Week 9 - Gene Expression part 2

Question 1

Methods for Whole genome gene expression analysis

Answer 1

Microarray
RNA - Seq

Question 2

Microarray - principles

Answer 2

mRNA extracted from cells
cDNA produced and fluorescently labelled
cDNA is hybridized to chip
Intensity of fluorescence indicates relative amounts of mRNA

Question 3

RNA-sequencing 2 methods

Answer 3

1. Sequence all products and align reads to reference genome sequence
2. Align reads to all other sequence reads, read depth relates to abundance of transcript

Both give genome wide determination of gene expression, used for mRNA but can be used on RNA rRNA snRNA

Question 4

Pre-processing steps for RNA-seq

Answer 4

1. remove adaptor sequences
2. generate read counts for each gene with Read mapping or Quasi mapping

Question 5

RNA-seq: Quantification by sequencing

Answer 5

1. Sample of interest
2. Isolate RNA
   3 .Make cDNA
3. sequence ends
4. Map to genome
5. Downstream analysis

Question 6

Differences between Microarray and RNA-seq

Answer 6

Microarray: Explore changes in expression of known transcripts
Dynamic range - 44 fold
Simple data analysis - <1GB

RNA-Seq: explore expression changes in known transcripts and find novel ones
Dynamic range 9,560 fold
Complex data analysis - >5GB

Question 7

Steps for analysis of transcriptomic data analysis

Answer 7

1. Quality control (happens at multiple stages)
2. Data pre-processing
3. Differential gene analysis
4. Clustering
5. Network analysis

Question 8

What is normalization of gene expression data

Answer 8

It is a process that adjusts expression data so that a series of values are on a common scale, this allows for comparisons across samples

must have similar levels of expression otherwise normalization distorts biological differences.

Question 9

Normalization methods and packages for Microarray and RNA-seq

Answer 9

RNA-Seq:
M - Total count
P - edgeR

Microarray:
M - Global
P - MAS5