教程
- griffithlab/rnaseq_tutorial
- WSBIM2122
- DGE_workshop_salmon_online
- Transcriptome Assembly, Functional Annotation
- Recommended Coverage and Read Depth for NGS Applications
测试数据
六例两组样本+spike-in
这里测试数据是mapping到22号染色体的reads，物种是Human。
数据来源：https://github.com/griffithlab/rnaseq_tutorial/wiki/RNAseq-Data
可选的数据下载地址：https://gitee.com/bioinfoFungi/testData/tree/master/RNA-seq
- UHR + ERCC Spike-In Mix1, Replicate 1
- UHR + ERCC Spike-In Mix1, Replicate 2
- UHR + ERCC Spike-In Mix1, Replicate 3
- HBR + ERCC Spike-In Mix2, Replicate 1
- HBR + ERCC Spike-In Mix2, Replicate 2
- HBR + ERCC Spike-In Mix2, Replicate 3
UHR是从10种不同的癌细胞系中分离的总RNA。HBR是从23名不同年龄但大多为60-80岁的白种人（男性和女性）的大脑中分离出的总RNA。ERCC ExFold RNA Spike-In Control Mixes被添加到每个样本中。Mix1被添加到UHR样品中，Mix2被添加到HBR样品中。我们还为每个样本进行了3次完整的实验复制
The spike-in consists of 92 transcripts that are present in known concentrations across a wide abundance range (from very few copies to many copies). This range allows us to test the degree to which the RNA-seq assay (including all laboratory and analysis steps) accurately reflects the relative abundance of transcript species within a sample.
包含chr22和 ERCC transcript的 fasta 文件
- chr22_with_ERCC92.fa
gzip -dc chr22_with_ERCC92.fa.gz > chr22_with_ERCC92.fa
chr22和 ERCC 的注释文件
- chr22_with_ERCC92.gtf
gzip -dc chr22_with_ERCC92.gtf.gz > chr22_with_ERCC92.gtf
4种不同条件下生长的粟酒裂殖酵母
RNA-Seq 数据包括在对数生长(Sp _ log)、平台期(Sp _ plat)、热休克(Sp _ hs)和双功能移位(Sp _ ds)4种不同条件下生长的粟酒裂殖酵母(Schizosaccharoymyces pombe,fission yeast)对应的配对末端76碱基链特异性 Illumina RNA-Seq reads。
数据来源: https://github.com/trinityrnaseq/RNASeq_Trinity_Tuxedo_Workshop/wiki
数据下载：https://github.com/trinityrnaseq/RNASeq_Trinity_Tuxedo_Workshop/tree/master/RNASEQ_data
https://gitee.com/bioinfoFungi/rna-seq
图片alt
RNA sequencing: the teenage years
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RNA-Seq differential expression analysis: An extended review and a software tool
RNA-Seq相关技术
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Coupling mRNA processing with transcription in time and space
5'加帽 Capping
可变剪切
可变ployA尾
RNA编辑
- FASTQ->BAM->Call SNP(筛选A->G)
- Call SNP:WGS、WES的GATK流程
转录起始位点鉴定
- GRO-Seq
- NET-Seq
- SLAM-Seq
翻译效率
- Ribosome footprint
RNA二级结构的测定(RNA-RNA Interaction)
PARS、SHAPE-Seq\SHAPE-MaP
相当于RNA-RNA的Interaction，测定DNA-DNA Interaction 的技术为Hi-C
RNA结合蛋白位点预测
- CLIP-Seq 鉴定RNA结合蛋白位点预测
- CHIP-Seq 鉴定DNA的结合蛋白
比对软件时间线
- 2009年 Tophat
- 2012年 STAR
- 2013年 Tophat2
- 2015年 HISAT
- 2019年 HISAT2
参考
https://bioincloud.tech/cloudir/reports/transcriptome/%E7%BB%93%E9%A2%98%E6%8A%A5%E5%91%8A.html#a3.1