第一步下载NOVOPlasty
在https://anaconda.org/bioconda/novoplasty/files?sort=ndownloads&sort_order=desc上下载压缩包，我下载的版本是novoplasty-4.3.1-pl5321hdfd78af_1.tar.bz2,然后上传到服务器的/home/monkeyflower/biosoft/novoplasty文件夹中
cd /home/monkeyflower/biosoft/novoplasty
转到目标文件夹
tar jxvf novoplasty-4.3.1-pl5321hdfd78af_1.tar.bz2
#解压缩
export PATH=/home/monkeyflower/biosoft/novoplasty/bin/:$PATH
#将其添加到环境变量
第二步准备config.txt
config.txt文档可以从https://github.com/ndierckx/NOVOPlasty上下载，下载后将其放到文件夹/home/monkeyflower/biosoft/novoplasty，后需要自己改一些参数，如下注释的都是需要改的。
Project:
-----------------------
Project name = Test
#为自己的项目取一个名
Type = mito
#如果是叶绿体就用chloro
Genome Range = 120000-180000
#叶绿体基因组大小在120000-180000
K-mer = 39
Max memory =
Extended log = 0
Save assembled reads = yes
#保存结果文件的格式，yes就是fasta格式
Seed Input = /home/monkeyflower/biosoft/novoplasty/Seed.fasta
#在https://github.com/ndierckx/NOVOPlasty上下载
Reference sequence = /path/to/reference_file/reference.fasta (optional)
#如果参考序列没有，则等号后面内容需要删除
Variance detection =
Chloroplast sequence = /path/to/chloroplast_file/chloroplast.fasta (only for "mito_plant" option)
#组装叶绿体的时候需要把等号后面的内容删掉
Dataset 1:
-----------------------
Read Length = 151
Insert size = 300
Platform = illumina
Single/Paired = PE
Combined reads =
Forward reads =/home/monkeyflower/bioworkplace/qiuhaitang919/qiuhaitangCleanData/qiuhaitang/qiuhaitang_1.fq.gz
#第一个测序文件路径
Reverse reads =/home/monkeyflower/bioworkplace/qiuhaitang919/qiuhaitangCleanData/qiuhaitang/qiuhaitang_1.fq.gz
#第二个测序文件路径
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
Output path = /home/monkeyflower/bioworkplace/qiuhaitang919/qiuhaitangCleanData
#选择输出文件目录
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)
当完成第一次的修改之后，后续的contig.txt文件只需要修改read length ,Insert size,Forward reads,reserve reads，output path几项
第三步运行
cd /home/monkeyflower/biosoft/novoplasty
#转到工作目录
perl /home/monkeyflower/biosoft/novoplasty/bin/NOVOPlasty4.3.1.pl -c config.txt
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