RNA样品分三个批次使用Illumina HiSeq 2000进行测序,得到长为100碱基对的单端序列片段。 本文所描述的分析假设从RNA-seq实验获得的序列片段已经与适当的参考基因组比对,并已经在基因水平上对序列进行了统计计数。在本文条件下,使用Rsubread包提供的基于R的流程将序列片段与小鼠参考基因组(mm10)比对(具体而言,先使用ali...
# 安装并加载所需的R包# BiocManager::install("dittoSeq")library(dittoSeq)library(dplyr)load("sce.Rdata")# 加载自己的单细胞数据dittoPlot(sce,"MS4A1",# 感兴趣的基因group.by="orig.ident",# 讲将细胞/样本分组的选项 plots=c("vlnplot","boxplot"),# 设置绘图类型,包括:jitter,boxplot,vlnplot,...
对于RNA-seq计数数据而言,原始计数或log-CPM值的方差并不独立于均值(Law et al. 2014)。有些差异表达分析方法使用负二项分布模型,假设均值与方差间具有二次的关系。而在limma中,假设log-CPM值符合正态分布,因此我们在对RNA-seq的log-CPM值进行线性建模时,需要使用voom函数计算每个基因的权重从而调整均值与方差的...
The RNA-seq dataset was originally collected as part of a comparative study of transcriptional responses to limb regeneration in three ambystomatid salamander species25, one with a reference genome (Ambystomatidae mexicanum, abbreviation MEX) and two without (Ambystomatidae andersoni, abbreviation AND;...
(B) Density plots of intron rate for lncRNA and protein-coding genes. (C) Relationship between intron rate and intron length. (D) Relationship between intron rate and the number of introns in a gene. The intron rate was calculated as follows. First, the number of reads mapped to intronic...
D Density plots of cancer cell correlation within samples for treated and untreated groups. E Gene set enrichment analysis of overall cancer cells, treated and untreated. Full size image To identify cell states, we used GSEA to check for common gene expression patterns of cancer cells in each ...
Density plots with the average cutoff estimates.The averaged cutoff estimates of DAFS, Mclust, Sen0.85, Sen0.90, and Sen0.95for simulated(a)log2 raw counts and(b)log2 RPKM data were presented. The black lines are empirical densities of the data. The black vertical lines present the DAFS cut...
In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers requi...
对象数据中变量之间的相互关系可以通过DensityScatter()函数来直观展示。此外,设置quantiles=TRUE选项,可以帮助我们迅速确定不同质量控制指标的适宜阈值。 DensityScatter(pbmc, x = 'nCount_ATAC', y = 'TSS.enrichment', log_x = TRUE, quantiles = TRUE) ...
#Starting from the output of the RNA-seq Tutorial Part 1. #Load libraries library(ggplot2) library(gplots) library(GenomicRanges) library(ballgown) #If X11 not available, open a pdf device for output of all plots pdf(file="Tutorial_Part3_Supplementary_R_output.pdf") ...