NOVOPlasty 是一个perl脚本，没有依赖任何其他软件，下载好以后直接可以使用。
下载链接
https://github.com/ndierckx/NOVOPlasty
其基本使用方法是
perl NOVOPlasty3.7.2.pl -c config.txt
config.txt文件是需要我们自己准备的，软件包里提供了这个文件，我们需要对应着改里面的内容，文件的内容如下：
Project:
-----------------------
Project name = Test
Type = mito
Genome Range = 12000-22000
K-mer = 39
Max memory =
Extended log = 0
Save assembled reads = no
Seed Input = /path/to/seed_file/Seed.fasta
Reference sequence = /path/to/reference_file/reference.fasta (optional)
Variance detection =
Chloroplast sequence = /path/to/chloroplast_file/chloroplast.fasta (only for "mito_plant" option)
Dataset 1:
-----------------------
Read Length = 151
Insert size = 300
Platform = illumina
Single/Paired = PE
Combined reads =
Forward reads = /path/to/reads/reads_1.fastq
Reverse reads = /path/to/reads/reads_2.fastq
Heteroplasmy:
-----------------------
MAF =
HP exclude list =
PCR-free =
Optional:
-----------------------
Insert size auto = yes
Insert Range = 1.9
Insert Range strict = 1.3
Use Quality Scores = no
Project:
-----------------------
Project name = Choose a name for your project, it will be used for the output files.
Type = (chloro/mito/mito_plant) "chloro" for chloroplast assembly, "mito" for mitochondrial assembly and
"mito_plant" for mitochondrial assembly in plants.
Genome Range = (minimum genome size-maximum genome size) The expected genome size range of the genome.
Default value for mito: 12000-20000 / Default value for chloro: 120000-200000
If the expected size is know, you can lower the range, this can be useful when there is a repetitive
region, what could lead to a premature circularization of the genome.
K-mer = (integer) This is the length of the overlap between matching reads (Default: 33).
If reads are shorter then 90 bp or you have low coverage data, this value should be decreased down to
23.
For reads longer then 101 bp, this value can be increased, but this is not necessary.
Max memory = You can choose a max memory usage, suitable to automatically subsample the data or when you have
limited
memory capacity. If you have sufficient memory, leave it blank, else write your available memory in GB
(if you have for example a 8 GB RAM laptop, put down 7 or 7.5 (don't add the unit in the config file))
Extended log = Prints out a very extensive log, could be useful to send me when there is a problem (0/1).
Save assembled reads = All the reads used for the assembly will be stored in seperate files; if option 2 is used, the
original ids will be retained (yes/no/2)
Seed Input = The path to the file that contains the seed sequence.
Reference (optional) = If a reference is available, you can give here the path to the fasta file.
The assembly will still be de novo, but references of the same genus can be used as a guide to resolve
duplicated regions in the plant mitochondria or the inverted repeat in the chloroplast.
References from different genus haven't beeen tested yet.
Variance detection = If you select yes, you should also have a reference sequence (previous line). It will create a vcf
file with all the variances compared to the give reference (yes/no)
Chloroplast sequence = The path to the file that contains the chloroplast sequence (Only for mito_plant mode).
You have to assemble the chloroplast before you assemble the mitochondria of plants!
Dataset 1:
-----------------------
Read Length = The read length of your reads.
Insert size = Total insert size of your paired end reads, it doesn't have to be accurate but should be close enough.
Platform = illumina/ion - The performance on Ion Torrent data is significantly lower
Single/Paired = PE/SE
Combined reads = The path to the file that contains the combined reads (forward and reverse in 1 file)
Forward reads = The path to the file that contains the forward reads (not necessary when there is a merged file)
Reverse reads = The path to the file that contains the reverse reads (not necessary when there is a merged file)
Heteroplasmy:
-----------------------
MAF = (0.007-0.49) Minor Allele Frequency: If you want to detect heteroplasmy, first assemble the genome
without this option. Then give the resulting sequence as a reference and as a seed input. And give the
minimum minor allele frequency for this option (0.01 will detect heteroplasmy of >1%)
HP exclude list = Option not yet available
PCR-free = (yes/no) If you have a PCR-free library write yes
Optional:
-----------------------
Insert size auto = (yes/no) This will finetune your insert size automatically (Default: yes)
Insert Range = This variation on the insert size, could lower it when the coverage is very high or raise it when the
coverage is too low (Default: 1.9).
Insert Range strict = Strict variation to resolve repetitive regions (Default: 1.3).
Use Quality Scores = It will take in account the quality scores, only use this when reads have low quality, like with the
300 bp reads of Illumina (yes/no)
我们自己需要修改的包括：
Project name:给自己的项目起一个名字，自己可以随便起
Type: 如果是组装叶绿体需要将这一项改为 chloro
Genome Range:叶绿体基因组序列长度通常为150kb左右，这一项可以改为130,000-170,000
K-mer：一般直接用默认的39即可
Max memory：Extended log：这两项不用管
Save assembled reads：这一项如果改为yes的话会将用于组装的数据以fasta的格式保留下来。
Seed Input：种子序列的路径，软件包里提供了一个Seed_RUBP_cp.fasta文件，直接使用这个文件就可以
Reference sequence：参考序列的路径，这个参考序列是可选的，如果没有参考序列，等号后面的内容需要删除
Variance detection：这个不用管，直接空着就可以
Chloroplast sequence：组装叶绿体的时候需要把等号后面的内容删掉
Read Length Insert size Platform：这些可以在测序报告中找到，需要改为自己的
Single/Paired:好像只支持双端测序数据
Combined reads：这个可以不用管
Forward reads：第一个fastq文件的路径
Reverse reads：第二个fastq文件的路径
剩下的都可以不用管了
这个config.txt文件准备好就可以直接运行
perl NOVOPlasty3.7.2.pl -c config.txt
软件运行很快，不一会就可以拿到自己的结果了！
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