ReAlign-N: an integrated realignment approach for multiple nucleic acid sequence alignment, combining global and local realignments

ReAlign-N is a tool written in C++11 for realigning the multiple nucleic acid sequence alignment. It runs on Linux.

🔨Installation and Usage

1.1 Linux/WSL(Windows Subsystem for Linux ) - from Anaconda

1.Install WSL for Windows. Instructional video 1 or 2 (Copyright belongs to the original work).

2.Download and install Anaconda. Download Anaconda for different systems here. Instructional video of anaconda installation 1 or 2 (Copyright belongs to the original work).

3.Install ReAlign-N.

#1 Create and activate a conda environment for ReAlign-N
conda create -n realign_n_env
conda activate realign_n_env

#2 Add channels to conda
conda config --add channels malab

#3 Install ReAlign-N
conda install -c malab realign_n

#4 Test ReAlign-N
realign_n -h

1.2 Linux/WSL(Windows Subsystem for Linux ) - from the source code

1. Download and Compile the source code. (Make sure your version of gcc >= 9.4.0)

#1 Download
git clone https://github.com/malabz/ReAlign-N.git

#2 Open the folder
cd ReAlign-N

#3 Compile
make

#4 Test ReAlign-N
./realign_n -h

2 Usage

Usage: /.realign_n [-r] path [-a] path [-o] path [-m] mode

  Necessary arguments:
    -r  Specify the path of raw data, a file in FASTA format.
    -a  Specify the path of initial alignment, a file in FASTA format.

  Optional arguments:
    -o  Specify the output for ReAlign-N, a file in FASTA format.
    -m  Specify the mode of ReAlign-N (default mode: 1).
        1 for local realignment followed by global realignment.
        2 for global realignment followed by local realignment.
    -h  Print the help message.

🔬Test dataset and the use case

1. Information about the test dataset

Dataset	Sequences Num	Repeats Num	Avg Length	Similarity
16s simu	100	9	about 1550bp	14 sets of data with different similarities (99%, 98%, 97%, 96%, 95%, 94%, 93%, 92%, 91%, 90%, 85%, 80%, 75%, 70%)
mt simu	100	9	about 16000bp	14 sets of data with different similarities (99%, 98%, 97%, 96%, 95%, 94%, 93%, 92%, 91%, 90%, 85%, 80%, 75%, 70%)
sars2 simu	100	9	about 29000bp	14 sets of data with different similarities (99%, 98%, 97%, 96%, 95%, 94%, 93%, 92%, 91%, 90%, 85%, 80%, 75%, 70%)
CIPRES-128	255	9	about 1550bp	The average similarity is about 80%
CIPRES-256	511	9	about 1550bp	The average similarity is about 80%
CIPRES-512	1023	9	about 1550bp	The average similarity is about 80%
CIPRES-1024	2047	9	about 1550bp	The average similarity is about 80%

2. The use case

# Download data
wget http://lab.malab.cn/soft/ReAlign-N/data/16s_like.tar.gz

# Unzip data
tar -zxvf 16s_like.tar.gz

# Get the folder path
cd 16s_like

# Run ReAlign-N
./realign_n -r raw_data/16s_similarity_70_1.fas -a msa_results/16s_similarity_70_1_clustalo.fas -o 16s_similarity_70_1_clustalo_realign_n.fas -m 1

📍Reminder

1. Currently ReAlign-N is ONLY available for DNA/RNA.
2. Ensure that the sequence ID entered into ReAlign is unique.
3. MAFFT installation is required for the utilization of ReAlign-N.

🖥️Environment

System	GCC version
Linux	GCC 9.4.0
WSL	GCC 9.4.0

🔖Citation

👋Contacts

The software tools are developed and maintained by 🧑‍🏫ZOU's lab.

If you find any bug, welcome to contact us on the issues page or email us at 👉📩.

More tools and infomation can visit our github.