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社区首页 >专栏 >生信技能树-R初级作业-1

生信技能树-R初级作业-1

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素素
发布于 2023-05-19 08:24:08
4010
发布于 2023-05-19 08:24:08
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文章被收录于专栏：生信课程note＋实验知识生信课程note＋实验知识
title: "R-all"

author: "susu"

date: "2023-05-18"

output: html_document

R Markdown

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#1.当前工作目录是什么路径。
getwd()
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## [1] "D:/desktop/sxjns h/zuoye chuji"
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#2.新建6个向量，基于不同的原子类型。（重点是字符串，数值，逻辑值）
#原子类型包括向量，列表，矩阵，数组，因子，数据帧。
a=c(1,2,3,4,5)#数值型向量
a
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## [1] 1 2 3 4 5
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b=c("a","b","c")#字符型向量
b
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## [1] "a" "b" "c"
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c=c(TRUE,TRUE,FALSE)#逻辑型向量
c
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## [1]  TRUE  TRUE FALSE
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v4=3L
v4
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## [1] 3
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##创建整数型向量
v5=2i+1 #复数向量
v5
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## [1] 1+2i
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#创建字符串向量
d=c("good night")
d
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## [1] "good night"
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#3.新建一些数据结构，比如矩阵，数组，数据框，列表等,重点是数据框，矩阵。
#矩阵 
m1=matrix(1:9,nrow=9)
m1
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##       [,1]
##  [1,]    1
##  [2,]    2
##  [3,]    3
##  [4,]    4
##  [5,]    5
##  [6,]    6
##  [7,]    7
##  [8,]    8
##  [9,]    9
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#数组
m2=array(1:24,c(2,3,4))
m2
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## , , 1
## 
##      [,1] [,2] [,3]
## [1,]    1    3    5
## [2,]    2    4    6
## 
## , , 2
## 
##      [,1] [,2] [,3]
## [1,]    7    9   11
## [2,]    8   10   12
## 
## , , 3
## 
##      [,1] [,2] [,3]
## [1,]   13   15   17
## [2,]   14   16   18
## 
## , , 4
## 
##      [,1] [,2] [,3]
## [1,]   19   21   23
## [2,]   20   22   24
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#数据框
m3=data.frame(a=c(1:10),b=paste("q",c(1:10),sep="."),c=1:10>3)#sep是以  分割
m3
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##     a    b     c
## 1   1  q.1 FALSE
## 2   2  q.2 FALSE
## 3   3  q.3 FALSE
## 4   4  q.4  TRUE
## 5   5  q.5  TRUE
## 6   6  q.6  TRUE
## 7   7  q.7  TRUE
## 8   8  q.8  TRUE
## 9   9  q.9  TRUE
## 10 10 q.10  TRUE
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#列表
m4=list(m1,m2,m3)
m4
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## [[1]]
##       [,1]
##  [1,]    1
##  [2,]    2
##  [3,]    3
##  [4,]    4
##  [5,]    5
##  [6,]    6
##  [7,]    7
##  [8,]    8
##  [9,]    9
## 
## [[2]]
## , , 1
## 
##      [,1] [,2] [,3]
## [1,]    1    3    5
## [2,]    2    4    6
## 
## , , 2
## 
##      [,1] [,2] [,3]
## [1,]    7    9   11
## [2,]    8   10   12
## 
## , , 3
## 
##      [,1] [,2] [,3]
## [1,]   13   15   17
## [2,]   14   16   18
## 
## , , 4
## 
##      [,1] [,2] [,3]
## [1,]   19   21   23
## [2,]   20   22   24
## 
## 
## [[3]]
##     a    b     c
## 1   1  q.1 FALSE
## 2   2  q.2 FALSE
## 3   3  q.3 FALSE
## 4   4  q.4  TRUE
## 5   5  q.5  TRUE
## 6   6  q.6  TRUE
## 7   7  q.7  TRUE
## 8   8  q.8  TRUE
## 9   9  q.9  TRUE
## 10 10 q.10  TRUE
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#4.在你新建的数据框进行切片操作，比如首先取第1，3行， 然后取第4，6列。
m5=m3[c(1,3),]
m5
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##   a   b     c
## 1 1 q.1 FALSE
## 3 3 q.3 FALSE
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m3$d=c(2:11)
m3
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##     a    b     c  d
## 1   1  q.1 FALSE  2
## 2   2  q.2 FALSE  3
## 3   3  q.3 FALSE  4
## 4   4  q.4  TRUE  5
## 5   5  q.5  TRUE  6
## 6   6  q.6  TRUE  7
## 7   7  q.7  TRUE  8
## 8   8  q.8  TRUE  9
## 9   9  q.9  TRUE 10
## 10 10 q.10  TRUE 11
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m3$e=c(3:12)
m3
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##     a    b     c  d  e
