10、RNA-seq for DE analysis training(Mapping to assign reads to genes)
1、Goal of mapping
1)We want to assign reads to genes they were derived from
2)The result of the mapping will be used to construct a summary of the counts: the count table.
2 、不同情况 in RNA-seq
1)Reference genome sequenceavailable
2)NO reference genome sequence available
De novo assembly of the reads (trinity transcriptome construction)
Map the reads to the assembly (RSEM mapper)
Extract count table (note:no removal of polyA is required. Computationally expensive!)
3、Reads mapped to reference genome
1、比对过程中主要点
1)Reference is haplotype: mixture of alleles, leads to mismatches.
相比较而言:多倍体个体在进行比对时错配的概率要大。
2)Reads contain sequencing errors「
reads在测序仪测bases时出错,本身存在bases的错误。
3)Reads derived from mRNA, genome is DNA
4、visualize SAM or aBAM
The outcome of the alignment is a SAM or a BAM format, which you can visualize in Galaxy (or with a stand-alone viewer such as GenomeView or IGV.
Galaxy https://www.galaxyproject.org/ stand-double
GenomeView stand-alone
IGV stand-alone
5、Mapping QC
RseQC http://rseqc.sourceforge.net/ After checking the mapping visually, determine more metrics with RseQC
BAMQC http://qualimap.bioinfo.cipf.es/ mainly useful for DNA-seq
exeicise: http://wiki.bits.vib.be/index.php/RNA-Seq_analysis_for_differential_expression#Mapping_processed_data
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