Tonon: Lecture II

Question 1

What is RNA-Seq?

Answer 1

it is the sequencing of RNA using technology

Question 2

What are the advantages of using Oxford Nanopore and Pacific Biosciences vs Illumina?

Answer 2

Pacific and Oxford offer better length, which is essential to detect phenomena such as alternative splicing, which leads to variables

Question 3

What are some disadvantages of Pacific and Oxford?

Answer 3

high error rate
high quality RNA is needed
lower throughput, which is needed for heterogenous cancer samples

Question 4

What do Illumina and microarrays focus on?

Answer 4

poly-A tail structure

Question 5

Is it better to have 50 million single hand or 25 double strand sequences?

Answer 5

the 50 million because it is important to have as many sequences as possible to ensure you have even low expressed genes

Question 6

After sequencing, what are the steps?

Answer 6

obtain FASTQ file from instrument
align unknown genome
assemble
quantification
normalization
model of differential expression is obtained

Question 7

How long do you have to analyze data?

Answer 7

depends but there is an expiration

Question 8

Biological Replicate

Answer 8

biological are done with different cell types

Question 9

Technical Repliate

Answer 9

same cell type, repeated

Question 10

Biological Replicates vs Technical Replicates

Answer 10

biological is more important

Question 11

What has been introduced to minimize bias?

Answer 11

Standarized Operational Procedures (SOPs)

Question 12

When analyzing data for large experiments, what can be done to minimize bias?

Answer 12

we can orthogonalize variables to prevent bias from being introduced (seen in batched)

Question 13

What is normalization?

Answer 13

removes background and non-biological variation as much as possible

Question 14

What are the 2 key assumptions normalization relies on?

Answer 14

expression levels of most genes remain the same across replicate groups

different sample groups do not exhibit a meaningful difference in overall mRNA levels

Question 15

How do we normalize data from RNA-seq?

Answer 15

we use all the genes in the expression to do

normalisation, we calculate the average amount, so we know the average expression level and then

we bring it down to the same level

Question 16

What is MYC?

Answer 16

gene expressed most cancers?

Question 17

How does MYC work?

Answer 17

MYC affects only specific targets, so we can normalize the data and report all genes 1 to 1 among other cells

low MYC → quiescent cells
increased MYC → selective gene regulation

proliferating cells with increased MYC have a lot of RNA but the MYC targets are few

Question 18

What are the 2 steps to filtering?

Answer 18

identify and remove a set of genes that seem to generate an uninformative signal

statistical testing only to genes that pass the filter

Question 19

What is the goal of filtering?

Answer 19

for true-differential expression to emerge and silence the non-informative

Question 20

What is the importance of Filtering on Overall Variance?

Answer 20

all samples (healthy and cancerous: without labels) are filtered

all genes that have low expression are removed…this leads to less genes with higher signifigance