## 1   1  q.1 FALSE  2  3
## 2   2  q.2 FALSE  3  4
## 3   3  q.3 FALSE  4  5
## 4   4  q.4  TRUE  5  6
## 5   5  q.5  TRUE  6  7
## 6   6  q.6  TRUE  7  8
## 7   7  q.7  TRUE  8  9
## 8   8  q.8  TRUE  9 10
## 9   9  q.9  TRUE 10 11
## 10 10 q.10  TRUE 11 12
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m3$f=c(4:13)
m3
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##     a    b     c  d  e  f
## 1   1  q.1 FALSE  2  3  4
## 2   2  q.2 FALSE  3  4  5
## 3   3  q.3 FALSE  4  5  6
## 4   4  q.4  TRUE  5  6  7
## 5   5  q.5  TRUE  6  7  8
## 6   6  q.6  TRUE  7  8  9
## 7   7  q.7  TRUE  8  9 10
## 8   8  q.8  TRUE  9 10 11
## 9   9  q.9  TRUE 10 11 12
## 10 10 q.10  TRUE 11 12 13
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m6=m3[,c(4,6)]
m6
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##     d  f
## 1   2  4
## 2   3  5
## 3   4  6
## 4   5  7
## 5   6  8
## 6   7  9
## 7   8 10
## 8   9 11
## 9  10 12
## 10 11 13
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#5.使用data函数来加载R内置数据集 rivers，并描述它。
data(rivers)
rivers
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##   [1]  735  320  325  392  524  450 1459  135  465  600  330  336  280  315  870  906  202
##  [18]  329  290 1000  600  505 1450  840 1243  890  350  407  286  280  525  720  390  250
##  [35]  327  230  265  850  210  630  260  230  360  730  600  306  390  420  291  710  340
##  [52]  217  281  352  259  250  470  680  570  350  300  560  900  625  332 2348 1171 3710
##  [69] 2315 2533  780  280  410  460  260  255  431  350  760  618  338  981 1306  500  696
##  [86]  605  250  411 1054  735  233  435  490  310  460  383  375 1270  545  445 1885  380
## [103]  300  380  377  425  276  210  800  420  350  360  538 1100 1205  314  237  610  360
## [120]  540 1038  424  310  300  444  301  268  620  215  652  900  525  246  360  529  500
## [137]  720  270  430  671 1770
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head(rivers)
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## [1] 735 320 325 392 524 450
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tail(rivers)
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## [1]  500  720  270  430  671 1770
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str(rivers)
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##  num [1:141] 735 320 325 392 524 ...
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plot(rivers)
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length(rivers)
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## [1] 141
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#6.下载 https://www.ncbi.nlm.nih.gov/sra?term=SRP133642 里面的 RunInfo Table文件读入到R里面，了解这个数据框，多少列，每一列都是什么属性的元素。（参考B站生信小技巧获取runinfo table）
SraRunTable <- read.table("http://www.bio-info-trainee.com/tmp/5years/SraRunTable.txt",fill=TRUE,header = T,sep = "\t")
dim(SraRunTable)
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## [1] 768  31
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colnames(SraRunTable)
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##  [1] "BioSample"          "Experiment"         "MBases"             "MBytes"            
##  [5] "Run"                "SRA_Sample"         "Sample_Name"        "Assay_Type"        
##  [9] "AssemblyName"       "AvgSpotLen"         "BioProject"         "Center_Name"       
## [13] "Consent"            "DATASTORE_filetype" "DATASTORE_provider" "InsertSize"        
## [17] "Instrument"         "LibraryLayout"      "LibrarySelection"   "LibrarySource"     
## [21] "LoadDate"           "Organism"           "Platform"           "ReleaseDate"       
## [25] "SRA_Study"          "age"                "cell_type"          "marker_genes"      
## [29] "source_name"        "strain"             "tissue"
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class(colnames(SraRunTable))
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## [1] "character"
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class(SraRunTable)
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## [1] "data.frame"
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str(SraRunTable)
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## 'data.frame':	768 obs. of  31 variables:
