シークエンシングの世代が変わるにつれてDNAシークエンサーの性能が急速に向上し、生成されるデータ量も増加した。この進化は、新しいバイオインフォマティクスの手法にもつながっており、モデルの精度やゲノム解析パイプラインの頑健性を検証する際に、in silicoデータが非常に重要になってきている。ここでは、現在利用可能な手法やプログラムよりも高速にリードをシミュレートする、次世代シーケンサーデータ用のマルチスレッド次世代シミュレーター（NGSNGS）を紹介する。NGSNGSは、ヌクレオチド品質スコアプロファイルに基づくプラットフォーム固有の特性を持つリードのシミュレーションが可能であり、古代DNAのシミュレーションに関連する死後損傷モデルも含んでいる。シミュレートされた配列は、ハプロイドゲノム、ポリプロイドアセンブリ、あるいは集団ハプロタイプを表すことができるリファレンスDNAゲノムから（置換を伴って）サンプリングされ、ユーザーは既知の可変部位を直接シミュレートすることができる。このプログラムはマルチスレッドフレームワークで実装されており、現在利用可能なツールよりも高速である。本手法と関連プログラムはオープンソースソフトウェアとして公開されており、コードとユーザーマニュアルはhttps://github.com/RAHenriksen/NGSNGSから利用できる。
インストール
htslibが必要。NGSNGSのmake時、HTSSRC環境変数にhtslibライブラリのパスを指定する。
git clone https://github.com/RAHenriksen/NGSNGS.git
cd NGSNGS/
git clone https://github.com/samtools/htslib.git
cd htslib/
git submodule update --init --recursive
make -j20
cd ../
make HTSSRC=./htslib -j20
> ./ngsngs
Next Generation Simulator for Next Generation Sequencing Data version v0.9.2.2: 37be551
Usage
./ngsngs [options] -i <input_reference.fa> -r/-c <Number of reads or depth of coverage> -l/-lf/-ld <fixed length, length file or length distribution> -seq <SE/PE> -f <output format> -o <output name prefix>
Example
./ngsngs -i Test_Examples/Mycobacterium_leprae.fa.gz -r 100000 -t 2 -s 1 -lf Test_Examples/Size_dist_sampling.txt -seq SE -m b,0.024,0.36,0.68,0.0097 -q1 Test_Examples/AccFreqL150R1.txt -f bam -o MycoBactBamSEOut
./ngsngs -i Test_Examples/Mycobacterium_leprae.fa.gz -c 3 -t 2 -s 1 -l 100 -seq PE -ne -a1 AGATCGGAAGAGCACACGTCTGAACTCCAGTCACCGATTCGATCTCGTATGCCGTCTTCTGCTTG -a2 AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGCCGTATCATTT -q1 Test_Examples/AccFreqL150R1.txt -q2 Test_Examples/AccFreqL150R2.txt -f fq -o MycoBactFqPEOut
./ngsngs -i Test_Examples/Mycobacterium_leprae.fa.gz -r 100000 -t 1 -s 1 -ld Pois,78 -seq SE -mf Test_Examples/MisincorpFile.txt -f fa -o MycoBactFaSEOut
./ngsngs -i Test_Examples/Mycobacterium_leprae.fa.gz -r 100000 -t 1 -s 1 -lf Test_Examples/Size_dist_sampling.txt -ll 50 -seq SE -qs 40 -f fq -o MycoBactFqQsLlSEOut
./ngsngs -i Test_Examples/hg19MSub.fa -r 1000 -t 1 -s 100 -l 150 -seq SE -ne -vcf Test_Examples/ChrMtSubDeletionDiploid.vcf -id 0 -q1 Test_Examples/AccFreqL150R1.txt -chr MT -DumpVCF DeltionInfo -f fq -o MtDeletionOut
-h | --help: Print help page.
-v | --version: Print NGSNGS version, git commit and htslib library.
----- Required -----
-i | --input: Reference file in fasta format (.fa,.fasta) to sample reads.
Sequence reads:
-r | --reads: Number of reads to simulate, conflicts with -c option.
-c | --coverage: Depth of Coverage to simulate, conflics with -r option.
