R语言 SRAdb包 SRAdb-package()函数中文帮助文档(中英文对照)

loveR

SRAdb-package(SRAdb)
SRAdb-package()所属R语言包：SRAdb

                                        Query NCBI SRA metadata within R or from a local SQLite database
                                         查询NCBI的储备金帐户内R或从本地SQLite数据库的元数据

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

The Sequence Read Archive (SRA) represents largest public repository of sequencing data from the next generation of sequencing platforms including Roche 454 GS System, Illumina Genome Analyzer, Applied Biosystems SOLiD System, Helicos Heliscope, and others. However, finding data of interest can be challenging using current tools. SRAdb is an attempt to make access to the metadata associated with submission, study, sample, experiment and run much more feasible. This is accomplished by parsing all the NCBI SRA metadata into a SQLite database that can be stored and queried locally. SRAdb is simply a thin wrapper around the SQLite database along with associated tools and documentation. Fulltext search in the package make querying metadata very flexible and powerful.  SRA data files (sra or sra-lite) can be downloaded for doing alignment locally. Available BAM files in local or in the Meltzerlab sraDB can be loaded into IGV for visualization easily. The SQLite database is updated regularly as new data is added to SRA and can be downloaded at will for the most up-to-date metadata.
读取存档（SRA）的序列代表的测序平台，包括罗氏454 GS系统，Illumina的Genome Analyzer的应用生物系统公司的SOLiD系统，Helicos Heliscope，和其他下一代测序数据的最大的公共仓库。然而，寻找感兴趣的数据可以挑战，利用现有的工具。 SRAdb是企图使提交的研究中，样品，实验相关的元数据的访问和运行更加可行。这是通过NCBI的储备金帐户元数据解析成一个SQLite数据库，可以存储和查询本地。 SRAdb围绕SQLite数据库是一个简单的瘦包装以及相关的工具和文档。包在全文搜索查询元数据非常灵活和强大。特别储备金帐户的数据文件（SRA或SRA-Lite的）可以下载做对齐本地。可用的BAM文件在本地或在Meltzerlab sraDB可以加载可视化很容易进入IGV的。 SQLite数据库的定期更新新的数据添加到SRA和可以随意下载的最先进的最新的元数据。


Details

详情----------Details----------


作者（S）----------Author(s)----------



Jack Zhu and Sean Davis

Maintainer: Jack Zhu <zhujack@mail.nih.gov>




参考文献----------References----------



举例----------Examples----------


if(file.exists('SRAmetadb.sqlite')) {
  
  library(SRAdb)
  sra_dbname <- 'SRAmetadb.sqlite'       
  sra_con <- dbConnect(dbDriver("SQLite"), sra_dbname)
  
  ## Get column descriptions[＃获取列的说明。]
  a <- colDescriptions(sra_con=sra_con)[1:5,]
  
  ## Convert SRA experiment accessions to other types[＃储备金帐户实验加入其他类型的转换]
  b <- sraConvert( in_acc=c(" SRR000137", "SRR000138 "), out_type=c('sample'), sra_con=sra_con )
  
  ## Fulltext search SRA meta data using SQLite fts3 module[＃全文搜索储备金帐户的元数据，使用SQLite fts3模块]
  rs <- getSRA (search_terms ='breas* NEAR/2 can*', out_types=c('run','study'), sra_con=sra_con)
  rs <- getSRA (search_terms ='breast', out_types=c('run','study'), sra_con=sra_con)
  rs <- getSRA (search_terms ='"breas* can*"', out_types=c('study'), sra_con=sra_con)
  rs <- getSRA (search_terms ='MCF7 OR "MCF-7"', out_types=c('sample'), sra_con=sra_con)
  rs <- getSRA (search_terms ='study_title: brea* can*', out_types=c('run','study'), sra_con=sra_con)  
  rs <- getSRA (search_terms ='study_title: brea* can*', out_types=c('run','study'), sra_con=sra_con, acc_only=TRUE)

  ## List sra-lite data files associated with each input SRA accessions[＃列出SRA-Lite的数据与每个输入储备金帐户加入相关的文件]
  ## Not run: [＃无法运行：]
          listSRAfile (in_acc=c("SRX000089"), sra_con=sra_con, sraType='litesra')
       
## End(Not run)[＃结束（不运行）]
  ## Get file size and date from NCBI ftp site for available sra-lite data files associated with input SRA accessions[＃从NCBI ftp站点获取输入储备金帐户加入相关的SRA-Lite的可用数据文件的文件大小和日期]
        ## Not run:   [＃无法运行：]
        getSRAinfo (in_acc=c("SRS012041","SRS000290"), sra_con=sra_con, sraType='litesra')
       
## End(Not run)[＃结束（不运行）]
          ## Download sra-lite data files associated with input SRA accessions from NCBI SRA ftp site [＃下载SRA-Lite的数据输入储备金帐户加入从NCBI储备金帐户的FTP站点的相关文件。]
        ## Not run: [＃无法运行：]
          getSRAfile (in_acc=c("SRR000648","SRR000657"), sra_con=sra_con, destdir=getwd(), sraType='litesra')
       
## End(Not run)[＃结束（不运行）]
  ## Start IGV from R if no IGV running[从R＃启动IGV的运行，如果没有IGV的]
## Not run: startIGV(memory='mm')[＃无法运行：startIGV（内存=毫米）]

  ## load BAM files to IGV[＃加载的BAM文件IGV的]
  ## Not run: [＃无法运行：]
  exampleBams = file.path(system.file('extdata',package='SRAdb'), dir(system.file('extdata',package='SRAdb'),pattern='bam$'))
  sock <- IGVsocket()
  IGVload(sock,exampleBams)
  
## End(Not run)[＃结束（不运行）]
  ## Change the IGV genome[＃更改IGV的基因。]
  ## Not run: [＃无法运行：]
  IGVgenome(sock,genome='hg18')
  
## End(Not run)[＃结束（不运行）]
  ## Go to a specified region in IGV[＃转到了IGV的指定区域]
  ## Not run: [＃无法运行：]
  IGVgoto(sock,'chr1:1-10000')
  IGVgoto(sock,'TP53')
  
## End(Not run)[＃结束（不运行）]

  ## Make a snapshot of the current IGV window[＃IGV的当前窗口的快照]
  ## Not run:   [＃无法运行：]
  IGVsnapshot(sock)
  dir()
  
## End(Not run)[＃结束（不运行）]
  
  ## create a graphNEL object from SRA accessions, which are full text search results of terms 'colon cancer'[＃创建一个“搜索结果graphNEL的对象从特别储备金帐户的加入，这是完整的文字条款结肠癌]
  g <- sraGraph('colon cancer', sra_con)
  
  ## Not run: [＃无法运行：]
  library(Rgraphviz)
  attrs <- getDefaultAttrs(list(node=list(fillcolor='lightblue', shape='ellipse')))
  plot(g, attrs=attrs)
  
## End(Not run)[＃结束（不运行）]
  
  dbDisconnect(sra_con)

} else {
  print("use getSRAdbFile() to get a copy of the SRAmetadb.sqlite file
and then rerun the example")
}

转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。