##  $ BioSample         : chr  "SAMN08619912" "SAMN08619911" "SAMN08619910" "SAMN08619909" ...
##  $ Experiment        : chr  "SRX3749902" "SRX3749903" "SRX3749904" "SRX3749905" ...
##  $ MBases            : int  16 16 8 8 11 7 18 5 11 15 ...
##  $ MBytes            : int  8 8 4 4 5 4 9 3 6 8 ...
##  $ Run               : chr  "SRR6790711" "SRR6790712" "SRR6790713" "SRR6790714" ...
##  $ SRA_Sample        : chr  "SRS3006138" "SRS3006148" "SRS3006137" "SRS3006136" ...
##  $ Sample_Name       : chr  "GSM3025845" "GSM3025846" "GSM3025847" "GSM3025848" ...
##  $ Assay_Type        : chr  "RNA-Seq" "RNA-Seq" "RNA-Seq" "RNA-Seq" ...
##  $ AssemblyName      : chr  "GCF_000001635.20" "GCF_000001635.20" "GCF_000001635.20" "GCF_000001635.20" ...
##  $ AvgSpotLen        : int  43 43 43 43 43 43 43 43 43 43 ...
##  $ BioProject        : chr  "PRJNA436229" "PRJNA436229" "PRJNA436229" "PRJNA436229" ...
##  $ Center_Name       : chr  "GEO" "GEO" "GEO" "GEO" ...
##  $ Consent           : chr  "public" "public" "public" "public" ...
##  $ DATASTORE_filetype: chr  "sra" "sra" "sra" "sra" ...
##  $ DATASTORE_provider: chr  "ncbi" "ncbi" "ncbi" "ncbi" ...
##  $ InsertSize        : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ Instrument        : chr  "Illumina HiSeq 2000" "Illumina HiSeq 2000" "Illumina HiSeq 2000" "Illumina HiSeq 2000" ...
##  $ LibraryLayout     : chr  "SINGLE" "SINGLE" "SINGLE" "SINGLE" ...
##  $ LibrarySelection  : chr  "cDNA" "cDNA" "cDNA" "cDNA" ...
##  $ LibrarySource     : chr  "TRANSCRIPTOMIC" "TRANSCRIPTOMIC" "TRANSCRIPTOMIC" "TRANSCRIPTOMIC" ...
##  $ LoadDate          : chr  "2018-03-01" "2018-03-01" "2018-03-01" "2018-03-01" ...
##  $ Organism          : chr  "Mus musculus" "Mus musculus" "Mus musculus" "Mus musculus" ...
##  $ Platform          : chr  "ILLUMINA" "ILLUMINA" "ILLUMINA" "ILLUMINA" ...
##  $ ReleaseDate       : chr  "2018-11-23" "2018-11-23" "2018-11-23" "2018-11-23" ...
##  $ SRA_Study         : chr  "SRP133642" "SRP133642" "SRP133642" "SRP133642" ...
##  $ age               : chr  "14 weeks" "14 weeks" "14 weeks" "14 weeks" ...
##  $ cell_type         : chr  "cancer-associated fibroblasts (CAFs)" "cancer-associated fibroblasts (CAFs)" "cancer-associated fibroblasts (CAFs)" "cancer-associated fibroblasts (CAFs)" ...
##  $ marker_genes      : chr  "EpCAM-, CD45-, CD31-, NG2-" "EpCAM-, CD45-, CD31-, NG2-" "EpCAM-, CD45-, CD31-, NG2-" "EpCAM-, CD45-, CD31-, NG2-" ...
##  $ source_name       : chr  "Mammary tumor fibroblast" "Mammary tumor fibroblast" "Mammary tumor fibroblast" "Mammary tumor fibroblast" ...
