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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]]5 o5 q7 }% d7 f# |
         if maxfragmentlength > len(fragment) > minfragmentlength:
+ p) r3 |/ B/ j3 x" w             self.fragmentList.append(fragment)
7 b# I' d$ \1 K& W: V% Y       return self.fragmentList
- F5 m' I, g$ r- s: B, u) e3 Y* ]/ f
# 模拟克隆时的随机丢失情况,random.random()生成0-1的保留概率! q( D! }% O/ C) `% _
def clonefragment(self, fragmentList, cloneRetainprobability):% W+ x9 b) c) r& Q. F1 r; H& n
      clonedfragmentList = []5 S1 b$ Q+ t- P: z  Q8 c0 R
      Lossprobability = [random.random() for _ in range(len(fragmentList))]
7 |: y* y+ K; r8 U9 q, z1 H! E: \       for i in range(len(fragmentList)):
2 O2 ~& i' [/ o# O# q* x6 _/ z          if Lossprobability <= cloneRetainprobability:
2 H6 r/ ]% h0 R3 s; W( Q             clonedfragmentList.append(fragmentList)  Y! f0 P1 M- V. P7 Q  k  Z, `! k$ A
      return clonedfragmentList
0 U1 _9 X. F- r0 j: f' w) E" N4 {7 W1 W0 N  i! w% e
# 模拟单端测序,并修改reads的ID号+ s1 m2 W/ q( p4 A* c
def singleread(self, clonedfragmentList):
* ~; n6 @, u; t" k       for fragment in clonedfragmentList:
) y6 o6 j9 o6 G          fragment.id = ""! v& ~2 v% ^% G3 n4 }
         fragment.name = ""9 d) }, _/ p2 j0 ?5 @, l: N, f3 m
         fragment.description = fragment.description[12:].split(",")[0]
  j1 v+ [6 @8 M& r3 c          fragment.description = str(self.readsID) + "." + fragment.description
- U1 Q% x- W4 W. @7 E8 G$ i          self.readsID += 1
# N2 B! c( Y. f          readslength = random.randint(self.minreadslength, self.maxreadslength)
6 L, x  k3 r7 V+ r, @+ r          self.allreadslength += readslength+ ]8 `6 v6 ?, c; X
         self.readsList.append(fragment[:readslength])% }/ Z5 J8 x# i, v. @" Y
6 F9 {0 d+ b2 J. J! j: }5 n  o
def singlereadsequencing(self, genomedata, sequencingResult):, Y  r  m% t+ K0 d( N
      for seq_record in SeqIO.parse(genomedata, "fasta"):5 {1 [$ _2 ?$ ~1 I" P; P/ q
         seqlen = len(seq_record)
- N9 @& P% {: j7 M/ z- q" a$ o          self.genomeLength += seqlen
8 m9 o* ]& X( J! r2 C          for i in range(self.N):' e( @- Y- N: J) q
            # 生成断裂点3 X) e, N  U2 u3 g5 T9 c
            breakpoint = self.generatebreakpoint(seqlen, self.averagefragmentlength)
  r- t( ?" O. h9 p3 }) b             # 沿断裂点打断基因组& _: K- p* f3 Z
            self.breakgenome(seq_record, breakpoint, self.minfragmentlength, self.maxfragmentlength)
" P" P# |# r4 ?       # 模拟克隆时的随机丢失情况- h( z- p3 x- p6 d7 I0 V8 x
      clonedfragmentList = self.clonefragment(self.fragmentList, self.cloneRetainprobability)/ m  r, G. o  \: _: \* \
      # 模拟单端测序
) w" @+ M* w" [* v, S3 j' B       self.singleread(clonedfragmentList)
. Y# p' O  |' d) F/ D- J1 ?3 ?: n       SeqIO.write(self.readsList, sequencingResult, "fasta")# O% |+ Z5 P: v

; k% b5 b9 n( M; \7 E def pairread(self, clonedfragmentList):
. r5 l. D9 r) H8 {1 T       for fragment in clonedfragmentList:/ F. ^) t; A2 R8 n0 c0 k3 T
         fragment.id = ""# z9 j" _1 z! i9 }
         fragment.name = ""4 }* d1 q) Z6 V! C% B% [* `* y/ u
         description = fragment.description[12:].split(",")[0]
