找到约 15 条结果

文章 基因组版本 Primary 和 Alternate的区别

...rimary assembly: a complete assembly with long stretches of phased blocks. The concept has been used by GRC. BAC-to-BAC assemblies can all be regarded as primary assemblies. Falcon-unzip is perhaps the first to produce such assemblies for whole-genome shotgun data.Alternate assembly: an incomplete ...

问题 抱歉打扰,我在做circos时遇到了下面问题,看到了您也遇到相似问题,想知道您是如何解决的,期待您的回复。

...rence/best_practices   The debugging facility is helpful to figure out what's happening under the   hood       http://www.circos.ca/documentation/tutorials/configuration/debugging   If you're still stumped, get support in the Circos Google Group.       http://groups.google.com/...

问题 vcftools过滤除了等位基因选项外,其他参数通通没用

...  13 Warning: Expected at least 2 parts in FORMAT entry: ID=PGT,Number=1,Type      14 Warning: Expected at least 2 parts in FORMAT entry: ID=PID,Number=1,Type      15 Warning: Expected at least 2 parts in FORMAT entry: ID=PL,Number=G,Type=      16 Warning: Expected at least 2 parts in F...

文章 网站编辑器代码块 高亮显示使用技巧:

...    -format => 'fasta');while ( my $seqobj = $in->next_seq() ) { # the human read-able id of the sequence my $id=$seqobj->id();  # string of sequence my $seq=$seqobj->seq(); # a description of the sequence my $desc=$seqobj->desc();  # one of 'dna','rna','protein'  https://www.bi...

文章 topGO分析结果说明

...方法。 Annotated : number of genes in go.db which are annotated with the GO-term.Significant : number of genes belonging to your input which are annotated with the GO-term.Expected : show an estimate of the number of genes a node of size Annotated would have if the significant genes were to be r...

文章 串联重复基因 tandem和segmental的区别与联系

...上,形成一个序列相似、功能相近的基因簇。According to the descriptions of Holub [1], a chromosomal region within 200 kb containing two or more genes is defined as a tandem duplication event. 3.染色体片段复制(Segmental duplication):导致复制的基因距离较远,...

文章 对组装结果中GAP左右批量设计引物

...primer3.input" or die "$!";my%ssr_pos=(); #ssr相关信息my%SSR=(); # SSR type while(my$line=){chomp $line;my@tmp=split(/\t/,$line);next if ($tmp[0] eq "ID");my$ID="$tmp[0]_$tmp[5]_$tmp[6]_$tmp[4]";$ssr_pos{$ID}="$tmp[0]\t$tmp[5]\t$tmp[6]\t$tmp[4]\t$tmp[2]";my$seq=&get_target_fa($tmp[0],$tmp[5...

文章 R语言包安装方法,设置国内镜像加快安装速度

...R终端:>install.packages("/path/to/mypackage.tar.gz", repos = NULL, type = "source")更多R语言可学习课程:R语言画图、R语言快速入门与提高

问题 GWAS筛选阈值设置

For SNPs, we set the thresholds as −log10(P value) = 6, 6, and 4 for litter size, numbers of horns and nipples, respectively. 请问,这种自选的阈值,怎么选择呢?为什么有的是6有的是4呢?

文章 TCGA挖掘高分文章

...文章标题:Clinical significance and immunogenomic landscape analyses of the immune cell signature based prognostic model for patients with breast cancer 文章标题:   Immune cell infiltration-based signature for prognosis and immunogenomic analysis in breast cancer 文章标题:  m 6 ...

文章 看懂变异记录结果文件(VCF)

... 更多参考:https://gatkforums.broadinstitute.org/gatk/discussion/1268/what-is-a-vcf-and-how-should-i-interpret-it 基因组重测序数据分析视频课程: https://bdtcd.xetslk.com/s/1VQOjQ 更多生物信息课程: 1. 文章越来越难发?是你没发现新思路,基因家...

文章 R语言-Cox比例风险模型

...相对于group one而言的,那么按照测试数据集来说:male=1,female=1,即女性的死亡风险相比男性要低 exp(coef)等于0.59,即风险比例等于0.59,说明女性(male=2)减少了0.59倍风险,女性与良好预后相关 lower .95 upper .95则是exp(coef)的95%...

文章 运行python STAMP程序报错

...g-6-9-0-31-setup.exe/download  然后按照以下方法设置:putty Other answers are outdated, or incomplete, or simply don't work.You need to also specify an X-11 server on the host machine to handle the launch of GUId programs. If the client is a Windows machine install Xming. If the client...

问题 用linux系统做gwas时运行脚本报错[Thread-9] ERROR net.maizegenetics.plugindef.AbstractPlugin - 0

...tics.plugindef.AbstractPlugin -  FileLoadPlugin Parameters format: Phenotype sortPositions: false keepDepth: true [pool-1-thread-2] INFO net.maizegenetics.plugindef.AbstractPlugin -  FileLoadPlugin Parameters format: Phenotype sortPositions: false keepDepth: true [pool-1-thread-1] IN...

文章 简单的数据处理代码

...:        self.args = args    def norm_expr(self, probe_expr_df, norm_type):        if norm_type == "raw":            return probe_expr_df        elif norm_type == "cpm":            norm_factor = probe_expr_df.sum()            return probe_expr_df * 1000000 / norm_fact...