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基因组测序模拟

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基因组测序模拟
基因组测序模拟

一、摘要

通过熟悉已有的基因组测序模拟和评估程序，加深全基因组鸟枪法测序原理的理解，并且能够编写程序模拟全基因组鸟枪法测序，理解覆盖度、测序深度、拷贝数等概念，设置测序相关参数，生成单端/双端测序结果文件

二、材料和方法

1、硬件平台

处理器:Intel（R） Core（TM）i7-4710MQ CPU @ 2.50GHz
安装内存(RAM)：16.0GB

2、系统平台
Windows 8.1，Ubuntu

3、软件平台

art_454
GenomeABC http://crdd.osdd.net/raghava/genomeabc/
Python3.5
Biopython
4、数据库资源

NCBI数据库：https://www.ncbi.nlm.nih.gov/

5、研究对象

酵母基因组Saccharomyces cerevisiae S288c (assembly R64)
ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/146/045/GCF_000146045.2_R64/GCF_000146045.2_R64_genomic.fna.gz

6、方法

art_454的使用
首先至art系列软件的官网，下载软件，在ubuntu系统安装，然后阅读相关参数设置的帮助文档，运行程序。
GenomeABC
进入GenomeABC(http://crdd.osdd.net/raghava/genomeabc/)，输入参数，获得模拟测序结果。
编程模拟测序
下载安装python，并且安装biopython扩展模块，编写程序，模拟单端/双端测序。
三、结果

1、art_454的运行结果

无参数art_454运行，阅读帮助文档

图表 1无参数art_454运行
对酵母基因组进行基因组单端测序模拟，FOLD_COVERAGE设为20，即覆盖度为20.
下图为模拟单端测序，程序运行过程及结果

图表 2 art454单端测序

图表 3 art454单端模拟结果
双端测序模拟，FOLD_COVERAGE设为20，即覆盖度为20；MEAN_FRAG_LEN设为1500，即平均片段长度为1500；STD_DEV设为20，即长度的标准差为20
下图为模拟双端测序，程序运行过程及结果

图表 4 art454双端测序

图表 5 art454双端模拟结果
2、GenomeABC
下图为设置参数页面

下图为结果下载页面

图表 6 结果下载页面
3、编程模拟测序结果
拷贝数是这里的N值；覆盖度是m，测序深度是宏观的量，在这里与覆盖度意思相同，就是测序仪10X，20X。
单端测序

图表 7 程序模拟单端测序
双端测序

图表 8 程序模拟双端测序
测序结果

图表 9 结果文件

因为期望片段长度是600bp，在片段长度区间200-1000bp内，所以大部分的片段都没有删除。
测序结果统计表

测序方式基因组大小(bp) 片段长度区间 (bp) N值期望片段长度克隆保留率片段数量 Reads长度范围（bp） Reads总数量 Reads总长度覆盖度(m值) 理论丢失率(e-m) 覆盖率(1-e-m)
单端 12157kb 200-1000 10 600 0.95 107378 50-100 101968 7645.541kb 0.62889 0.53318 0.46682
单端 12157kb 200-1000 20 600 0.95 213722 50-100 202996 15227.882kb 1.25259 0.28576 0.71424
双端 12157kb 200-1000 10 600 0.95 106704 50-100 202770 15212.662kb 1.25134 0.28612 0.71388
双端 12157kb 200-1000 20 600 0.95 214212 50-100 407186 30534.265kb 2.51164 0.08114 0.91886
四、讨论和结论

程序运行方法

在类的构造方法init()中，调整参数。
Averagefragmentlength为片段平均的长度；
minfragmentlength和maxfragmentlength是保留片段的范围；
cloneRetainprobability是克隆的保留率；
minreadslength和maxreadslength是测序reads的长度范围

模拟测序的诸多方法都封装成了Sequencing类，只需要创建类，并调用singlereadsequencing()和pairreadsequencing()方法，传入文件名的参数即可。

附录

from Bio import SeqIO
from math import exp
import random

class Sequencing:
# N代表拷贝份数
def __init__(self)
      self.fragmentList = []
      self.readsID = 1
      self.readsList = []
      self.averagefragmentlength = 650
      self.minfragmentlength = 500
      self.maxfragmentlength = 800
      self.cloneRetainprobability = 1
      self.minreadslength = 50
      self.maxreadslength = 150
      self.N = 10
      self.genomeLength = 0
      self.allreadslength = 0

