GcatWiki - User contributions [en]

My Notes

2018-02-20T15:01:36Z

Itcuellar:

[[2/6/18]]

[[2/8/18]]

[[2/15/18]]

[[2/20/18]]

2/15/18

2018-02-15T15:54:50Z

Itcuellar: Created page with "Gene weaver: -Different tools based on graph algorithms -look for combinations of genes between sets (our genes Vs set of genes) -mapping genes across species --> rely on h..."

Gene weaver:

-Different tools based on graph algorithms
-look for combinations of genes between sets (our genes Vs set of genes)
-mapping genes across species --> rely on homology on NCBI
-data tiers- depending on source of data
Anatomy of gene set
---projects are collections of gene sets

Tier 1 is highly trusted
tier 3 ; golden ticket to access to whats in the literature

can used NOT, OR,AND booleans to filter data

High sim graph
--zoom
---right gene sets we used
---going left : nodes of various combinations
---far left: highest order of intersections

want to know if genes are really random, or is there a population of genes that have previously been associated together before

My Notes

2018-02-15T14:44:32Z

Itcuellar:

[[2/6/18]]

[[2/8/18]]

[[2/15/18]]

2/8/18

2018-02-08T15:59:49Z

Itcuellar: Created page with "Clicking on i button lets us see what parameters we entered when running test P-values: -adjuststed p-value wont work because our samples are so small -we will use regular..."

Clicking on i button lets us see what parameters we entered when running test

P-values:
-adjuststed p-value wont work because our samples are so small
-we will use regular p-value (cutoff <0.05)

Test:
-DEseq
---All C201R vs all wildtype (both male and female)
link:
[https://docs.google.com/spreadsheets/d/1aqRSoBKsdD7N9NNgYIWdH-uLPmGy_y3Wm94tVvXbLso/edit?ts=5a7c661a#gid=0
]

Today-
-sort by p value
FNTM-mouse specific
Gene cards
Gene Weaver
Go rilla
FNTM
String

minimum fold change: ~2 needed

How our data was collected: whole spinal cord

reasons why we might get genes that dont have anything to do with CMT
-non-nueronal tissue
-genes

impression:
-protein is secreted and blocking signaling
-surface protein,

reason why we don't have tighter clustering:
-receptors not completely BLOCKED, and thats part of the disease progression
-baseline genetic differences related NOT related to CMT

Itzy Cuellar

2018-02-08T14:33:14Z

Itcuellar: Replaced content with "My Notes"

[[My Notes]]

2/6/18

2018-02-08T14:32:47Z

Itcuellar: Created page with "FastQC: Quality control to see how the run went, and the quality of our data. Uses quality read information to give us an image/graph Trimmomatic: Takes of lower quality read..."

FastQC: Quality control to see how the run went, and the quality of our data. Uses quality read information to give us an image/graph

Trimmomatic: Takes of lower quality reads as well as removed adaptor sequence. Uses quality read information to chop of low quality data.

-Four lines -@identified -Bases -+ other information : has quality read information

r1- forward r2-reverse

Tophat: Aligns sequences to mamilian genome. A challenge arises because mapping needs to take place with gaps because of introns that are removed in mature RNA. Similar more updated program called HISAT2, thats faster but does the same thing as Tophat. Yeilds a BAM/SAM file. Tells where sequence aligns to gene.

Cufflinks: FPKM values Must input annotation file( gff/gtf) and tophat file. Gives number of reads. Used HTseq (a newer version).

What Dr. Campbell & Dr. TS did:

The mapping to genome (HISAT), HISeq, then DEseq2 ( where we get to do the difference between samples we choose).

My Notes

2018-02-08T14:32:43Z

Itcuellar: Created page with "2/6/18 2/8/18"

[[2/6/18]]

[[2/8/18]]

Itzy Cuellar

2018-02-08T14:32:04Z

Itcuellar:

[[My Notes]]

FastQC:
Quality control to see how the run went, and the quality of our data. Uses quality read information to give us an image/graph

Trimmomatic:
Takes of lower quality reads as well as removed adaptor sequence. Uses quality read information to chop of low quality data.

