update README

README.md

@@ -1,75 +1,84 @@
 # Description
 
-This study utilized GitLab CI/CD and GitHub Actions to automate the construction of the Hidden Markov Model ( HMM ) and conduct a search for Homeotic genes. It further screened out gene IDs that satisfy the user-defined threshold and extracted protein sequences from the obtained results files.
+使用 GitHub 的 action 功能来进行自动化的 hmmer，主要功能有 hmmersearch、基因筛选、蛋白质序列提取及自定义的 hmmer 命令。
 
 # Usage
 
-You need to define the following variables in `config.py`.
+你需要在 `config.py`中修改一些参数。
 
 | name | example | description |
 | -- | -- | -- |
 | PF_number | PF00031 | The Gene family number of the [pfam](http://pfam-legacy.xfam.org/) , such as PF00031 |
 | evaluation_threshold | 1e-5 | The threshold for filtering IDs from the results of hmmsearch |
 | species | Oryza_sativa | Species of gene family |
 
-The repository only contains the genome protein sequences of three species: Arabidopsis_thaliana , Oryza_sativa , Lolium_perenne, and Zea_mays .
+仓库文件夹中只有这几个物种的蛋白序列：Arabidopsis_thaliana , Oryza_sativa , Lolium_perenne, and Zea_mays。
 
 ## Local usage
 
-I suggest that you use Conda for installation.
+使用 conda 建立一个单独的环境来使用，本地使用时需要自己安装 hmmer 和对应的 python 库。
 
 ```bash
 conda create -n hmmer python=3.7
 conda activate hmmer
 conda install wget biopython hmmer
 ```
 
-After setting up the environment, modify the information in `config.py` and run `main.py`.
+环境搭建完成后修改 `config.py`然后运行`main.py`。
 
 ## Cloud usage
 
-You need to clone the warehouse locally first.
+`fork`此仓库，clone 到本地：
 
 ```bash
 git clone https://github.com/UncleCAT4/auto-hmmer.git
 ```
 
-Fork this warehouse to your own account, modify the information in `config.py`, and submit the changes to the repository. CI/CD will help you complete the remaining tasks.
+修改`config.py`中的参数后提交更改，action 会自动开始。
 
 ```bash
 git add .
 git commit -m "update"
 git push
 ```
 
-You can also make modifications directly on the webpage of the code repository, and the running results can be downloaded from the product.
+你也可以直接在 GitHub 网页版修改参数，但并不建议这样做。
 
 # Results
 
-If you are running locally, the results are clearly visible.If you are using it in the cloud,you can download the completed files from the GitHub Action or Gitlab CI/CD running artifacts.
-
-Usually contains the following three main artifacts:
+action 运行完成后你可以在产物中下载以下文件：
 
 > result.out ( Results of hmmsearch )
 
 > id_list.txt ( Filtered ID List )
 
 > protein_for_target_id.fasta ( Protein sequence extracted from ID list )
 
-# Customize the hmmer command
+# 自定义 hmmer 命令
 
-You only need to define the format of the new command in `main.py`, such as the following command:
+你只需要在`main.py`中定义一个新的 hmmer 命令，例如：
 
 ```python
 hmmbuild_command = 'hmmbuild model.hmm PFseed.txt'
 ```
 
-Then run the command by calling the function in `main.py`.
+随后在`main.py`中调用命令：
 
 ```python
 run_command(hmmbuild_command)
 ```
 
 # Problem
 
-Different transcripts of the same gene were not removed.
+- 没有去除基因的不同转录本。
+
+# More
+
+如果你想使用额外物种的蛋白序列，将序列放在`protein_seq`文件夹下，修改`config.py`中的物种名称即可，请注意，序列的文件拓展名应该是`fasta`，如果是其他拓展名，你可以在`main.py`中修改。
+
+```python
+target_species_proteins = "./protein_seq/{}.fasta".format(config.species)
+target_gene_proteins = 'protein_for_target_id.fasta'
+```
+
+由于 GitHub 的仓库大小限制为 1GB，所以建议`clone`到本地后先清除其它物种的蛋白序列。