RNA数据不支持VQSR,使用FS > 30.0 & QD < 2.0,GATK建议过滤掉在35bp范围内出现3个以上的SNP的情况(-window 35 -cluster 3)推荐命令 /home/software/gatk-4.1.4.0/gatk VariantFiltration -R /home/sheep-reference/GCF_002742125.1_Oar_rambouillet_v1.0_genomic.fna \ -V combined.genotype.snp.vcf \ -O c...
GATK是一个很全面的工具,不仅可以做DNA-seq的数据分析,也可以用来做RNA-seq的数据分析,此为用GATK做RNA-seq的数据分析(snps 和indels)。 1.mapping to the reference. 其中这一步不是用GATK的命令来做,但是GATK有推荐做RNA-seq的软件,GATK推荐的是STAR,为什么选择这个,作者说的很清楚,因为它提高了sensitivity,...
对RNA-seq 产出的数据进行变异检测分析,与常规重测序的主要区别就在序列比对这一步,因为 RNA-seq 的数据是来自转录本的,比对到参考基因组需要跨越转录剪切位点,所以 RNA-seq 进行变异检测的重点就在于跨剪切位点的精确序列比对。 文献systematic evaluation of spliced alignment programs for RNA-seq data中对 RNA-s...
RNA-seq和转录元件(transcriptionfactor,TF)染色质免疫沉淀测序(ChIPseq)数据的组合可用于去除ChIPseq分析中的假阳性并且表明TF对其目标基因的激活或抑制作用。例如,BETA将差异表达基因与来自ChIP-seq称为TF目标。其他RNA-ChIP测序综合方法在中进行了描述:将来自FAIRE-seq和DNase-seq的开放染色质数据与RNA-seq验证基因的...
如果有读者仔细看过RNA-seq结题报告,就会发现在定量分析以外通常还会有SNP和INDEL分析。目前,对人类测序数据找突变最常用的软件是GATK,除了速度慢以外,没有其他明显缺点(可以通过部署Spark提高速度;当然,如果有钱,可以购买Sentieon,快了15-20倍)。 和WES不同,RNA-seq对于外显子区域的覆盖度极度不均一,并且由于其数...
How to call genetic variants from Iso-Seq data using our pipeline To illustrate how to call variants from Iso-Seq data using our pipeline, we use as input a small public Iso-Seq BAM that contains full-length non-concatemer reads, which can be downloadedhere. ...
Large compendia of gene expression data have proven valuable for the discovery of novel biological relationships. Historically, most available RNA assays were run on microarray, while RNA-seq is now the platform of choice for many new experiments. The da
RNA-seq 生物学重复相关性验证 根据拿到的表达矩阵设为exprSet 1、用scale 进行标准化 数据中心化:数据集中的各个数字减去数据集的均值 数据标准化:中心化之后的数据在除以数据集的标准差。 在R中利用scale方法来对数据进行中心化和标准化 1scale(data, center=T, scale=F)23其中,center为T,表示数据中心化45...
The rapidly growing plant RNA-Seq databases call for the assessment of the alignment tools on curated plant data, which will aid the calibration of these tools for applications to plant transcriptomic data. We therefore focused here on benchmarking RNA-Seq read alignment tools, using simulated ...
(Fig.1a). This accuracy is in line with what was reported from bulk cell RNA-seq25. The false positive rate is consistently <0.1, and the median reaches below 0.05 when the read depth is >6 (Fig.1b). We compared the SNV call results from GATK to those from another SNV caller ...