Fragment Length:
-l | --length: Fixed length of simulated fragments, conflicts with -lf & -ld option.
-lf | --lengthfile: CDF of a length distribution, conflicts with -l & -ld option.
-ld | --lengthdist: Discrete or continuous probability distributions, given their Probability density function, conflicts with -l & -lf option.
<Uni,Min,Max> Uniform distribution from a closed interval given a minimum and maximum positive integer, e.g. Uni,40,180.
<Norm,Mean,Variance> Normal Distribution, given a mean and variance, e.g. Norm,80,30.
<LogNorm,Mean,Variance> Log-normal Distribution, given a mean and variance, e.g. LogNorm,4,1.
<Pois,Rate> Poisson distribution, given a rate, e.g. Pois,165.
<Exp,Rate> Exponential distribution, given a rate, e.g. Exp,0.025.
<Gam,Shape,Scale> Gamma distribution, given a shape and scale, e.g. Gam,20,2.
Output characteristics:
-seq | --sequencing: Simulate single-end or paired-end reads.
<SE> single-end
<PE> paired-end.
-f | --format: File format of the simulated output reads.
Nucletide sequence w. different compression levels.
<fa||fasta>
<fa.gz||fasta.gz>
Nucletide sequence with corresponding quality score w. different compression levels.
<fq||fastq>
<fq.gz||fastq.gz>
Sequence Alignment Map w. different compression levels.
<sam||bam||cram>
-o | --output: Prefix of output file name.
Format specific:
-q1 | --quality1: Read Quality profile for single-end reads (SE) or first read pair (PE) for fastq or sequence alignment map formats.
-q2 | --quality2: Read Quality profile for for second read pair (PE) for fastq or sequence alignment map formats.
-qs | --qualityscore: Fixed quality score, for both read pairs in fastq or sequence alignment map formats. It overwrites the quality profiles.
----- Optional -----
Reference Variations:
-mr | --mutationrate: Adding stochastic variations to the reference genome (-i) from a fixed mutation rate, conflicts with number of variations (-v), default = 0.0
-g | --generations: Adding stochastic variations to the reference genome (-i) according to the fixed mutation rate (-mr) across numerous generations, default = 1
-v | --variations: Adding a fixed number of stochastic variations to the reference genome (-i), conflicts with mutation rate (-mr), default = 0
Genetic Variations:
-bcf | -vcf: Variant Calling Format (.vcf) or binary format (.bcf)
-id | --indiv: Integer value (0 - index) for the number of a specific individual defined in bcf header from -vcf/-bcf input file, default = -1 (no individual selected).
e.g -id 0 First individual in the provided vcf file.
-DumpVCF: The prefix of an internally generated fasta file, containing the sequences representing the haplotypes with the variations from the provided vcf file (-vcf|-bcf), for diploid individuals the fasta file contains two copies of the reference genome with the each allelic genotype.
Stochastic Variations:
-indel: Input probabilities and lambda values for a geometric distribution randomly generating insertions and deletions of a random length.
<InsProb,DelProb,InsParam,DelParam>
Insertions and deletions -indel 0.05,0.1,0.1,0.2
Only Insertions -indel 0.05,0.0,0.1,0.0
Only Deletions -indel 0.0,0.5,0.0,0.9
-DumpIndel: The prefix of an internally generated txt file, containing the the read id, number of indels, the number of indel operations saving the position before and after and length of the indel, simulated read length before and after, see supplementary material for detailed example and description.
Postmortem damage (PMD) - Deamination:
-m | --model: Choice of deamination model.
<b,nv,Lambda,Delta_s,Delta_d> || <briggs,nv,Lambda,Delta_s,Delta_d> Parameters for the damage patterns using the Briggs model altered to suit modern day library preparation.
<b7,nv,Lambda,Delta_s,Delta_d> || <briggs07,nv,Lambda,Delta_s,Delta_d> Parameters for the damage patterns using the Briggs model 2007.
nv: Nick rate per site.
Lambda: Geometric distribution parameter for overhang length.
Delta_s: PMD rate in single-strand regions.
