene copies. That is because copyseparator uses clustering analyses to separate reads from different gene copies. The more the gene copies, the harder it is to separate them apart.

Can copyseparator separate the two alleles of a gene copy?

Usually cannot. Those alleles are usually very similar to each other. There may be long runs (>300bp) of invariable sites.

What is the length of gene copies that copyseparator can separate?

Theoretically, if the coverage is high and relatively even, there is no limitation on the length. In reality, however, copyseparator is usually used to separate gene copies that are several hundred to several thousand base pairs long. I have used it to successfully separate mitogenomes (~16,000 bp) of two shark species, whose reads (from gene capture, paired-end, read length 300bp) have been combined intentionally. Long-read sequencing is the better way to go for separating very long gene copies.

How to generate the input data for copyseparator?

1. PCR amplicons --- shear to desired size (e.g. ~ 500bp) if needed --- prepare libraries --- NGS short-read sequencing
2. Target gene capture --- NGS short-read sequencing
3. Some other ways ...

Why short reads need to be mapped to a reference before runing copyseparator?

Mapping to a reference can organize the short reads in order. In this way, the subsets, the picked clusters and their respective consensus sequences, and the assembled gene copy sequences can all be in the correct order.

Why the read-length has to be 250bp or longer?

During assembling, short reads can easily result in chimeric sequences. Email me at leiyangslu@gmail.com if you really want to use copyseparator for NGS data with a read length < 250bp.

How to assemble gene copies if "sep_assem" or "copy_assemble" fails?

I use SeaView (http://doua.prabi.fr/software/seaview) to examine the results from "copy_separate". I prefer to assemble gene copies by moving sequences around and link gene copies by eye. It just like assembling the forward and reverse sequences from Sanger sequencing. Even if you prefer to use "copy_assemble", you still need to check the alignment first. Pay special attention to the nucleotide overhangs introduced by mistake during the calculation of consensus sequences of picked clusters.

How to cite copyseparator?

Run the following to get the appropriate citation for the version you’re using:

citation(package = "copyseparator")

To cite package ‘copyseparator’ in publications use:

Yang L (2022). copyseparator: Assembling Long Gene Copies from Short Read Data. R package version 1.2.0, https://CRAN.R-project.org/package=copyseparator.

A BibTeX entry for LaTeX users is

@Manual{, title = {copyseparator: Assembling Long Gene Copies from Short Read Data}, author = {Lei Yang}, year = {2022}, note = {R package version 1.2.0}, url = {https://CRAN.R-project.org/package=copyseparator}, }

ATTENTION: This citation information has been auto-generated from the package DESCRIPTION file and may need manual editing, see ‘help("citation")’.