-Four lines
-@identified
-Bases
-+
other information : has quality read information

r1- forward
r2-reverse

Tophat:
Aligns sequences to mamilian genome. A challenge arises because mapping needs to take place with gaps because of introns that are removed in mature RNA. Similar more updated program called HISAT2, thats faster but does the same thing as Tophat. Yeilds a BAM/SAM file. Tells where sequence aligns to gene.

Cufflinks:
FPKM values
Must input annotation file( gff/gtf) and tophat file. Gives number of reads. Used HTseq (a newer version).

What Dr. Campbell & Dr. TS did:

The mapping to genome (HISAT), HISeq, then DEseq2 ( where we get to do the difference between samples we choose).

What does Cuffdiff do?

2018-02-06T16:01:23Z

Itcuellar:

The cutdiff function finds any significant changes in transcript expression, splicing, and promoter use (Trapnell et al., 2010). Cuttdiff is an algorithm for transcript assembly that uses a statistical model to produce estimates of isoforms (functionally similar proteins with different amino acids) abundances.

Where we compare the abundances of 2 samples and tell us which RNA reads are different. Ultimately gives us differential expression.

References:
Trapnell C. et al., 2010. Transcript assembly and quantification by RNA-Seq revels annotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 28(5):511-515. doi:10.1038/nbt.1621

What does Cuffdiff do?

2018-02-06T16:00:49Z

Itcuellar:

The cutdiff function finds any significant changes in transcript expression, splicing, and promoter use (Trapnell et al., 2010). Cuttdiff is an algorithm for transcript assembly that uses a statistical model to produce estimates of isoforms (functionally similar proteins with different amino acids) abundances.

Where we compare the abundances of 2 samples and tell us which RNA reads are different. Ultimately gives us differential expression.

what does it output?
Cufflinks

what kind of files do we need?

why would we use one over the other?
DEseq2 model varience across transcrips and works better for fewer
cuttdiff we need more replicates, not very good for lower number of replicates

References:
Trapnell C. et al., 2010. Transcript assembly and quantification by RNA-Seq revels annotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 28(5):511-515. doi:10.1038/nbt.1621

Itzy Cuellar

2018-02-06T15:47:06Z

Itcuellar:

[[Notes]]

FastQC:
Quality control to see how the run went, and the quality of our data. Uses quality read information to give us an image/graph

Trimmomatic:
Takes of lower quality reads as well as removed adaptor sequence. Uses quality read information to chop of low quality data.

-Four lines
-@identified
-Bases
-+
other information : has quality read information

r1- forward
r2-reverse

Tophat:
Aligns sequences to mamilian genome. A challenge arises because mapping needs to take place with gaps because of introns that are removed in mature RNA. Similar more updated program called HISAT2, thats faster but does the same thing as Tophat. Yeilds a BAM/SAM file. Tells where sequence aligns to gene.

Cufflinks:
FPKM values
Must input annotation file( gff/gtf) and tophat file. Gives number of reads. Used HTseq (a newer version).

What Dr. Campbell & Dr. TS did:

The mapping to genome (HISAT), HISeq, then DEseq2 ( where we get to do the difference between samples we choose).

Itzy Cuellar

2018-02-06T15:46:23Z

Itcuellar: Replaced content with "Notes"

[[Notes]]

Itzy Cuellar

2018-02-06T15:32:25Z

Itcuellar:

FastQC:
Quality control to see how the run went, and the quality of our data. Uses quality read information to give us an image/graph

Trimmomatic:
Takes of lower quality reads as well as removed adaptor sequence. Uses quality read information to chop of low quality data.

-Four lines
-@identified
-Bases
-+
other information : has quality read information

r1- forward
r2-reverse

Tophat:
Aligns sequences to mamilian genome. A challenge arises because mapping needs to take place with gaps because of introns that are removed in mature RNA. Similar more updated program called HISAT2, thats faster but does the same thing as Tophat. Yeilds a BAM/SAM file. Tells where sequence aligns to gene.

Cufflinks:
FPKM values
Must input annotation file( gff/gtf) and tophat file. Gives number of reads. Used HTseq (a newer version).