# 生成断裂点
def generatebreakpoint(self, seqlen, averageLength):
      # 假设平均每500bp 产生一个断裂点(averageLength = 500),通过随机函数生成seqlen/500个随机断裂点(1到seqlen之间的随机整数)
      breakpoint = [random.randint(0, seqlen) for _ in range(int(seqlen / averageLength))]
      breakpoint.append(seqlen)
      breakpoint.append(0)
      # 把随机断裂点从小到大排序
      breakpoint.sort()
      return breakpoint

# 沿断裂点打断基因组,并删除不符合长度要求的序列片段,定义片段范围:200-1000bp
def breakgenome(self, seq, breakpoint, minfragmentlength, maxfragmentlength):
      for i in range(len(breakpoint) - 1):
         fragment = seq[breakpoint:breakpoint[i + 1]]
& M* J3 T, b* m/ ?3 H1 i& ?, Y- O          if maxfragmentlength > len(fragment) > minfragmentlength:3 t) B7 N( M3 W
            self.fragmentList.append(fragment)
9 f2 W* y4 A( V8 x, P0 I3 t' ?3 b       return self.fragmentList# f2 z) i/ _6 o9 [
6 o' `. X8 R6 @6 J
# 模拟克隆时的随机丢失情况,random.random()生成0-1的保留概率; y# U9 |7 ?6 f
def clonefragment(self, fragmentList, cloneRetainprobability):. @& E. T9 ^% |0 u
      clonedfragmentList = []3 O+ M) R% r1 L" @2 D, W1 J
      Lossprobability = [random.random() for _ in range(len(fragmentList))]
) x* T' U5 h9 a9 [       for i in range(len(fragmentList)):1 H# h/ Y! A7 J/ y" X7 E* q, F+ \
         if Lossprobability <= cloneRetainprobability:
7 r* ^- h0 `# `' {8 W             clonedfragmentList.append(fragmentList)
1 H6 Z" x& H- \3 Z, Z/ Y       return clonedfragmentList7 O- u$ i7 l' H+ S

# w( J! C: O* s& k # 模拟单端测序,并修改reads的ID号8 Y6 ]2 N" j  x: d" A! Q( P3 v
def singleread(self, clonedfragmentList):
0 X, z1 O# e6 s8 c: q. K       for fragment in clonedfragmentList:9 ^9 Z; J9 {% p& q9 G$ N5 }0 A
         fragment.id = ""1 f% ?1 E! O$ j5 O
         fragment.name = ""
( {, U: ~0 |" b4 m1 o* N* i6 j" c          fragment.description = fragment.description[12:].split(",")[0], `" I+ A+ j, Q( i8 l- X
         fragment.description = str(self.readsID) + "." + fragment.description" C& ~* l( v$ H9 C0 H
         self.readsID += 1% f5 Y( {8 s9 \9 Q4 q( \* f3 K& P
         readslength = random.randint(self.minreadslength, self.maxreadslength)$ E. f6 D  l* [
         self.allreadslength += readslength
# X* w9 P& [8 B2 M( P          self.readsList.append(fragment[:readslength])' G. s0 u; z. R
. E' ^% X& J" p! B4 M
def singlereadsequencing(self, genomedata, sequencingResult):
3 H" t& b0 Y2 m1 I+ W       for seq_record in SeqIO.parse(genomedata, "fasta"):" v2 Y; k7 `4 O/ M" c8 Z- x) z
         seqlen = len(seq_record)
) c9 g- A7 |3 X- ~3 E* m: [          self.genomeLength += seqlen
8 z' C( d) `) c- s( ?0 d0 I8 M          for i in range(self.N):/ Z/ U( U* N, L# e9 S5 P4 |* u
            # 生成断裂点
- T( @# r% s5 Q3 w# F: C$ V% v             breakpoint = self.generatebreakpoint(seqlen, self.averagefragmentlength)
: d7 z3 g  v+ F3 f2 D8 i! ^             # 沿断裂点打断基因组$ M  O. s+ ^0 i; e+ a, N
            self.breakgenome(seq_record, breakpoint, self.minfragmentlength, self.maxfragmentlength)$ R# X/ f% l- v# I; B  q( u
      # 模拟克隆时的随机丢失情况& M" D" H8 M. R
      clonedfragmentList = self.clonefragment(self.fragmentList, self.cloneRetainprobability)' i: Z2 H9 n% b/ v* H0 _
      # 模拟单端测序
      self.singleread(clonedfragmentList)
& X* ^7 v2 E+ E3 i       SeqIO.write(self.readsList, sequencingResult, "fasta")) A$ j7 J; W9 q4 s, v- B4 `/ P( P

