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