How to use miniasm galaxy? Miniasm Galaxy is a tool built from the ground to improve the de novo assembly of genomes with fast rates. Different from many other classical genome assemblers, in Miniasm, therefore, error-correction step is omitted to cut short the time for assembly. Because of this, it readily works with big data and is widely used for piecing together the data generated by platforms such as PacBio or Oxford Nanopore.
How to use miniasm galaxy, however, different from other genome assemblers since Miniasm does not perform error correction. This approach is less computationally intensive but rather presupposes pre-correction of the input data. Here, Miniasm avoids the error correction phase, which is best for those seeking speed in their genome assembly results.
Why Choose Miniasm Galaxy?
Miniasm Galaxy is a straightforward and efficient method for joining genomes while avoiding the massive computational load of other programs. Its major strengths include:
Speed: It is also very fast which makes it very suitable for deployment on big projects.
Simplicity: It should also be noted that the tool has been made command based and they are easy to remember.
Scalability: Miniasm has been designed to work with big genomic projects and it is capable of handling incredibly large datasets.
Due to removal of such steps as error correction this tool saves time in assembly of scaffolds but yields good results in the cases of using pre-corrected data.
Installation and Setup
System Requirements
Linux operating system, (the operating system for the application can be either Ubuntu or CentOS).
For datasets of at least several GB, work is recommended to be done on a local machine with at least 8 GB of RAM, although more is better for large projects.
In this sector, you need to have access to a firm and steady connection to the internet for downloading the required dependencies.
Installation Guide
To install Miniasm Galaxy, follow these steps:
Download Miniasm: Copy the repository from the GitHub using the command displayed below:
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git clone https://github.com/lh3/miniasm
Compile Miniasm: Go into the directory and build the program with:
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cd miniasm && make
Verify Installation: To verify if it was installed successfully, type:
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./miniasm
This should show the help menu to ensure that the tool is now operational to be used.
Basic Commands and Functionalities
After Miniasm is installed, now it is about to execute the tool for the first time. Miniasm operates on genome assembly by responding to commands in plain language. Here are some essential commands.
Output: Miniasm will create a GFA file format (Graphical Fragment Assembly) and can be converted to a readable form.
How to use miniasm galaxy
The assembly process of Miniasm is quite simple because it does not need more sophisticated steps than alignment and some additional activities. The input normally consists of corrected raw reads of long sequencing such as from pdb or nanopore SEasher and the alignment is done through programs such as minimap2.
Miniasm then directly creates a graph of the assembly sequence from the overlaps that result from it. The main output is GFA file that can be used for the subsequent more detailed data analysis.
Genome Assembly: Step-by-Step
Here’s a basic workflow for assembling a genome using Miniasm:
Prepare your data: Read and make sure they are error corrected by a tool to minimize cases such as Racon.
Align reads: Then use minimap2 to align for the generation of overlaps between the reads.
Run Miniasm: Now, he used Miniasm package to put together the genomes from the overlaps found.
Handling Large Datasets
Miniasm is expected to work on big data sets; However, performance scaling is crucial. When dealing with big data, consider the following:
RAM Usage: All parameters for Miniasm evaluation suggested that the program has a high demand in the memory, especially when working with large genomes. However, to optimize performance and guarantee effectiveness of your system, make sure it has the necessary input.
Parallelization: This can be solved in advanced by multi-threading in order to reduce processing time.
Troubleshooting Miniasm Galaxy
If you encounter errors, here are some common fixes:
Low Memory: Upgrade your system or get Miniasm to run on a supercomputer or beam computer.
Input Errors: Look that you are printing and editing your input files with no important mistakes and omissions.
Conclusion
How to use miniasm galaxy? Miniasm Galaxy provides a possibility of the fast, efficient, and scalable assembly of genome. Due to its simplicity coupled with its capabilities, the software is an important component for any molecular biology scientist. From simple microbial genomes to large and intricate ones, Miniasm is a tool that fits to crack the nut.