##  $ strain            : chr  "FVB/N-Tg(MMTVPyVT)634Mul/J" "FVB/N-Tg(MMTVPyVT)634Mul/J" "FVB/N-Tg(MMTVPyVT)634Mul/J" "FVB/N-Tg(MMTVPyVT)634Mul/J" ...
##  $ tissue            : chr  "Mammary tumor fibroblast" "Mammary tumor fibroblast" "Mammary tumor fibroblast" "Mammary tumor fibroblast" ...
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sapply(SraRunTable,mode)
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##          BioSample         Experiment             MBases             MBytes 
##        "character"        "character"          "numeric"          "numeric" 
##                Run         SRA_Sample        Sample_Name         Assay_Type 
##        "character"        "character"        "character"        "character" 
##       AssemblyName         AvgSpotLen         BioProject        Center_Name 
##        "character"          "numeric"        "character"        "character" 
##            Consent DATASTORE_filetype DATASTORE_provider         InsertSize 
##        "character"        "character"        "character"          "numeric" 
##         Instrument      LibraryLayout   LibrarySelection      LibrarySource 
##        "character"        "character"        "character"        "character" 
##           LoadDate           Organism           Platform        ReleaseDate 
##        "character"        "character"        "character"        "character" 
##          SRA_Study                age          cell_type       marker_genes 
##        "character"        "character"        "character"        "character" 
##        source_name             strain             tissue 
##        "character"        "character"        "character"
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#7.下载 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE111229 里面的样本信息sample.csv读入到R里面，了解这个数据框，多少列，每一列都是什么属性的元素。
sample <- read.csv('sample.csv')
class(sample)
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## [1] "data.frame"
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dim(sample)
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## [1] 768  12
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str(sample)
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## 'data.frame':	768 obs. of  12 variables:
##  $ Accession          : chr  "GSM3025845" "GSM3025846" "GSM3025847" "GSM3025848" ...
##  $ Title              : chr  "SS2_15_0048_A1" "SS2_15_0048_A2" "SS2_15_0048_A3" "SS2_15_0048_A4" ...
##  $ Sample.Type        : chr  "SRA" "SRA" "SRA" "SRA" ...
##  $ Taxonomy           : chr  "Mus musculus" "Mus musculus" "Mus musculus" "Mus musculus" ...
##  $ Channels           : int  1 1 1 1 1 1 1 1 1 1 ...
##  $ Platform           : chr  "GPL13112" "GPL13112" "GPL13112" "GPL13112" ...
##  $ Series             : chr  "GSE111229" "GSE111229" "GSE111229" "GSE111229" ...
##  $ Supplementary.Types: chr  "SRA Run Selector" "SRA Run Selector" "SRA Run Selector" "SRA Run Selector" ...
##  $ Supplementary.Links: chr  "https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749902" "https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749903" "https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749904" "https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749905" ...