6 F: F8 G  G6 t; g. t def pairread(self, clonedfragmentList):
. `7 p% S& k; L  o: o1 h! d       for fragment in clonedfragmentList:' S6 ?8 }0 j* ?2 T& w) a
         fragment.id = ""2 `  P8 h- _3 r7 k
         fragment.name = ""
! ^! _  x9 L! t) x! S          description = fragment.description[12:].split(",")[0]
1 K. m: g' h. w          fragment.description = str(self.readsID) + "." + description
. ]( g: p- D# k) Y" ~6 A: @$ A- t          readslength = random.randint(self.minreadslength, self.maxreadslength)
4 A/ d+ w7 s7 u& P( N+ s          self.allreadslength += readslength6 {- e) T+ }! ]5 Q% c5 H" F( |
         self.readsList.append(fragment[:readslength])
% u& q) ^: ~# u5 t: I6 d% f
2 e6 L5 ~7 e9 }4 ^1 u& ~          readslength = random.randint(self.minreadslength, self.maxreadslength)
* d. _0 {9 q, d* M- z          self.allreadslength += readslength+ ~4 B/ a+ l  Q5 \6 V

2 ?0 u2 j6 ~# x' n$ G- b          fragmentcomplement = fragment.reverse_complement()
/ _$ ?* {2 W3 U          fragmentcomplement.id = ""
/ t- j% h$ P9 Z- m0 |' [          fragmentcomplement.name = "". l% g. f8 C# r8 R; \& C  y0 l
         fragmentcomplement.description = str(self.readsID) + "." + description  e6 j3 ]3 E* J0 g: G$ w2 H. x
         self.readsList.append(fragmentcomplement[:readslength])
/ ?$ X; M* `, ^, Z( x
0 E! O, F* M5 r. g: g          self.readsID += 1% w: T$ |9 v  ]4 o# @! `- v

