• Create data frame called Annotation with a column of gene names ("Gene_1", "Gene_2", "Gene_3","Gene_4","Gene_5"), ensembl gene names ("Ens001", "Ens003", "Ens006", "Ens007", "Ens010"), pathway information ("Glycolysis", "TGFb", "Glycolysis", "TGFb", "Glycolysis") and gene lengths (100, 3000, 200, 1000,1200). • Create data frame called Sample1 with ensembl gene names ("Ens001", "Ens003", "Ens006", "Ens010") and expression (1000, 3000, 10000,5000) Create data frame called Sample2 with ensembl gene names ("Ens001", "Ens003", "Ens006", "Ens007", "Ens010") and expression (1500, 1500, 17000,500,10000) • Create a data frame containing only those gene names common to all data frames with all information from Annotation and the expression from Sample 1 and Sample 2. ensembl geneNames pathway geneLengths expression.x expression.y 1 Ens001 Gene 1 Glycolysis Ens003 Gene 2 TGFb 2 3 Ens006 Gene 3 Glycolysis 4 Ens010 Gene 5 Glycolysis • Add an extra two columns containing the length normalised expressions for Sample 1 and Sample 2 ensembl geneNames pathway geneLengths expression.x expression.y 1 En 001 #2 Ens003 Ens006 Gene 1 Glycolysis Gene 2 TGFb Gene 3 Glycolysis EN5010 Gene 5 Glycolysis Sample1 Ine Sample2 Ine 3 4 10.000000 15.000000 1.000000 0.500000 50.000000 85.000000 4.166667 8.333333 100 3000 200 1200 100 3000 200 1200 1000 3000 10000 5000 Gene S 1.0000000 1000 3000 10000 5000 • Identify the total length of genes in Glycolysis pathway. [1] 1500 1500 1500 17000 10000 Identify the mean length normalised expression across Sample 1 and Sample2 for Ens006 genes [1] 67.5 1500 1500 17000 10000 For all genes, identify the log2 fold change in length normalised expression from Sample 1 to Sample 2. Gene 3 Gene 1 Gene 2 0.5849625 -1.0000000 0.7655347
• Create data frame called Annotation with a column of gene names ("Gene_1", "Gene_2", "Gene_3","Gene_4","Gene_5"), ensembl gene names ("Ens001", "Ens003", "Ens006", "Ens007", "Ens010"), pathway information ("Glycolysis", "TGFb", "Glycolysis", "TGFb", "Glycolysis") and gene lengths (100, 3000, 200, 1000,1200). • Create data frame called Sample1 with ensembl gene names ("Ens001", "Ens003", "Ens006", "Ens010") and expression (1000, 3000, 10000,5000) Create data frame called Sample2 with ensembl gene names ("Ens001", "Ens003", "Ens006", "Ens007", "Ens010") and expression (1500, 1500, 17000,500,10000) • Create a data frame containing only those gene names common to all data frames with all information from Annotation and the expression from Sample 1 and Sample 2. ensembl geneNames pathway geneLengths expression.x expression.y 1 Ens001 Gene 1 Glycolysis Ens003 Gene 2 TGFb 2 3 Ens006 Gene 3 Glycolysis 4 Ens010 Gene 5 Glycolysis • Add an extra two columns containing the length normalised expressions for Sample 1 and Sample 2 ensembl geneNames pathway geneLengths expression.x expression.y 1 En 001 #2 Ens003 Ens006 Gene 1 Glycolysis Gene 2 TGFb Gene 3 Glycolysis EN5010 Gene 5 Glycolysis Sample1 Ine Sample2 Ine 3 4 10.000000 15.000000 1.000000 0.500000 50.000000 85.000000 4.166667 8.333333 100 3000 200 1200 100 3000 200 1200 1000 3000 10000 5000 Gene S 1.0000000 1000 3000 10000 5000 • Identify the total length of genes in Glycolysis pathway. [1] 1500 1500 1500 17000 10000 Identify the mean length normalised expression across Sample 1 and Sample2 for Ens006 genes [1] 67.5 1500 1500 17000 10000 For all genes, identify the log2 fold change in length normalised expression from Sample 1 to Sample 2. Gene 3 Gene 1 Gene 2 0.5849625 -1.0000000 0.7655347
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
Related questions
Question
By using R language do the following:
![• Create data frame called Annotation with a column of gene names ("Gene_1", "Gene_2",
"Gene_3","Gene_4","Gene_5"), ensembl gene names ("Ens001", "Ens003", "Ens006", "Ens007", "Ens010"),
pathway information ("Glycolysis", "TGFb", "Glycolysis", "TGFb", "Glycolysis") and gene lengths (100, 3000, 200,
1000,1200).