##  $ SRA.Accession      : chr  "SRX3749902" "SRX3749903" "SRX3749904" "SRX3749905" ...
##  $ Contact            : chr  "Kristian Pietras" "Kristian Pietras" "Kristian Pietras" "Kristian Pietras" ...
##  $ Release.Date       : chr  "Nov 23, 2018" "Nov 23, 2018" "Nov 23, 2018" "Nov 23, 2018" ...
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#8.把前面两个步骤的两个表（RunInfo Table 文件，样本信息sample.csv）关联起来，使用merge函数。
merge=merge(sample,SraRunTable,by.x = "Accession",by.y = "Sample_Name")
merge
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##     Accession           Title Sample.Type     Taxonomy Channels Platform.x    Series
## 1  GSM3025845  SS2_15_0048_A1         SRA Mus musculus        1   GPL13112 GSE111229
## 2  GSM3025846  SS2_15_0048_A2         SRA Mus musculus        1   GPL13112 GSE111229
## 3  GSM3025847  SS2_15_0048_A3         SRA Mus musculus        1   GPL13112 GSE111229
## 4  GSM3025848  SS2_15_0048_A4         SRA Mus musculus        1   GPL13112 GSE111229
## 5  GSM3025849  SS2_15_0048_A5         SRA Mus musculus        1   GPL13112 GSE111229
## 6  GSM3025850  SS2_15_0048_A6         SRA Mus musculus        1   GPL13112 GSE111229
## 7  GSM3025851  SS2_15_0048_A7         SRA Mus musculus        1   GPL13112 GSE111229
## 8  GSM3025852  SS2_15_0048_A8         SRA Mus musculus        1   GPL13112 GSE111229
## 9  GSM3025853  SS2_15_0048_A9         SRA Mus musculus        1   GPL13112 GSE111229
## 10 GSM3025854 SS2_15_0048_A10         SRA Mus musculus        1   GPL13112 GSE111229
## 11 GSM3025855 SS2_15_0048_A11         SRA Mus musculus        1   GPL13112 GSE111229
## 12 GSM3025856 SS2_15_0048_A12         SRA Mus musculus        1   GPL13112 GSE111229
## 13 GSM3025857 SS2_15_0048_A13         SRA Mus musculus        1   GPL13112 GSE111229
## 14 GSM3025858 SS2_15_0048_A14         SRA Mus musculus        1   GPL13112 GSE111229
## 15 GSM3025859 SS2_15_0048_A15         SRA Mus musculus        1   GPL13112 GSE111229
## 16 GSM3025860 SS2_15_0048_A16         SRA Mus musculus        1   GPL13112 GSE111229
## 17 GSM3025861 SS2_15_0048_A17         SRA Mus musculus        1   GPL13112 GSE111229
## 18 GSM3025862 SS2_15_0048_A18         SRA Mus musculus        1   GPL13112 GSE111229
## 19 GSM3025863 SS2_15_0048_A19         SRA Mus musculus        1   GPL13112 GSE111229
## 20 GSM3025864 SS2_15_0048_A20         SRA Mus musculus        1   GPL13112 GSE111229
## 21 GSM3025865 SS2_15_0048_A21         SRA Mus musculus        1   GPL13112 GSE111229
## 22 GSM3025866 SS2_15_0048_A22         SRA Mus musculus        1   GPL13112 GSE111229
## 23 GSM3025867 SS2_15_0048_A23         SRA Mus musculus        1   GPL13112 GSE111229
##    Supplementary.Types                                       Supplementary.Links
## 1     SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749902
## 2     SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749903
## 3     SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749904
## 4     SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749905
## 5     SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749906
## 6     SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749907
## 7     SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749908
## 8     SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749909
## 9     SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749910
## 10    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749901
## 11    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749911
## 12    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749912
## 13    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749913
## 14    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749914
## 15    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749915
## 16    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749916
## 17    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749917
## 18    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749918
## 19    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749919
## 20    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749920
## 21    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749921
## 22    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749922
## 23    SRA Run Selector https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRX3749923
##    SRA.Accession          Contact Release.Date    BioSample Experiment MBases MBytes
## 1     SRX3749902 Kristian Pietras Nov 23, 2018 SAMN08619912 SRX3749902     16      8
## 2     SRX3749903 Kristian Pietras Nov 23, 2018 SAMN08619911 SRX3749903     16      8
## 3     SRX3749904 Kristian Pietras Nov 23, 2018 SAMN08619910 SRX3749904      8      4
## 4     SRX3749905 Kristian Pietras Nov 23, 2018 SAMN08619909 SRX3749905      8      4
## 5     SRX3749906 Kristian Pietras Nov 23, 2018 SAMN08619908 SRX3749906     11      5
## 6     SRX3749907 Kristian Pietras Nov 23, 2018 SAMN08619919 SRX3749907      