Delta_d: PMD rate in double-strand regions.
e.g -m b,0.024,0.36,0.68,0.0097
-dup | --duplicates: Number of PCR duplicates, used in conjunction with briggs modern library prep -m <b,nv,Lambda,Delta_s,Delta_d>
<1,2,4> Default = 1
Nucleotide Alterations:
-mf | --mismatch: Nucleotide substitution frequency file.
-ne | --noerror: Disabling the sequencing error substitutions based on nucleotide qualities from the provided quality profiles -q1 and -q2.
Read Specific:
-na | --noalign: Using the SAM output as a sequence container without alignment information.
-cl | --cycle: Read cycle length, the maximum length of sequence reads, if not provided the cycle length will be inferred from quality profiles (q1,q2).
-ll | --lowerlimit: Lower fragment length limit, default = 30. The minimum fragment length for deamination is 30, so simulated fragments below will be fixed at 30.
-bl | --bufferlength: Buffer length for generated sequence reads stored in the output files, default = 30000000.
-chr | --chromosomes: Specific chromosomes from input reference file to simulate from.
-a1 | --adapter1: Adapter sequence to add for simulated reads (SE) or first read pair (PE).
e.g. Illumina TruSeq Adapter 1: AGATCGGAAGAGCACACGTCTGAACTCCAGTCACCGATTCGATCTCGTATGCCGTCTTCTGCTTG
-a2 | --adapter2: Adapter sequence to add for second read pair (PE).
e.g. Illumina TruSeq Adapter 2: AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGCCGTATCATTT
-p | --poly: Create Poly(X) tails for reads, containing adapters with lengths below the inferred readcycle length.
e.g -p G or -p A
Simulation Specific:
-t | --threads: Number of sampling threads, default = 1.
-t2 | --threads2: Number of compression threads, default = 0.
-s | --seed: Random seed, default = current calendar time (s).
-rng | --rand: Pseudo-random number generator, OS specific
<0,1,2,3>
0 : drand48_r, default for linux or unix, not available for MacOS.
1 : std::uniform_int_distribution
2 : rand_r
3 : erand48, default for MacOS.
実行方法
１、ヒトhg19.faから1000リードをシミュレートする。100塩基長、出力fastqはfq.gz、シングルエンド、1スレッド使用。fastqとsamのシミュレーションでは、リードのクオリティプロファイルのテキストも指定する必要がある。Test_Examplesのプロファイルを指定する。
ngsngs -i hg19.fa -r 1000 -f fq.gz -l 100 -seq SE -t 1 -q1 Test_Examples/AccFreqL150R1.txt -o prefix
-
-i Reference file in fasta format (.fa,.fasta) to sample reads.
-
-r Number of reads to simulate, conflicts with -c option.
-
-c Depth of Coverage to simulate, conflics with -r option.
-
-l Fixed length of simulated fragments, conflicts with -lf & -ld option.
-
-t Number of sampling threads, default = 1.
- -q1 Read Quality profile for single-end reads (SE) or first read pair (PE) for fastq or sequence alignment map formats.
- -o Prefix of output file name.
- -f File format of the simulated output reads. Nucletide sequence w. different compression levels.
<fa || fasta>
<fa.gz || fasta.gz>
Nucletide sequence with corresponding quality score w. different compression levels.
<fq || fastq>
<fq.gz || fastq.gz>
Sequence Alignment Map w. different compression levels.
<sam || bam || cram>
- -seq Simulate single-end or paired-end reads.
<SE> single-end
<PE> paired-end.
prefix.fq.gzが出力される。
２、hg19.faから 1000 リードをシミュレート。シングルエンド、固定品質スコア、下限フラグメント長50。
./ngsngs -i hg19.fa -r 1000 -f fq -lf Test_Examples/Size_dist_sampling.txt -ll 50 -seq SE -t 1 -qs 40 -o prefix
３、hg19.faから 1000 リードをシミュレート。ペアエンド (-seq)、フラグメント（インサート）長は正規分布で平均350塩基長、SD 20、サイクル長を固定 (-cl)、2つの独立した品質プロファイル (-q1,-q2) で生成する。
./ngsngs -i hg19.fa -r 1000 -f fq -ld norm,350,20 -cl 100 -seq PE -t 1 -q1 Test_Examples/AccFreqL150R1.txt -q2 Test_Examples/AccFreqL150R2.txt -o prefix
-
-ld Discrete or continuous probability distributions, given their Probability density function, conflicts with -l & -lf option.