• Create data frame called Sample1 with ensembl gene names ("Ens001", "Ens003", "Ens006", "Ens010") and
expression (1000, 3000, 10000,5000)
• Create data frame called Sample2 with ensembl gene names ("Ens001", "Ens003", "Ens006",
"Ens007", "Ens010") and expression (1500, 1500, 17000,500,10000)
• Create a data frame containing only those gene names common to all data frames with all information from
Annotation and the expression from Sample 1 and Sample 2.
ensembl geneNames pathway geneLengths expression.x expression.y
## 1 Ens881
## 2 Ens883
Ens886
## 3
## 4 Ens010
##
##
## 2 Ens003
## 3 Ens006
##4
##
## 1
## 2
## 3
## 4
• Add an extra two columns containing the length normalised expressions for Sample 1 and Sample 2
ensembl geneNames pathway geneLengths expression.x expression.y
##1 Ens001
Gene 1 Glycolysis
Gene_2
TGFb
Gene 3 Glycolysis
Ens010 Gene 5 Glycolysis
Sample1 Ine Sample2_1ne
15.000000
8.500000
85.000000
8.333333
18.000000
1.000000
##
Gene_1 Glycolysis
Gene_2
TGFb
Gene 3 Glycolysis
Gene 5 Glycolysis
58.000000
4.166667
100
3000
288
1200
188
3000
288
1200
1000
3808
18888
5888
• Identify the total length of genes in Glycolysis pathway.
## [1] 1500
1500
1500
17888
10000
1808
3808
10000
5888
• Identify the mean length normalised expression across Sample 1 and Sample2 for Ens006 genes
## [1] 67.5
• For all genes, identify the log2 fold change in length normalised expression from Sample 1 to Sample 2.
Gene 1
Gene 2
Gene 3
Gene 5
## 8.5849625 -1.0080000 8.7655347 1.0800000
1500
1500
17800
10000](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F352e11ca-88ef-47e6-aaf3-43746f591920%2F718b54cf-40e2-4907-8bcc-310148a50f66%2F1ncdsa_processed.png&w=3840&q=75)
Transcribed Image Text:• Create data frame called Annotation with a column of gene names ("Gene_1", "Gene_2",
"Gene_3","Gene_4","Gene_5"), ensembl gene names ("Ens001", "Ens003", "Ens006", "Ens007", "Ens010"),
pathway information ("Glycolysis", "TGFb", "Glycolysis", "TGFb", "Glycolysis") and gene lengths (100, 3000, 200,
1000,1200).
• Create data frame called Sample1 with ensembl gene names ("Ens001", "Ens003", "Ens006", "Ens010") and
expression (1000, 3000, 10000,5000)
• Create data frame called Sample2 with ensembl gene names ("Ens001", "Ens003", "Ens006",
"Ens007", "Ens010") and expression (1500, 1500, 17000,500,10000)
• Create a data frame containing only those gene names common to all data frames with all information from
Annotation and the expression from Sample 1 and Sample 2.
ensembl geneNames pathway geneLengths expression.x expression.y
## 1 Ens881
## 2 Ens883
Ens886
## 3
## 4 Ens010
##
##
## 2 Ens003
## 3 Ens006
##4
##
## 1
## 2
## 3
## 4
• Add an extra two columns containing the length normalised expressions for Sample 1 and Sample 2
ensembl geneNames pathway geneLengths expression.x expression.y
##1 Ens001
Gene 1 Glycolysis
Gene_2
TGFb
Gene 3 Glycolysis
Ens010 Gene 5 Glycolysis
Sample1 Ine Sample2_1ne
15.000000
8.500000
85.000000
8.333333
18.000000
1.000000
##
Gene_1 Glycolysis
Gene_2
TGFb
Gene 3 Glycolysis
Gene 5 Glycolysis
58.000000
4.166667
100
3000
288
1200
188
3000
288
1200
1000
3808
18888
5888
• Identify the total length of genes in Glycolysis pathway.
## [1] 1500
1500
1500
17888
10000
1808
3808
10000
5888
• Identify the mean length normalised expression across Sample 1 and Sample2 for Ens006 genes
## [1] 67.5
• For all genes, identify the log2 fold change in length normalised expression from Sample 1 to Sample 2.
Gene 1
Gene 2
Gene 3
Gene 5
## 8.5849625 -1.0080000 8.7655347 1.0800000
1500
1500
17800
10000
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