7      4
## 7     SRX3749908 Kristian Pietras Nov 23, 2018 SAMN08619918 SRX3749908     18      9
## 8     SRX3749909 Kristian Pietras Nov 23, 2018 SAMN08619921 SRX3749909      5      3
## 9     SRX3749910 Kristian Pietras Nov 23, 2018 SAMN08619920 SRX3749910     11      6
## 10    SRX3749901 Kristian Pietras Nov 23, 2018 SAMN08619914 SRX3749901     15      8
## 11    SRX3749911 Kristian Pietras Nov 23, 2018 SAMN08619913 SRX3749911     14      7
## 12    SRX3749912 Kristian Pietras Nov 23, 2018 SAMN08619922 SRX3749912     14      7
## 13    SRX3749913 Kristian Pietras Nov 23, 2018 SAMN08619928 SRX3749913     14      7
## 14    SRX3749914 Kristian Pietras Nov 23, 2018 SAMN08619927 SRX3749914     13      7
## 15    SRX3749915 Kristian Pietras Nov 23, 2018 SAMN08619926 SRX3749915     15      7
## 16    SRX3749916 Kristian Pietras Nov 23, 2018 SAMN08619925 SRX3749916     13      7
## 17    SRX3749917 Kristian Pietras Nov 23, 2018 SAMN08619917 SRX3749917      5      3
## 18    SRX3749918 Kristian Pietras Nov 23, 2018 SAMN08619916 SRX3749918     13      7
## 19    SRX3749919 Kristian Pietras Nov 23, 2018 SAMN08619915 SRX3749919     20     10
## 20    SRX3749920 Kristian Pietras Nov 23, 2018 SAMN08619924 SRX3749920     12      6
## 21    SRX3749921 Kristian Pietras Nov 23, 2018 SAMN08619923 SRX3749921     15      8
## 22    SRX3749922 Kristian Pietras Nov 23, 2018 SAMN08622126 SRX3749922     13      6
## 23    SRX3749923 Kristian Pietras Nov 23, 2018 SAMN08622125 SRX3749923      2      1
##           Run SRA_Sample Assay_Type     AssemblyName AvgSpotLen  BioProject Center_Name
## 1  SRR6790711 SRS3006138    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 2  SRR6790712 SRS3006148    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 3  SRR6790713 SRS3006137    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 4  SRR6790714 SRS3006136    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 5  SRR6790715 SRS3006149    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 6  SRR6790716 SRS3006140    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 7  SRR6790717 SRS3006150    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 8  SRR6790718 SRS3006142    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 9  SRR6790719 SRS3006141    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 10 SRR6790720 SRS3006139    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 11 SRR6790721 SRS3006151    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 12 SRR6790722 SRS3006143    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 13 SRR6790723 SRS3006152    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 14 SRR6790724 SRS3006153    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 15 SRR6790725 SRS3006154    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 16 SRR6790726 SRS3006144    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 17 SRR6790727 SRS3006155    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 18 SRR6790728 SRS3006145    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 19 SRR6790729 SRS3006146    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 20 SRR6790730 SRS3006147    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 21 SRR6790731 SRS3006156    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 22 SRR6790732 SRS3007304    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
## 23 SRR6790733 SRS3007303    RNA-Seq GCF_000001635.20         43 PRJNA436229         GEO
##    Consent DATASTORE_filetype DATASTORE_provider InsertSize          Instrument
## 1   public                sra               ncbi          0 Illumina HiSeq 2000
## 2   public                sra               ncbi          0 Illumina HiSeq 2000
## 3   public                sra               ncbi          0 Illumina HiSeq 2000
## 4   public                sra               ncbi          0 Illumina HiSeq 2000
## 5   public                sra               ncbi          0 Illumina HiSeq 2000
## 6   public                sra               ncbi          0 Illumina HiSeq 2000
## 7   public                sra               ncbi          0 Illumina HiSeq 2000
## 8   public                sra               ncbi          0 Illumina HiSeq 2000
## 9   public                sra               ncbi          0 Illumina HiSeq 2000
## 10  public                sra               ncbi          0 Illumina HiSeq 2000
## 11  public                sra               ncbi          0 Illumina HiSeq 2000
## 12  public                sra               ncbi          0 Illumina HiSeq 2000
## 13  public                sra               ncbi          0 Illumina HiSeq 2000
## 14  public                sra               ncbi          0 Illumina HiSeq 2000
## 15  public                sra               ncbi          0 Illumina HiSeq 2000
## 16  public                sra               ncbi          0 Illumina HiSeq 2000
## 17  public                sra               