What Dr. Campbell & Dr. TS did:

The mapping to genome (HISAT), HISeq, then DEseq2 ( where we get to do the difference between samples we choose).

How is it different from DESeq2?

2018-02-06T15:28:55Z

Itcuellar:

DESeq2:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302049/
(Some direct quotes at the moment)

A method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.

'''Ideal for data sets with a small sample size due to compound comparisons within and between samples. Uses comparative means across the whole genome.'''

Data read as (Samples) vs. (Gene), or rather a matrix with reads mapped to gene in a specific sample

Mostly used for RNA seq, but also some other methods (HTS assays), such as chromatin immunoprecipitation sequencing, chromosome conformation capture, or counting observed taxa in metagenomic studies.

Improved version of DESeq (1).

How is it different from DESeq2?

2018-02-06T15:28:39Z

Itcuellar:

DESeq2:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302049/
(Some direct quotes at the moment)

A method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.

'''Ideal for data sets with a small sample size due to compound comparisons within and between samples. Uses comparative means.'''

Data read as (Samples) vs. (Gene), or rather a matrix with reads mapped to gene in a specific sample

Mostly used for RNA seq, but also some other methods (HTS assays), such as chromatin immunoprecipitation sequencing, chromosome conformation capture, or counting observed taxa in metagenomic studies.

Improved version of DESeq (1).

How is it different from DESeq2?

2018-02-06T15:26:16Z

Itcuellar:

DESeq2:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302049/
(Some direct quotes at the moment)

A method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.

'''Ideal for data sets with a small sample size due to compound comparisons within samples.'''

Data read as (Samples) vs. (Gene), or rather a matrix with reads mapped to gene in a specific sample

Mostly used for RNA seq, but also some other methods (HTS assays), such as chromatin immunoprecipitation sequencing, chromosome conformation capture, or counting observed taxa in metagenomic studies.

Improved version of DESeq (1).

How is it different from DESeq2?

2018-02-06T15:23:29Z

Itcuellar:

DESeq2:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302049/

A method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.

'''Ideal for data sets with a small sample size due to compound comparisons within samples.'''

Data read as (Samples) vs. (Gene), or rather a matrix with reads mapped to gene in a specific sample

Mostly used for RNA seq, but also some other methods (HTS assays), such as chromatin immunoprecipitation sequencing, chromosome conformation capture, or counting observed taxa in metagenomic studies.

Improved version of DESeq (1).

How is it different from DESeq2?

2018-02-06T15:21:24Z

Itcuellar:

DESeq2:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302049/

A method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.

Ideal for data sets with a small sample size due to compound comparisons within samples.

Data read as (Samples) vs. (Gene), or rather a matrix with reads mapped to gene in a specific sample

Mostly used for RNA seq, but also some other methods (HTS assays), such as chromatin immunoprecipitation sequencing, chromosome conformation capture, or counting observed taxa in metagenomic studies.

Improved version of DESeq (1).

How is it different from DESeq2?

2018-02-06T15:21:00Z

Itcuellar: Created page with "DESeq2: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302049/ - A method for differential analysis of count data, using shrinkage estimation for dispersions and fold change..."

DESeq2:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302049/

- A method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
- Ideal for data sets with a small sample size due to compound comparisons within samples.
- Data read as (Samples) vs. (Gene), or rather a matrix with reads mapped to gene in a specific sample
- Mostly used for RNA seq, but also some other methods (HTS assays), such as chromatin immunoprecipitation sequencing, chromosome conformation capture, or counting observed taxa in metagenomic studies.
- Improved version of DESeq (1).

What does Cuffdiff do?

2018-02-06T14:46:51Z

Itcuellar: Created page with "The cutdiff function finds any significant changes in transcript expression, splicing, and promoter use."

The cutdiff function finds any significant changes in transcript expression, splicing, and promoter use.

Jonah and Itzy

2018-02-06T14:43:13Z

Itcuellar:

[[What does Cuffdiff do?]]

[[How is it different from DESeq2?]]

Itzy Cuellar

2018-02-06T14:38:49Z

Itcuellar: Created page with "."