Docker封装生物信息学circRNA流程
2020-11-06 本文已影响0人
儒雅随和王小板
circRNA分析主要流程模块:
图片.pngcircRNA主要作用机制
(1) 能够通过miRNA sponge方式作为一种内源性竞争RNA(ceRNA)参与转录后调控。
(2) 核内circRNA能够结合Pol II 复合物或者与启动子相互作用,调控转录过程。
(3) mRNA 前体的可变剪接由于介入环化的外显子,导致基因表达的改变。
(4) circRNA能够直接与蛋白互作形成特定的circRNP,通过改变构象影响蛋白功能。
(5) circRNA在特定的条件下具有编码能力,且翻译的蛋白具有生物意义。
(6) circRNA逆转录能够驱动假基因的形成。
(7) 由于特殊的拓扑结果,植物circRNA能够通过维管长距离传递信息。
(8) 虽然circRNA的表达丰度并不高,但是能够富集在某些组织如大脑、神经细胞中发挥功能。
1.构建镜像
docker镜像基于lncRNA基础
docker run -itd --name circ_rna lnc:v1
docker exec -it 00d50983a98e /bin/bash
首先拷贝数据库与脚本 质控--整理样本数据到一个目录 使用miARma1.7.2 软件进行后续分析
软件下载地址:miARma1.7.2, 大小60M左右
测试数据下载地址:Examples,大小在700M左右
注意R的版本,否则会报错:
运行方式:
/data/xczhang/sRNA-pipeline/software/miARma1.7.2/miARma miARma_circRNAs_pipeline.ini
miARma_circRNAs_pipeline.ini 内容:
;General parameters
[General]
; type of analysis (miRNA, mRNA or circRNA)
type=circRNA
;0 for no verbose, otherwise to print "almost" everything verbose=almost
; Folder for miRNA reads
read_dir=/data/xczhang/sRNA-pipeline/project/circRNAseq/Rawdata/
; Number of process to run at the same time
threads=4
; label for the analsysis label=Asthma
; Folder where miARma has been instaled
miARmaPath=/data/xczhang/sRNA-pipeline/software/miARma1.7.2
; Folder to store results
output_dir=/data/xczhang/sRNA-pipeline/project/circRNAseq/
; organism used
organism=human
;Type of sequencing ; could be Paired or Single. [Single by default]
seqtype=Paired
#Whether the data is from a strand-specific assay (yes, no or reverse, yes by default) for featureCounts analysis
strand=no
stats_file=/data/xczhang/sRNA-pipeline/project/circRNAseq/miARma_stat.75582.log
logfile=/data/xczhang/sRNA-pipeline/project/circRNAseq/miARma_logfile.75582.log
[Aligner]
; Aligner (BWA for circRNAs)
aligner=bwa
; Path of the genomic fasta sequence to build the index
;Name to write in the index files
bwaindex=/data/xczhang/sRNA-pipeline/databases/genome/BWA_index/Homo_sapiens.GRCh37.75.dna.toplevel.fa
[ReadCount]
;Specific software to perform the Differential Expression Analysis (Allowed values: edger, noiseq or edger-noiseq)
desoft=Noiseq-EdgeR
;Complete path of the target file.
targetfile=/data/xczhang/sRNA-pipeline/project/circRNAseq/targets.txt
;Path of the contrast file.
contrastfile=/data/xczhang/sRNA-pipeline/project/circRNAseq/contrast.txt
;This value refers to filter processing in the reads (Should be "yes" or "no").
filter=no
;anser yes if replicates samples are included
replicates=yes
;Provide a file with normalized reads
cpm=yes
运行结束
图片.png
整理生成结果文件
软件自带生成图片比较难看,可以根据需求自行画图。
后续GO与KEGG分析方法较多,正在测试中。