* p: K8 J& H# r: e! U% W: v  ^          fragment.description = str(self.readsID) + "." + description4 c( Z  \$ t* ~5 {
         readslength = random.randint(self.minreadslength, self.maxreadslength)' O$ v7 u7 e8 \3 G2 Z! i
         self.allreadslength += readslength
3 Z- c1 A9 z3 X+ W; u8 E+ `& S' R  x          self.readsList.append(fragment[:readslength])" {2 P3 P! v/ {$ i+ C* ~# K! `. k, Y

% M, }. z1 g+ t' W1 v$ [$ s9 B          readslength = random.randint(self.minreadslength, self.maxreadslength)+ A; A, m  G  e+ @; Y$ L* I
         self.allreadslength += readslength9 t3 p- n/ k1 V' w6 ~* E
0 I% u' X; b# k
         fragmentcomplement = fragment.reverse_complement()2 O2 h5 W! L0 n$ y
         fragmentcomplement.id = ""
' N( l: U/ L# I. B7 q9 c          fragmentcomplement.name = ""8 c2 u) b1 ?& s+ B! h3 M8 j
         fragmentcomplement.description = str(self.readsID) + "." + description
9 z; G! q; |+ n3 x5 E& L8 P; f! b) P          self.readsList.append(fragmentcomplement[:readslength])1 D9 |0 a: ~# G/ g8 I: @
8 F* O9 g4 o& @" z8 A3 l( \+ n
         self.readsID += 19 n9 C3 H& n/ e  K8 i6 F

. T# X# _( J1 K def pairreadsequencing(self,genomedata, sequencingResult_1, sequencingResult_2):$ F' Z8 k: f8 o$ Z
      for seq_record in SeqIO.parse(genomedata, "fasta"):
1 k% w; c* L% }- I: W          seqlen = len(seq_record)
: C1 p# G* ?' d          self.genomeLength += seqlen
7 @$ d; l% l& n) I          for i in range(self.N):8 q7 d, q1 U. Q7 ~6 i
            # 生成断裂点% P: C! s3 b- G( ~9 z* L  x
            breakpoint = self.generatebreakpoint(seqlen, self.averagefragmentlength)2 w; q% P+ N" ?! E' T& L
            # 沿断裂点打断基因组* x% y; ~/ i$ ~) T: T$ L
            self.breakgenome(seq_record, breakpoint, self.minfragmentlength, self.maxfragmentlength)! w$ u" F9 S6 m& d1 u
      # 模拟克隆时的随机丢失情况% \& @- ~- S/ L; x# _7 F
      clonedfragmentList = self.clonefragment(self.fragmentList, self.cloneRetainprobability)9 W% J7 R( K8 ~( L  C5 m5 w& ?
      # 模拟双端测序' _' V7 r) Y- o1 s
      self.pairread(clonedfragmentList)) G  s: i) F! F) w
      readsList_1 = [self.readsList for i in range(len(self.readsList)) if i % 2 == 0]
7 O& t' ~7 J( d0 a8 N% x* @5 {       readsList_2 = [self.readsList for i in range(len(self.readsList)) if i % 2 == 1]
% \/ q+ w; O0 k( W0 |3 B% E       SeqIO.write(readsList_1, sequencingResult_1, "fasta")% c9 p. i7 `8 w; ]) o% r. H
      SeqIO.write(readsList_2, sequencingResult_2, "fasta")
, @% X" V3 C4 g" |( b; N9 t: d9 j& m. y' o
def resultsummary(self):
- s# o  z% E% c2 {( u+ F& H       print("基因组长度:" + str(self.genomeLength / 1000) + "kb")
: X$ b, v# m" }       print("片段长度区间:" + str(self.minfragmentlength) + "-" + str(self.maxfragmentlength))
, n8 b5 t& k9 x3 X       print("N值:" + str(self.N))
2 ]$ c! w2 I* C/ p. x       print("期望片段长度:" + str(self.averagefragmentlength))
9 K; D4 D" x5 y' u       print("克隆保留率:" + str(self.cloneRetainprobability))9 Y8 K7 e- G- v0 F7 D# y; v
      print("片段数量:" + str(len(self.fragmentList)))( V5 N8 T6 p4 J, P
      print("reads长度:" + str(self.minreadslength) + "-" + str(self.maxreadslength))8 z* k5 l. x0 _/ K; F2 a/ m- o2 n
      print("reads总数量:" + str(len(self.readsList)))3 {+ @) v! g7 i  i' \( u5 h# ?
