HA-MLCS

Introduction

We propose a novel High-precision Approximate Multiple Longest Common Subsequence algorithm HA-MLCS for COVID-19 big sequence data similarity analysis.

Install & Run

1. Install JDK-1.8;
2. Put the data files to be processed into the 'file' folder of this project;
3. Run the following command in a shell command window.

java -jar -Dmlcs.max-thread=2 -Djava.util.Arrays.useLegacyMergeSort=true -Dmlcs.rt=1 HA-MLCS.jar [fileName]

• [fileName]: program parameter, files should be put in 'file' Folder to be read;
• [-Dmlcs.max-thread]: VM parameter, the number of threads you need to start;
• [-Djava.util.Arrays.useLegacyMergeSort]: VM parameter, should be set true;
• [-Dmlcs.rt]: VM parameter, is a user-customized parameter ($1 \leqslant rt \in \mathbb{Z}$), which represents how many number of key points to be retained in each layer when constructing MLCS-ODAG.