recount3超大规模可用转录组数据集

随着测序数据的积累，如何复用这些数据是一个挑战。recount项目，目前是recount3，共收集了8,679人和10,088小鼠的数据集，超过750,000个样本，经过统一处理（uniformly processed），得到gene或exon的表达以及exon-exon junction的数据。好多年前，我就了解过recount项目，很奇怪很少有介绍的。

一，recount对所有属于进行了uniformly processed，避免了分析流程的bias；

二，recount提供了超大规模的预处理之后的数据，直接拿来用，避免研究人员从原始数据分析；

三，recount提供了简单易用的工具，方便研究人员下载和处理数据。

方法1：下载TCGA-OV为例，检索过滤然后下载

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library(recount3)

# 同 https://jhubiostatistics.shinyapps.io/recount3-study-explorer/
# 可以看到project_home和project，包括TCGA,GTEX和SRA
human_projects <- available_projects()

proj_info <- subset(
  human_projects,
  project == "OV" & project_type == "data_sources"
)

rse_gene_tcga_ov <- create_rse(proj_info)

#counts data
assays(rse_gene_tcga_ov)$counts <- transform_counts(rse_gene_tcga_ov)
# ## Compute TPMs
assays(rse_gene_tcga_ov)$TPM <- recount::getTPM(rse_gene_tcga_ov, length_var = "score")
# ## Check TPM. Should all be equal to 1
colSums(assay(rse_gene_tcga_ov, "TPM")) / 1e6 


# View sample annotation
View(data.frame(colData(rse_gene_tcga_ov)))

# View gene annotation
View(data.frame(exp$tcga.ov.expr@rowRanges))

方法2：直接选中数据集，生成下载code

在这个网站选中想要下载的数据集，https://jhubiostatistics.shinyapps.io/recount3-study-explorer/，网站下方会显示下载的code。注释不一定是26，还可以是RefSeq v109，Gencode v29等。

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rse_gene_tcga_ov = recount3::create_rse_manual(
    project = "OV",
    project_home = "data_sources/tcga",
    organism = "human",
    annotation = "gencode_v26",
    type = "gene"
)

#counts data
assays(rse_gene_tcga_ov)$counts <- transform_counts(rse_gene_tcga_ov)
# ## Compute TPMs
assays(rse_gene_tcga_ov)$TPM <- recount::getTPM(rse_gene_tcga_ov, length_var = "score")
# ## Check TPM. Should all be equal to 1
colSums(assay(rse_gene_tcga_ov, "TPM")) / 1e6

下载exon-exon junction数据：

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rse_jxn_tcga_ov = recount3::create_rse_manual(
    project = "OV",
    project_home = "data_sources/tcga",
    organism = "human",
    annotation = "gencode_v26",
    type = "jxn"
)

但好像大陆有些不能访问，下载不了。

参考：

https://www.bioconductor.org/packages/devel/bioc/vignettes/recount3/inst/doc/recount3-quickstart.html

https://rna.recount.bio/

https://rna.recount.bio/docs/bioconductor.html#recount3

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#Author: Jason

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