      print("reads总长度:" + str(self.allreadslength / 1000) + "kb")% M  z- ^. n8 _8 D8 m8 ]$ y+ H  Z
      m = self.allreadslength / self.genomeLength& c5 U1 R' x$ X4 @: h
      print("覆盖度(m值):" + str(round(m, 5)))
  r  S- w3 E8 n/ S       print("理论丢失率(e^-m):" + str(round(exp(-m), 5))). ^9 R) O4 b5 z( o2 F
      print("覆盖率(1-e^-m):" + str(round(1 - exp(-m), 5)))
" ], |+ Q; e2 s1 H' U+ @( g# -------------------------------------------主程序-------------------------------------------
! b  c' J5 x% m0 e# 模拟单端测序
2 E/ r3 {% B( S) s* r$ xsequencingObj = Sequencing()
0 u* f. g# \* YsequencingObj.singlereadsequencing("data/NC_025452.fasta", "result/virusSingleRead.fa")
7 I; k$ T/ m8 `  k9 N% C) ~- p7 asequencingObj.resultsummary()
0 X8 N! ?4 |1 M! C2 F+ ~# A" I% S  G, q" B
# 模拟双端测序
! N$ ^- [- C/ h8 ]sequencingObj = Sequencing()
! ]3 t. X( v  \5 P2 x5 {# ~sequencingObj.pairreadsequencing("data/GCF_000146045.2_R64_genomic.fna", "result/yeastPairRead_1.fa", "result/yeastPairRead_2.fa")
' \$ N, U  e7 z1 c0 g* }+ AsequencingObj.resultsummary()) j: \/ b' Y8 i2 |
from Bio import SeqIO
5 Z- ^7 V/ j  C: bfrom math import exp
+ }9 ?" T) ?4 t- ]& F! s9 g7 @import random
. Q2 {4 V: y5 H
2 B) X5 a$ j  @' m1 ]class Sequencing:, m' S) T  J& s# v
# N代表拷贝份数) c6 H* p$ N% `. T
def __init__(self):
5 C4 s0 X; w3 n3 S7 m1 A7 R  R1 L       self.fragmentList = []
& B6 d) x$ h- q* U( v8 R. C0 u       self.readsID = 1
2 W) v; u# d* v2 J9 @       self.readsList = []
) h! c) K, m. Q& a       self.averagefragmentlength = 650' r( n. f  y* A, ]( f
      self.minfragmentlength = 500. E/ E# F- T  J/ e7 u% E* a) o9 _) s
      self.maxfragmentlength = 800
2 G( X) c1 z4 [( b       self.cloneRetainprobability = 1
2 q$ i- l- Z& ~- h       self.minreadslength = 502 |/ a2 v" `& C2 h
      self.maxreadslength = 150& U% R: I3 D0 o1 J# z! Y8 U
      self.N = 106 ~4 s" r* G" G% w) @$ m
      self.genomeLength = 0
6 l3 C) ]1 q7 J& X$ Y( v% J       self.allreadslength = 0
. E) K* J6 S: b" s% ]4 z
( ?( G3 ]' P/ s- M' Q. e0 O3 C # 生成断裂点
& ^: X9 r& f# I def generatebreakpoint(self, seqlen, averageLength):2 `* s+ g  c/ T7 g2 s( f, h1 }
      # 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)
6 f, l. J+ h- P& q9 l       breakpoint = [random.randint(0, seqlen) for _ in range(int(seqlen / averageLength))]
/ \, [% L6 X! U  c2 ]       breakpoint.append(seqlen)  U0 y7 D/ D  N
      breakpoint.append(0)
: F# ?' p+ S1 O7 l0 K       # 把随机断裂点从小到大排序
6 G5 @9 _, V  ]" K( _! M       breakpoint.sort()7 y0 V* B) v6 t8 P
      return breakpoint
' K* c. O1 I; t9 ~5 S
* g; o' y- q9 z+ a( [+ }% a # 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
$ Z  h( N) |4 n1 e  _. }& }4 ~ def breakgenome(self, seq, breakpoint, minfragmentlength, maxfragmentlength):3 B3 ^. u  [' M; `3 V9 g
      for i in range(len(breakpoint) - 1):. u7 x0 e9 s1 _& I
         fragment = seq[breakpoint:breakpoint[i + 1]]
8 n  ~+ i  S! V2 m. u* t          if maxfragmentlength > len(fragment) > minfragmentlength:7 P9 J7 d( k' b1 i- _+ b4 m
            self.fragmentList.append(fragment)
, R7 H  N3 F# D. n3 L) _# ~       return self.fragmentList
9 D% O' z0 n) b' s9 z) x0 H' |  l! g  H5 l# {; l
# 模拟克隆时的随机丢失情况,random.random()生成0-1的保留概率. v& j# M% h% y1 q6 _6 U
def clonefragment(self, fragmentList, cloneRetainprobability):
, w; P) i6 y6 {) G/ G       clonedfragmentList = [], _2 ?  n* ~# L# ^/ O. l/ l
      Lossprobability = [random.random() for _ in range(len(fragmentList))]' R1 \* f* V0 U! p( ^4 c
      for i in range(len(fragmentList)):: U( U. J) ]! z8 r, t* L' [8 a
         if Lossprobability <= cloneRetainprobability:
5 N. s, @) ?4 d2 j( D5 Q9 m             clonedfragmentList.append(fragmentList)4 T9 o/ L: ]: Z7 Q
      return clonedfragmentList
2 A* g8 h$ l# {3 S, V8 ]$ f
2 |  X; ~; ]) ~5 U; t # 模拟单端测序,并修改reads的ID号* Z0 v# ~$ x3 e
def singleread(self, clonedfragmentList):9 I5 R8 m7 ^0 s5 h
      for fragment in clonedfragmentList:
# P- u  u' y. u) J1 z          fragment.id = ""/ h) d- i& P- ^# k
         fragment.name = "": G% i. Y: n" f6 {6 s8 Z
         fragment.description = fragment.description[12:].split(",")[0]
, l5 [: F" ?% Q          fragment.description = str(self.readsID) + "." + fragment.description" p9 \5 p9 ]) I$ u3 }
         self.readsID += 18 }( A) L! {! e$ ?