<Uni, Min, Max> Uniform distribution from a closed interval given a minimum and maximum positive integer, e.g. Uni,40,180.
<Norm, Mean, Variance> Normal Distribution, given a mean and variance, e.g. Norm,80,30.
<LogNorm, Mean, Variance> Log-normal Distribution, given a mean and variance, e.g. LogNorm,4,1.
<Pois,Rate> Poisson distribution, given a rate, e.g. Pois,165.
<Exp,Rate> Exponential distribution, given a rate, e.g. Exp,0.025.
<Gam,Shape,Scale> Gamma distribution, given a shape and scale, e.g. Gam,20,2.
- -cl Read cycle length, the maximum length of sequence reads, if not provided the cycle length will be inferred from quality profiles (q1,q2).
- -q1 Read Quality profile for single-end reads (SE) or first read pair (PE) for fastq or sequence alignment map formats.
- -q2 Read Quality profile for for second read pair (PE) for fastq or sequence alignment map formats.
- -qs Fixed quality score, for both read pairs in fastq or sequence alignment map formats. It overwrites the quality profiles.
prefix_R1.fqとprefix_R2.fqが出力される。
４、hg19.faから 1000 リードをシミュレート。プラットフォーム固有のエラーを無効化(-ne)、Briggs 2007モデルによる脱アミノ化パターンを追加、古代のフラグメント長分布(-lf)、シード4(-s)を使用。
./ngsngs -i hg19.fa -r 1000 -f fq -s 4 -ne -lf Test_Examples/Size_dist_sampling.txt -seq SE -m b7,0.024,0.36,0.68,0.0097 -q1 Test_Examples/AccFreqL150R1.txt -o prefix
５、hg19.faから 1000 リードをシミュレート。ペアエンドリード、フラグメント（インサート）長400、Quality Profile (-q1)の分布からサイクル長150とし、内部距離100(400-150*2)と推定、アダプターを追加。
./ngsngs -i hg19.fa -r 1000 -f fq -l 400 -seq PE -q1 Test_Examples/AccFreqL150R1.txt -q2 Test_Examples/AccFreqL150R1.txt -a1 AGATCGGAAGAGCACACGTCTGAACTCCAGTCACCGATTCGATCTCGTATGCCGTCTTCTGCTTG -a2 AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGCCGTATCATTT -o prefix
-
-a1 Adapter sequence to add for simulated reads (SE) or first read pair (PE).
e.g. Illumina TruSeq Adapter 1: AGATCGGAAGAGCACACGTCTGAACTCCAGTCACCGATTCGATCTCGTATGCCGTCTTCTGCTTG
-
-a2 Adapter sequence to add for second read pair (PE).
e.g. Illumina TruSeq Adapter 2: AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGCCGTATCATTT
- -l Fixed length of simulated fragments, conflicts with -lf & -ld option.
６、hg19.faから 1000 リードをシミュレート。シングルエンド、アダプター配列付与、ポリGテール(-p)付与。
./ngsngs -i hg19.fa -r 1000 -f fq -l 80 -seq SE -q1 Test_Examples/AccFreqL150R1.txt -a1 AGATCGGAAGAGCACACGTCTGAACTCCAGTCACCGATTCGATCTCGTATGCCGTCTTCTGCTTG -p G -o prefix
- -p Create Poly(X) tails for reads, containing adapters with lengths below the inferred readcycle length. e.g -p G or -p A
レポジトリから
- 実行可能なフラグメント長の上限は10,000で、30塩基以下のフラグメントは脱アミノ化されない。
- 1024以上のフラグメントの脱アミノ化をシミュレートする場合、相補的なG>A置換で3'末端は脱アミノされない。
- これらは今後のリリースで修正される予定。
- 1千万のシングルエンドリードのシミュレーションに要した時間は16秒だった（20スレッド、3990X CPU使用）。
引用
NGSNGS: next-generation simulator for next-generation sequencing data
Rasmus Amund Henriksen, Lei Zhao, Thorfinn Sand Korneliussen Author Notes
Bioinformatics, Volume 39, Issue 1