* \# ?- ?5 u  e8 |  l0 z( O def pairreadsequencing(self,genomedata, sequencingResult_1, sequencingResult_2):
0 e8 d2 Q' e5 y, y/ C       for seq_record in SeqIO.parse(genomedata, "fasta"):
. K& O4 {8 T# k/ }& R4 e9 |& k          seqlen = len(seq_record)
+ G5 j. N: r3 g1 I' h          self.genomeLength += seqlen
* S  k2 c# p8 a. ^; r; E          for i in range(self.N):9 j& h  w5 h6 @+ {' J! }
            # 生成断裂点
& q5 a" t5 t7 o  R, K- J9 @             breakpoint = self.generatebreakpoint(seqlen, self.averagefragmentlength)
9 M: O* H! d7 f             # 沿断裂点打断基因组6 y+ U0 t" q- T2 R" }% k0 v
            self.breakgenome(seq_record, breakpoint, self.minfragmentlength, self.maxfragmentlength)
6 H1 K7 d/ X8 X       # 模拟克隆时的随机丢失情况" p/ I0 d( X! P1 `
      clonedfragmentList = self.clonefragment(self.fragmentList, self.cloneRetainprobability)1 O/ q5 L/ U3 K+ y% e2 i
      # 模拟双端测序
% r0 X" z4 m9 J7 F       self.pairread(clonedfragmentList)
/ x7 |) F! Z! m! Q       readsList_1 = [self.readsList for i in range(len(self.readsList)) if i % 2 == 0]8 a0 Y3 O, p% R; c6 ^/ a6 f
      readsList_2 = [self.readsList for i in range(len(self.readsList)) if i % 2 == 1]4 _+ @5 U  P' T
      SeqIO.write(readsList_1, sequencingResult_1, "fasta")0 L/ _0 I8 C" }7 f" \
      SeqIO.write(readsList_2, sequencingResult_2, "fasta"), n1 N1 X0 g' B2 J- C0 c
4 r, l6 V% |" h9 a. a
def resultsummary(self):
6 P7 B* u- [! h- @  ^# n/ |+ Y       print("基因组长度:" + str(self.genomeLength / 1000) + "kb")
" I0 A+ M* v/ ]1 D* n       print("片段长度区间:" + str(self.minfragmentlength) + "-" + str(self.maxfragmentlength))6 d  m# k  G, f$ O: _6 \
      print("N值:" + str(self.N))9 |: f6 w- h9 \
      print("期望片段长度:" + str(self.averagefragmentlength))
) j: n+ X  s. U2 B" m% D# u. J       print("克隆保留率:" + str(self.cloneRetainprobability))4 N- o7 G+ e# c6 ]$ ^; h7 ?
      print("片段数量:" + str(len(self.fragmentList)))
; ]  I: ]% Y5 e3 w9 m5 ^- Q9 d* {% o       print("reads长度:" + str(self.minreadslength) + "-" + str(self.maxreadslength))2 O8 ]# i1 I5 P& D  S7 a
      print("reads总数量:" + str(len(self.readsList)))
* x/ U2 L5 b9 j9 Z       print("reads总长度:" + str(self.allreadslength / 1000) + "kb")
$ `- H1 V1 i( u. t9 m' L       m = self.allreadslength / self.genomeLength
* Z. B+ y4 \2 q7 Y' o5 A       print("覆盖度(m值):" + str(round(m, 5)))
6 w( r; t& K7 i- C% N7 r" r       print("理论丢失率(e^-m):" + str(round(exp(-m), 5)))3 y3 X4 F& T0 g) F, ?0 l+ `
      print("覆盖率(1-e^-m):" + str(round(1 - exp(-m), 5)))
3 Q/ J. R) h& T/ }" V# -------------------------------------------主程序-------------------------------------------7 c9 @  j) [# |% f
# 模拟单端测序0 i( v) N( ]9 O- W* p# N
sequencingObj = Sequencing()8 X+ r# g  Y0 P) G# [$ z4 d9 p
sequencingObj.singlereadsequencing("data/NC_025452.fasta", "result/virusSingleRead.fa")! J6 q" `6 ~. R7 [% L, D3 V- q! r
sequencingObj.resultsummary(), Y) T6 L- u; Y) B& s$ K
" P: x9 P  x) ?  E$ @1 H  c; E; a
# 模拟双端测序
# N: D3 P; X8 w6 B8 JsequencingObj = Sequencing()
3 ~" G8 F3 D1 n  ]sequencingObj.pairreadsequencing("data/GCF_000146045.2_R64_genomic.fna", "result/yeastPairRead_1.fa", "result/yeastPairRead_2.fa")
9 p2 {+ V) e: D. [sequencingObj.resultsummary()3 K! K4 @2 U$ P& ?$ H% h9 a, ~7 |
from Bio import SeqIO
  p' K& i6 ^9 j1 y% p6 j( l3 S8 `from math import exp
2 x' f* Y% j. |" {. Y, H! l" J8 j2 }import random  O: j) t" a/ W+ ]8 O5 m8 v4 {2 E