         readslength = random.randint(self.minreadslength, self.maxreadslength): F/ E, k! h4 e$ z8 }# Y
         self.allreadslength += readslength
* |# d  a$ O& }/ Y( g          self.readsList.append(fragment[:readslength])  }# M) f0 C. r' n5 x

; o% X2 L! K9 l% G def singlereadsequencing(self, genomedata, sequencingResult):
2 Q) c& W' b; T" [2 V( n! e       for seq_record in SeqIO.parse(genomedata, "fasta"):) n8 @( Z& K8 s- f, G8 Z
         seqlen = len(seq_record)8 o/ ?; D) v) Y( h
         self.genomeLength += seqlen
/ W! j$ \8 p" C9 R0 S1 V          for i in range(self.N):
) I" }. H- n. l0 P/ `             # 生成断裂点
/ a. E4 L6 L" B% p# Y2 {0 X( v             breakpoint = self.generatebreakpoint(seqlen, self.averagefragmentlength)% y% D2 q" W! @3 Q. [9 g7 I6 P
            # 沿断裂点打断基因组
* k) L0 K) y; e             self.breakgenome(seq_record, breakpoint, self.minfragmentlength, self.maxfragmentlength)* U$ m4 F' S6 J% z5 P' @
      # 模拟克隆时的随机丢失情况
! [! v5 x8 h" Q4 k" K       clonedfragmentList = self.clonefragment(self.fragmentList, self.cloneRetainprobability)
& f/ U& a0 Q' ^5 a. K$ u& I       # 模拟单端测序2 h6 u# A( ~6 a3 q! i
      self.singleread(clonedfragmentList)
% O3 n8 S2 y$ }; ^4 S       SeqIO.write(self.readsList, sequencingResult, "fasta")
3 Z/ |; x: z$ d+ ]2 ~, \0 D) S9 ?
: Q! A  U7 t) i/ k8 I  n3 H def pairread(self, clonedfragmentList):* X9 H; G/ s' c) Z$ p
      for fragment in clonedfragmentList:5 T( \% ]9 i$ A0 U
         fragment.id = ""7 I" Z' b2 h# J9 o" W3 u
         fragment.name = ""( h) \- ^( ]" ~8 Q) ?8 ?
