RNA-‐seq  Gene  Expression  Analysis  

Tzu  L.  Phang  Ph.D.  Robert  Stearman  Ph.D.  Michael  Edwards  Ph.D.  

University  of  Colorado  Denver  2014  AACR  Workshop,  Snowmass  CO  

What  is  gene  expression?  

“Gene  expression  is  the  process  by  which  informaSon  from  a  gene  is  used  in  the  synthesis  of  a  funcSonal  gene  product”  

The Central Dogma

Transcriptome Proteomic

Agenda  

•  Import  BAM  file  •  What  is  Next  GeneraSon  Sequencing  (NGS)?  •  NGS  Usages:  RNA-‐seq  and  ChIP-‐seq  •  NGS  File  Format  and  Size  •  Mapping  Phred  Quality  Score  •  Demo:  Using  SeqMonk  for  RNA-‐seq  and  ChIP-‐seq  Analysis  

Installing  SeqMonk  

h]p://www.bioinformaScs.babraham.ac.uk/projects/seqmonk/  

SeqMonk:  First  Look  

List  Panel  

Chromosome  Panel  

Track  Panel  

Quick  Assess  Panel  

Sample  BAM  Files  •  ABC_DHL2.bam  •  ABC_Ly10.bam  •  ABC_Ly3.bam  •  ABC_U2932.bam  •  GCB_DHL10.bam  •  GCB_DHL4.bam  •  GCB_DHL6.bam  •  GCB_Ly7.bam  •  STAT3  ChIPSeq  Genes.txt  

Import  BAM  files  

Next  GeneraSon  Sequencing  

h]p://www.youtube.com/watch?v=77r5p8IBwJk  

How RNA-seq works

Figure  from  Wang  et.  al,  RNA-‐Seq:  a  revolu=onary  tool  for  transcriptomics,  Nat.  Rev.  GeneScs  10,  57-‐63,  2009).  

Next  generaSon  sequencing  (NGS)  

Sample  preparaSon  

How ChIP-seq works

File  System  

unknown:5:1:2:836#0/1:CATACAAGTTGTTTGTACTATAGNTGTTTTTGAATT:aabaaaa^abaaba^_]_aaaXPD\^_aaa`Y]_aa!unknown:5:1:2:717#0/1:TCTGTTCCAGATTCTAAGGGCATNGTCTTTTTGAAT:aa^]]`\_^[Y_`^aZP^VZV[SDLZ^aa__^^\Ya!unknown:5:1:2:188#0/1:TAAGAAGAAAGATGCATAGGTACNATATTTTTGAAT:a``Z[^Y^`\\\^[\^][WNTWNDS_[^_^^[OWY_!unknown:5:1:2:1262#0/1:CACTTACAAACAAGGAATGTTGGNCGGTTTTTGAAT:a`ababaabaaaa_``aa``_ULDXZ_^aaa`O_aa!unknown:5:1:2:1046#0/1:CTAAGATGGCCTAAGAGTAGACTNACTTTTTTGAAT:abb`Xa`Z_aabaaa`]__Z^`\D\`aaaaaa^aab!

!

@ILLUMINA-‐545855_0001:4:100:743:1210#0  TAACATGTGTCATATGTCCCAGGATGTC  +ILLUMINA-‐545855_0001:4:100:743:1210#0  ab^aaaa_a_aaaa`a^abaaaa``a_a  

Data Structure

FASTQ format

Quality  Control  of  sequences  

•  The  quality  scores  are  the  only  measure  of  confidence  

•  QualiSes  usually  fall  with  length  where  trimming  is  needed  to  remove  

Phred  QualiSes  

•  Developed  by  Phil  Green’s  group  at  the  University  of  Washington  in  the  1990’s  

•  AutomaScally  processes  sequence  chromatogram  files  – Reports  sequence  and  associated  qualiSes  –  Introduced  concept  of  phred  quality  values  

James  H.  Thomas,  University  of  Washington  

James  H.  Thomas,  University  of  Washington  

FASTQ  QC  VisualizaSon  Per  base  sequence  quality  

h]p://www.bioinformaScs.babraham.ac.uk/projects/fastqc/  

Our  Dataset  

RNA-‐seq  Analysis  Workflow  

From  FASTQ  to  SAM/BAM  

galaxyproject.org  

h]ps://usegalaxy.org  

File  Format  

SCARF

FASTQ

SAM

BAM

VCF

GTF

BED WIG

Single-End

Paired-End

PILEUP

Mapping

Input for Visualization

Tools

QC Visualization

5.2 GB

3.3 GB

4.5 GB

696 MB

NOW  A  DEMONSTRATION  

Arer  BAM  Import  

RNA-‐seq  Analysis  Workflow  

Define  Probes  &  QuanStaSon  

RNA-‐seq  Analysis  Workflow  

Why  normalizaSon?  

•  Remove systematic errors introduced in labeling, hybridization and scanning procedures

•  Correct these errors while preserve biological variability / information

A  different  look  …  Technical  rep

licate  diffe

rence  

Average  Intensity  Values  

To  normalize  or  not  to  …  

ChIP-‐seq  Analysis  Strategy  

ChIP-‐seq  Analysis  Caveats  

ChIP-‐seq  Analysis  Workflow