+ l7 h' L! D  y4 Gclass Sequencing:
# p; R' V3 y$ H: c" Q8 e& V # N代表拷贝份数" ^5 x2 A1 [" X
def __init__(self):2 v* s+ j# p8 [$ a" L
      self.fragmentList = []
% @: W  g5 k0 D3 A! c' F- ?7 P       self.readsID = 1) @1 x. K! T* t
      self.readsList = []3 r) @' w: [4 a; b7 i+ q
      self.averagefragmentlength = 650
: `% r, I1 E, q4 \       self.minfragmentlength = 500
( D; @& Z" z6 @+ b9 j3 U9 b( `8 d       self.maxfragmentlength = 800
9 f& \2 O9 c% \3 Q+ ~       self.cloneRetainprobability = 1, L  C" o3 V) N( {3 _
      self.minreadslength = 50
0 L5 O& P( U# ^' R: i: I       self.maxreadslength = 150
; G2 {* D6 S$ c; y. x* R4 A       self.N = 10
( H# q$ D: u# H9 y       self.genomeLength = 0
- P( W$ O6 v/ S$ \6 f# T9 R       self.allreadslength = 07 z4 m3 D6 n0 d3 u1 ?4 X' J, l
  u& O* p8 o6 E, a% B# x
# 生成断裂点
' c+ r, h3 f2 a8 W- r def generatebreakpoint(self, seqlen, averageLength):
! j) s! H( ?' U$ D  p! @7 p* g       # 假设平均每500bp 产生一个断裂点(averageLength = 500),通过随机函数生成seqlen/500个随机断裂点(1到seqlen之间的随机整数)7 d( s/ a! S, P0 F
      breakpoint = [random.randint(0, seqlen) for _ in range(int(seqlen / averageLength))]
* B8 V2 ]) X% M       breakpoint.append(seqlen)) c5 `0 l* N8 h; S! t! d! }" J
      breakpoint.append(0)
4 ]1 ^% h+ D( C8 G       # 把随机断裂点从小到大排序0 v; J9 `* f4 I) X9 w7 w9 _
      breakpoint.sort()! z' ]) Y: l; c, s$ l) N4 j% e
      return breakpoint
$ s: @. Y  N) ?+ ~; `( t* d# m) ]" b9 R, k( ?" ?
# 沿断裂点打断基因组,并删除不符合长度要求的序列片段,定义片段范围:200-1000bp% s8 ]5 R  I, x2 p4 N( ^; Z4 j
def breakgenome(self, seq, breakpoint, minfragmentlength, maxfragmentlength):  w: Q6 i% }6 P8 x
      for i in range(len(breakpoint) - 1):' _; o0 M" h, j: n& E: P% Z
         fragment = seq[breakpoint:breakpoint[i + 1]]+ c# g$ k5 }& d5 d
         if maxfragmentlength > len(fragment) > minfragmentlength:  B. ~1 A9 T1 _& W; f. O$ z
            self.fragmentList.append(fragment)
- r4 B; T6 ~4 L! N# E0 z       return self.fragmentList1 p" t7 |+ Z+ X  h

$ k! y4 P' R, d9 l) h: X1 V- p # 模拟克隆时的随机丢失情况,random.random()生成0-1的保留概率$ o- m* R" H& _4 A
def clonefragment(self, fragmentList, cloneRetainprobability):
- M' e2 [* o# D* L       clonedfragmentList = []$ C; y* s( \/ F+ k. m( N4 C
      Lossprobability = [random.random() for _ in range(len(fragmentList))]: G  }$ n- _, |4 j
      for i in range(len(fragmentList)):
& a" z+ l* P4 b          if Lossprobability <= cloneRetainprobability:
1 Y1 t9 K7 l  r' L" s; m2 N             clonedfragmentList.append(fragmentList)* O% e+ ~% f) _: U
      return clonedfragmentList0 A4 ?! g+ P; a0 c: x
% P& x/ Z, S: @% ]" T: k( o
# 模拟单端测序,并修改reads的ID号$ M  o  d% Y# A+ f4 X
def singleread(self, clonedfragmentList):
, {6 C7 I7 \& r4 ^$ \! _) h4 X       for fragment in clonedfragmentList:6 }& h. {3 r- ~
         fragment.id = ""
# ]; _& L% K; P9 E4 u0 M: u          fragment.name = ""
4 m/ F! Y" y- c% e! X7 t          fragment.description = fragment.description[12:].split(",")[0], G  }' m0 `( K; b* u4 g
         fragment.description = str(self.readsID) + "." + fragment.description7 g* B) R& x, S% _( z' x
         self.readsID += 1
  F% H9 @1 g$ E+ V6 u! G          readslength = random.randint(self.minreadslength, self.maxreadslength)
) B5 M' x' S6 F8 h) {7 f4 |1 y9 P          self.allreadslength += readslength
9 g  X* h  J; r5 A. h, r7 F2 F          self.readsList.append(fragment[:readslength])' h& ?9 H3 M  s# u: E

