scaffold：plum_0630.scafSeq.FG和gene注释结果(Prunus_mume_scaffold.gff)下操作：
- 统计scaffold.fa染色体基本信息，输出的内容与格式如下结果，输出成文本文件。
| Name | Total Length | Effective Length | N Length | GC Length | GC Rate (%) |
|---|---|---|---|---|---|
| scaffold.fa |
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计算scaffold.fa的N50 ，N90；（N50定义google）
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以250bp为窗口，无重叠的沿序列滑动，计算GC含量，用R或者SVG做出GC含量分布曲线
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根据序列scaffold.fa以及基因注释文件scaffold.glimmer.gff，提取scaffold.fa上的所有的基因的CDS序列，结果以fa格式输出；（gff文件的格式google一下就知道每列意义）
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将提取的CDS序列翻译成氨基酸序列，结果以fa格式输出。（三联体密码子对应的氨基酸自己建hash）计算scaffold.fa的N50 ；（N50定义google）
First, open Terminal.app or iTerm2.app and change to the src/ directory:
cd src/
All the following commands are run in this directory.
All the length values will be shown on screen.
$ ./length.pl
Total Length: 60233856
Effective Length: 57637416
N Length: 2596440
GC Length: 21508836
GC Rate: 0.357088810651604
N50 and N90 will be shown on screen.
$ ./N50.pl
N50: 1580070
N90: 1085026
The GC counts in a 250bp sliding window are saved in ../GC-count.txt.
$ ./window.pl
Then change the value of count_path in plot-gc-count.R appropriately.
Open plot-gc-count.R in R.app.
R.app will produce the GC count histogram plot.
The coding sequence will be saved in ../Prunus_mume_scaffold.fasta.
$ ./coding-sequence.pl
The protein sequences translated from CDS will be save in ../Prunus_mume_scaffold_protein.fasta.
$ ./translate.pl