         description = fragment.description[12:].split(",")[0]
' |0 _4 v& a3 M          fragment.description = str(self.readsID) + "." + description
4 g% I5 ]$ O4 {4 X0 r          readslength = random.randint(self.minreadslength, self.maxreadslength); l* I% _' F: O! y) {
         self.allreadslength += readslength
9 i* w  k5 j6 B, W; e9 w* ~' a          self.readsList.append(fragment[:readslength])
. O1 {% I( U% W- ], B. O
8 J4 ], S6 l5 J4 H. y3 s" Q          readslength = random.randint(self.minreadslength, self.maxreadslength)
% U0 b& g( \8 V3 F" z          self.allreadslength += readslength
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         fragmentcomplement = fragment.reverse_complement()
/ k& _( u: p9 F- r1 @7 J          fragmentcomplement.id = ""& }& k: I. _' P
         fragmentcomplement.name = ""
7 z1 M6 z, q1 X3 n1 k& i          fragmentcomplement.description = str(self.readsID) + "." + description2 q* C# g* b1 q! g; Q
         self.readsList.append(fragmentcomplement[:readslength])
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         self.readsID += 1
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def pairreadsequencing(self,genomedata, sequencingResult_1, sequencingResult_2):  m$ [! p8 X3 _% n6 N
      for seq_record in SeqIO.parse(genomedata, "fasta"):6 r2 ~7 g. G  U9 X1 {+ T( y
         seqlen = len(seq_record)
+ Y$ I5 T/ J$ Z( j3 g          self.genomeLength += seqlen
& V; q* u% o  M- p8 u          for i in range(self.N):9 r, ?+ L0 h. `0 x4 `* G" V
            # 生成断裂点
8 F# ~% y6 m  o5 x' J             breakpoint = self.generatebreakpoint(seqlen, self.averagefragmentlength)
5 z1 y6 k& l/ |$ [8 w! S! p# \             # 沿断裂点打断基因组
) x& B4 O/ x2 c1 @/ u             self.breakgenome(seq_record, breakpoint, self.minfragmentlength, self.maxfragmentlength)
5 `; t. e/ a# ^0 Y2 i3 h       # 模拟克隆时的随机丢失情况, |: `5 g( U5 w3 G
      clonedfragmentList = self.clonefragment(self.fragmentList, self.cloneRetainprobability)
' Y4 e# h8 N" ~/ e2 U( {9 s       # 模拟双端测序
: U1 R" i" ?' c) X* N       self.pairread(clonedfragmentList)+ P! @  c2 H* O+ Q* c
      readsList_1 = [self.readsList for i in range(len(self.readsList)) if i % 2 == 0]# q5 X& J0 _* p
      readsList_2 = [self.readsList for i in range(len(self.readsList)) if i % 2 == 1]; I3 I9 P$ r& {: i; l; y
      SeqIO.write(readsList_1, sequencingResult_1, "fasta")+ P  I4 D$ w% B, U5 p
      SeqIO.write(readsList_2, sequencingResult_2, "fasta"). V5 K$ r3 D8 l- Q
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def resultsummary(self):
2 Z& t9 Z( Q+ B8 s, g& D# g$ t       print("基因组长度:" + str(self.genomeLength / 1000) + "kb")/ P* z; _' ]& [
      print("片段长度区间:" + str(self.minfragmentlength) + "-" + str(self.maxfragmentlength))- d* g5 ?+ A- m- N& K
      print("N值:" + str(self.N))
" R. X. ?# z8 v' X6 a       print("期望片段长度:" + str(self.averagefragmentlength))+ g6 S7 p  \4 U4 y( j( T
      print("克隆保留率:" + str(self.cloneRetainprobability))$ U+ A2 |. R( K- |  B2 M
      print("片段数量:" + str(len(self.fragmentList)))
& `7 V9 f7 T; z       print("reads长度:" + str(self.minreadslength) + "-" + str(self.maxreadslength))! C$ ]8 W) Y. d, i& ~( @
      print("reads总数量:" + str(len(self.readsList)))3 i9 G' T0 j+ \( C
      print("reads总长度:" + str(self.allreadslength / 1000) + "kb"); |# `+ H8 w6 ]' V
      m = self.allreadslength / self.genomeLength
# g+ z# Q1 `( l8 P+ Y  v       print("覆盖度(m值):" + str(round(m, 5)))- a: ]5 Z3 q$ }6 ^7 L: `& ]8 J
      print("理论丢失率(e^-m):" + str(round(exp(-m), 5)))
  l/ T- o* x! |" R* W* p       print("覆盖率(1-e^-m):" + str(round(1 - exp(-m), 5)))4 ~9 J/ b; c+ y8 g+ c# I6 P
# -------------------------------------------主程序-------------------------------------------
- `+ L9 K0 S5 L5 H4 v! _" N# 模拟单端测序! c( W) u& y( x3 b: D5 l# F
sequencingObj = Sequencing()  g" v% O$ w/ x* S0 J3 x( l
sequencingObj.singlereadsequencing("data/NC_025452.fasta", "result/virusSingleRead.fa")
5 M! n$ A% S% n% WsequencingObj.resultsummary()7 a8 u5 j) @2 H& e

5 f/ n- j1 S& W% m3 Y  W* K# 模拟双端测序  |2 K& @1 V+ s% D2 ^/ _' n! \
sequencingObj = Sequencing()3 _, h! p! h8 h( p1 n( y0 n
sequencingObj.pairreadsequencing("data/GCF_000146045.2_R64_genomic.fna", "result/yeastPairRead_1.fa", "result/yeastPairRead_2.fa")! R( Y' Z+ H6 M5 l
sequencingObj.resultsummary()/ ?( m+ I. e/ w

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