$ n8 s8 Q6 |2 `2 N. R/ p% ?1 t def singlereadsequencing(self, genomedata, sequencingResult):
: b1 h* x' C2 o) T- U' c( q! L       for seq_record in SeqIO.parse(genomedata, "fasta"):
3 c2 [% i: t5 m$ w          seqlen = len(seq_record)
4 w6 c7 p3 [) i" c* ~          self.genomeLength += seqlen
5 }# j, M8 q# w4 G  w& Y          for i in range(self.N):
' K+ o! }! W1 s/ o6 C             # 生成断裂点% E+ {7 C7 I+ O
            breakpoint = self.generatebreakpoint(seqlen, self.averagefragmentlength)! L( {8 Y, V3 o" X# L# k
            # 沿断裂点打断基因组0 A/ V0 |+ Z: ~: S
            self.breakgenome(seq_record, breakpoint, self.minfragmentlength, self.maxfragmentlength)# [8 O0 a+ D. A& B* W
      # 模拟克隆时的随机丢失情况
8 [) Y# o1 ^. h+ H6 M8 M       clonedfragmentList = self.clonefragment(self.fragmentList, self.cloneRetainprobability)) F. ^' Q) k, P9 ~( Y; k
      # 模拟单端测序* r; i" K% e" I+ C( k6 t
      self.singleread(clonedfragmentList)
& |4 \6 l% C& L       SeqIO.write(self.readsList, sequencingResult, "fasta"), O% @4 e. U( D

- T- r9 l, @1 L; j; A% K5 }( N def pairread(self, clonedfragmentList):8 Q3 x7 ^, j, e3 Y" g5 f
      for fragment in clonedfragmentList:
8 V" C* r; Q$ w  |! q* a! n          fragment.id = ""
: }1 y5 x5 q2 D+ i# \4 l- R          fragment.name = ""
- t" v6 G; G  y  [  o          description = fragment.description[12:].split(",")[0]
) M7 t  g5 S' o% y8 Z4 c2 u& ~          fragment.description = str(self.readsID) + "." + description
6 {+ c! W$ A$ s, I          readslength = random.randint(self.minreadslength, self.maxreadslength)
: B2 r! b# N# z9 E9 m" W          self.allreadslength += readslength
8 M/ s2 O* A# r3 J3 @7 \/ O8 _3 X          self.readsList.append(fragment[:readslength])
/ k6 K) R' v/ f9 g
+ ]8 s5 F$ r  h" h          readslength = random.randint(self.minreadslength, self.maxreadslength)
. q+ P5 q2 C" C4 A          self.allreadslength += readslength
+ Y- O( v8 @/ @( O- c( D+ d+ w: e; f
         fragmentcomplement = fragment.reverse_complement()/ @4 w  E0 B, A& E0 T8 ^
         fragmentcomplement.id = ""+ p) E$ `& O: f; X1 H( {  c
         fragmentcomplement.name = ""( w: T* \2 m5 |. S  X! s/ P4 Y
         fragmentcomplement.description = str(self.readsID) + "." + description# `7 t9 I4 F" J6 _. V
         self.readsList.append(fragmentcomplement[:readslength])/ y3 ]  V9 E8 f$ b  X
* a1 h0 ?' ?8 c  z7 V" X# s
         self.readsID += 1
' Y& c3 T8 y5 i0 y; C! ~! t3 ]" W) K7 k2 @4 D# o1 \$ w: N/ ?# f; [
def pairreadsequencing(self,genomedata, sequencingResult_1, sequencingResult_2):
' j7 ?$ \# [+ A$ C; ]       for seq_record in SeqIO.parse(genomedata, "fasta"):
3 S- p$ x4 D$ u4 }3 F3 G. }& E# j          seqlen = len(seq_record)# a2 g" _, s- `. \
         self.genomeLength += seqlen
7 e" q% k4 D6 q6 ^/ ^3 d/ a& n          for i in range(self.N):
+ j2 B3 c1 Y' Z) T             # 生成断裂点. A, G" v2 ?+ V( V$ s2 o
            breakpoint = self.generatebreakpoint(seqlen, self.averagefragmentlength)0 p) p! b' `5 H8 ?2 \8 g6 }2 R
            # 沿断裂点打断基因组/ \: x2 T2 @, g
            self.breakgenome(seq_record, breakpoint, self.minfragmentlength, self.maxfragmentlength)
0 G8 {: \, a, m: U4 ]! S7 n       # 模拟克隆时的随机丢失情况' W6 |& G4 y! H- [9 V& Y$ s7 B7 N  N: I
      clonedfragmentList = self.clonefragment(self.fragmentList, self.cloneRetainprobability)
4 o  g- t( S! {: o1 z       # 模拟双端测序
+ ~( s+ q1 H1 B( i/ q: O8 a9 ^# p4 y: T       self.pairread(clonedfragmentList)% L- h* i$ x; i% Y5 T  m
      readsList_1 = [self.readsList for i in range(len(self.readsList)) if i % 2 == 0]& p: t% X: ^7 `9 w* M- m) t& W5 q
      readsList_2 = [self.readsList for i in range(len(self.readsList)) if i % 2 == 1]& t- Y2 R! U; H/ C  G5 _
      SeqIO.write(readsList_1, sequencingResult_1, "fasta")  p6 i* x; V9 t+ ~- L' t  W4 k1 S( S7 e
      SeqIO.write(readsList_2, sequencingResult_2, "fasta")1 ]* \1 P; ~; t& S