ncbi          0 Illumina HiSeq 2000
## 18  public                sra               ncbi          0 Illumina HiSeq 2000
## 19  public                sra               ncbi          0 Illumina HiSeq 2000
## 20  public                sra               ncbi          0 Illumina HiSeq 2000
## 21  public                sra               ncbi          0 Illumina HiSeq 2000
## 22  public                sra               ncbi          0 Illumina HiSeq 2000
## 23  public                sra               ncbi          0 Illumina HiSeq 2000
##    LibraryLayout LibrarySelection  LibrarySource   LoadDate     Organism Platform.y
## 1         SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 2         SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 3         SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 4         SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 5         SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 6         SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 7         SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 8         SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 9         SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 10        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 11        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 12        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 13        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 14        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 15        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 16        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 17        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 18        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 19        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 20        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 21        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 22        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
## 23        SINGLE             cDNA TRANSCRIPTOMIC 2018-03-01 Mus musculus   ILLUMINA
##    ReleaseDate SRA_Study      age                            cell_type
## 1   2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 2   2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 3   2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 4   2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 5   2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 6   2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 7   2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 8   2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 9   2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 10  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 11  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 12  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 13  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 14  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 15  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 16  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 17  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 18  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 19  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 20  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 21  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 22  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
## 23  2018-11-23 SRP133642 14 weeks cancer-associated fibroblasts (CAFs)
##                  marker_genes              source_name                     strain
## 1  EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 2  EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 3  EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 4  EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 5  EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 6  EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 7  EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 8  EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 9  EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 10 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 11 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 12 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 13 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 14 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 15 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 16 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 17 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 18 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 19 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 20 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 21 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 22 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
## 23 EpCAM-, CD45-, CD31-, NG2- Mammary tumor fibroblast