" ]+ M) a; G7 l7 W def resultsummary(self):* ?( W$ M& I0 v1 ?; k2 M5 ^5 Q* [
      print("基因组长度:" + str(self.genomeLength / 1000) + "kb")
+ S9 }+ E0 [  V; r       print("片段长度区间:" + str(self.minfragmentlength) + "-" + str(self.maxfragmentlength))/ ~% p2 o3 {) f; [, e
      print("N值:" + str(self.N)). g6 Q* W* m8 V4 Q7 y0 |7 ?" Q
      print("期望片段长度:" + str(self.averagefragmentlength))
; y, L8 \* R) z2 P) M       print("克隆保留率:" + str(self.cloneRetainprobability)), U2 l! Z2 f( [5 R3 W- H
      print("片段数量:" + str(len(self.fragmentList)))
. A1 P0 J. O6 i9 |       print("reads长度:" + str(self.minreadslength) + "-" + str(self.maxreadslength))& D; s. Q7 K5 W: ]
      print("reads总数量:" + str(len(self.readsList)))1 E0 l; }& L1 B" x( _* F6 J7 r
      print("reads总长度:" + str(self.allreadslength / 1000) + "kb")
' Q2 x& m5 [" y: {9 N- l& o       m = self.allreadslength / self.genomeLength
, j9 H2 N% |' r5 a       print("覆盖度(m值):" + str(round(m, 5)))9 r2 z# M4 t& Y1 Y6 p& i! S
      print("理论丢失率(e^-m):" + str(round(exp(-m), 5)))
8 g: ?7 q) e- A: Z: Z- [+ i       print("覆盖率(1-e^-m):" + str(round(1 - exp(-m), 5)))" w1 |3 q1 Z6 n; B) N" z9 i) m
# -------------------------------------------主程序-------------------------------------------
) D: F/ s/ J6 N$ Q4 ?1 U& u# 模拟单端测序
$ w  `# J% Q, e8 q% tsequencingObj = Sequencing(): J! Z) x$ i) i
sequencingObj.singlereadsequencing("data/NC_025452.fasta", "result/virusSingleRead.fa")- \; w) l0 W2 ~: c
sequencingObj.resultsummary()' C2 |& z* j1 t+ z/ w

$ ^. y* }- b; M* {, R% i5 Z( ]# 模拟双端测序4 b/ k" W% I7 w& d$ X3 N
sequencingObj = Sequencing()
$ W) _& X7 `9 X2 f* GsequencingObj.pairreadsequencing("data/GCF_000146045.2_R64_genomic.fna", "result/yeastPairRead_1.fa", "result/yeastPairRead_2.fa")' e6 u$ }- ?+ t" K* r6 y' P$ v
sequencingObj.resultsummary(). h3 y% T# ~5 [& `! ]% v

2 f) W( x6 L$ g4 [! d: i8 x$ F( S0 N; Z9 X- U# F& s; {1 |' l
' [% |, z3 Q0 v6 D

6 ~0 d1 Q" B7 R* ^