FVB/N-Tg(MMTVPyVT)634Mul/J
##                      tissue
## 1  Mammary tumor fibroblast
## 2  Mammary tumor fibroblast
## 3  Mammary tumor fibroblast
## 4  Mammary tumor fibroblast
## 5  Mammary tumor fibroblast
## 6  Mammary tumor fibroblast
## 7  Mammary tumor fibroblast
## 8  Mammary tumor fibroblast
## 9  Mammary tumor fibroblast
## 10 Mammary tumor fibroblast
## 11 Mammary tumor fibroblast
## 12 Mammary tumor fibroblast
## 13 Mammary tumor fibroblast
## 14 Mammary tumor fibroblast
## 15 Mammary tumor fibroblast
## 16 Mammary tumor fibroblast
## 17 Mammary tumor fibroblast
## 18 Mammary tumor fibroblast
## 19 Mammary tumor fibroblast
## 20 Mammary tumor fibroblast
## 21 Mammary tumor fibroblast
## 22 Mammary tumor fibroblast
## 23 Mammary tumor fibroblast
##  [ reached 'max' / getOption("max.print") -- omitted 745 rows ]
代码语言：text
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dim(merge)
代码语言：txt
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## [1] 768  42
代码语言：text
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#9.对前面读取的 RunInfo Table 文件在R里面探索其MBases列，包括箱线图(boxplot)和五分位数(fivenum)，还有频数图(hist)，以及密度图(density) 。
data=SraRunTable$MBases
data
代码语言：txt
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##   [1] 16 16  8  8 11  7 18  5 11 15 14 14 14 13 15 13  5 13 20 12 15 13  2 18 13  8 18  7  8
##  [30]  5 12  6  8 11  8 12 13  9  5 14  7  9  9  4 12 12 13 12 54 12 12  3 12 13 15 12 13  9
##  [59] 19 13 20 16 12 22 11 14 20 13 14 14 14 18 16 12 18  9 12 16 17 16  8  9 16 16 17 11  6
##  [88] 15 12  8 14  3 15 13  8 27 18  4 19  2 10  7 18 16 20 20 12 18 20  9 16 20 14 17 24  5
## [117] 10 17 14 15 10 12 21 11 16  7 17  9 17 18 16 19 13 11 11 16 10 13 17 12 23 19 17 22 21
## [146] 13 23 13  4 15 31 11 20 28 26 19 18 14 10 21  8 16 22 11 15 24 15 24  9 16 15 16 16 14
## [175] 21 11 19 19 15 21 13 13 11 20  3 16 19 14 20 20 25 15 11 13 12  8 15 13 15  9 17 14 19
## [204] 16 19 17 12 16  7 16 16  8 12 14 13  4 15 11 19  8 19 10  8 11 11 12 19 17 16  7 12 19
## [233] 13 13 16 10 17 18 15  4 20 20 15  7 19  7 25 10 20 14 23  9 19 16 16 14 15 16 11  4  6
## [262] 14 16  6 13  6 11  9 11  5 13 11  7 12 10  9  5  9  4  8  5  9  6 16  7 11  9  2 14 10
## [291] 19 11 18 15 26 18 20 22 15 18 22 11 14 13 13 17 15 13 24 16 10  3 15 16  5 10 10 11 19
## [320]  6 13 24 15 10  5  7  6 14 12  6 14 12 12 19 15  3  4  4  5  8 11 16  8  7 18 19  8 16
## [349]  7 15 12 11 11 15 19  7 10 13  4  5 11  7  7  9 13  9  9  8  6  8 16  9 11  2  5  6  9
## [378] 10 10  7 14  6 10  4  1  4  9  5 11  7 14  5  4 15 15 17 17  9 10 10 11 10 14  0 16 14
## [407]  9 12  8  6 13  2 14  9 11  2  6  4 12 11 10  8  4  7  7 10 14  8 11 15 11  8  6  7 17
## [436]  6 14 18 21 11 14 23  9 21 13 11 12 20 11 14 17 12 16 19  8  5 11  7 16 10 13 16 20 10
## [465] 18 16  4 17 13  7  7 14 10  8 15  5 17  9  7 14 16 15 20  1 19 18 16 14 25 20 25 19 20
## [494] 12 14 19  4  3 16  3 16 25  9 17  6 11 15  8  6  6 19  8 16  8 16 18 19  6  9 14  9 11
## [523] 18 12 17 21 15 16 17 13 22 16 13 19 18 14 26 23 24 27 23 10 12 11 16 16 19 13 23 22 11
## [552] 19  9 15 19  4 17  7 24 12 25 18 20 19 13  8 12 17 14  7 20 12 20 18 22 21 12 13 10  6
## [581] 13 13  9  2 14 17 11 15  7  4  9 14  7  7 12  8 19 17 14  3  7  9 18  9 13  3 18  5 21
## [610]  8  4 16 18 14  9 14 10 13 13 13 20 19 15  4 12  6 12  2  2  8  7  6 22 19 15 18 20 13
## [639]  5 24 17 74 12 10 16  6  4  1  5  5 13  8  9  2 12  6 17  7 10  9 11  8  2  7  6  6  6
## [668] 13  4 16  2  1  5 17 20  5  5 14 10 10 25 24 21 12  8 13 12 61 14 36 10  4  9 13 16  3
## [697] 10 13 11  2  8 12 10  3  2  7 14 11 11  5  7  6  4  7  9  1  2 11 11  2 17 13 14  6 15
## [726]  3  7 10 19 15 11 10  4 14  9 15 10 12 12  9 16 16 11  4  2 10 11  2  4  6 13  4 11 14
## [755] 10  9 13  3  4 10 10 11 14  2 11 15 11  3
代码语言：text
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#箱线图
library(ggplot2)
library(reshape2)
library(ggsignif)
boxplot(data)
代码语言：text
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fivenum(data)
代码语言：txt
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## [1]  0  8 12 16 74
代码语言：text
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hist(data)
代码语言：text
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density(data)
代码语言：txt
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## 
## Call:
## 	density.default(x = data)
## 
## Data: data (768 obs.);	Bandwidth 'bw' = 1.423
## 
##        x                y            
##  Min.   :-4.269   Min.   :0.0000000  
##  1st Qu.:16.366   1st Qu.:0.0000353  
##  Median :37.000   Median :0.0003001  
##  Mean   :37.000   Mean   :0.0121039  
##  3rd Qu.:57.634   3rd Qu.:0.0142453  
##  Max.   :78.269   Max.   :0.0665647
代码语言：text
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plot(density(data,na.rm=T))

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原创声明：本文系作者授权腾讯云开发者社区发表，未经许可，不得转载。

如有侵权，请联系 cloudcommunity@tencent.com 删除。

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