genesFromRandomPathways: Function to randomly select genes associated with randomly...
In sigora: Signature Overrepresentation Analysis
Description
Usage
Arguments
Value
References
See Also
Examples
View source: R/genesFromRandomPathways.R
Description
This function first randomly selects a number (np) of pathways, then
randomly selects a number (ng) of genes that are associated with at
least one of the selected pathways. The function can be used to compare
Sigora's performance to traditional overrepresentation tests.
Usage
1
genesFromRandomPathways(seed = 1234, GPSrepo, np, ng)
Arguments
seed
A random seed.
GPSrepo
A signature repository (created by ..) or one of the precompiled options.
np
How many pathways to select.
ng
Number of genes to be selected.
Value
selectedPathways
A vector containing the "np" originally selected pathways.
genes
A vector containing the "ng" selected genes from selectedPathways.
References
Foroushani AB, Brinkman FS and Lynn DJ (2013).“Pathway-GPS and SIGORA: identifying relevant pathways based on the over-representation of their gene-pair signatures.”PeerJ, 1
See Also
Examples
1
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10
11
12
13
## select 50 genes from 3 human KEGG pathways
a1<-genesFromRandomPathways(seed=12345,kegH,3,50)
## originally selected pathways:
a1[["selectedPathways"]]
## what are the genes
a1[["genes"]]
## sigora's results
sigoraRes <- sigora(GPSrepo =kegH, queryList = a1[["genes"]],
level = 4)
## compare to traditional methods results:
oraRes <- ora(a1[["genes"]],kegH)
dim(oraRes)
oraRes
Example output
### randomly selected pathways are:
hsa04145
hsa05323
hsa00380
[1] "hsa04145" "hsa05323" "hsa00380"
[1] "ENSG00000090339" "ENSG00000204267" "ENSG00000167553" "ENSG00000019169"
[5] "ENSG00000116039" "ENSG00000105953" "ENSG00000115008" "ENSG00000082781"
[9] "ENSG00000117410" "ENSG00000137124" "ENSG00000150337" "ENSG00000242574"
[13] "ENSG00000170458" "ENSG00000007952" "ENSG00000108774" "ENSG00000102755"
[17] "ENSG00000164400" "ENSG00000250565" "ENSG00000258947" "ENSG00000102524"
[21] "ENSG00000153086" "ENSG00000196735" "ENSG00000237541" "ENSG00000241106"
[25] "ENSG00000116701" "ENSG00000159720" "ENSG00000135218" "ENSG00000143149"
[29] "ENSG00000259207" "ENSG00000005844" "ENSG00000078142" "ENSG00000227507"
[33] "ENSG00000150093" "ENSG00000241644" "ENSG00000121691" "ENSG00000162747"
[37] "ENSG00000167552" "ENSG00000109576" "ENSG00000178462" "ENSG00000164904"
[41] "ENSG00000104951" "ENSG00000115020" "ENSG00000185883" "ENSG00000152086"
[45] "ENSG00000113296" "ENSG00000106803" "ENSG00000119699" "ENSG00000112115"
[49] "ENSG00000111537" "ENSG00000197102"
pathwy.id description pvalues Bonferroni
6 hsa04145 Phagosome 1.959e-33 5.485e-31
18 hsa05332 Graft-versus-host disease 8.288e-24 2.321e-21
11 hsa05130 Pathogenic Escherichia coli infection 1.827e-19 5.116e-17
2 hsa00380 Tryptophan metabolism 3.736e-07 1.046e-04
12 hsa05145 Toxoplasmosis 3.122e-05 8.742e-03
successes PathwaySize N sample.size
6 21.43 815.48 350891 116.03
18 15.00 612.25 350891 116.03
11 16.44 1529.91 350891 116.03
2 4.58 170.73 350891 116.03
12 9.37 4744.94 350891 116.03
[1] 29 7
pathwyid description
21215 hsa04966 Collecting duct acid secretion
18308 hsa05310 Asthma
4972 hsa05330 Allograft rejection
10482 hsa05332 Graft-versus-host disease
17452 hsa00380 Tryptophan metabolism
6942 hsa04940 Type I diabetes mellitus
10428 hsa04672 Intestinal immune network for IgA production
12316 hsa05144 Malaria
17913 hsa00280 Valine, leucine and isoleucine degradation
19585 hsa05110 Vibrio cholerae infection
17542 hsa05150 Staphylococcus aureus infection
17491 hsa00310 Lysine degradation
5006 hsa05130 Pathogenic Escherichia coli infection
18680 hsa05416 Viral myocarditis
10366 hsa05321 Inflammatory bowel disease (IBD)
7727 hsa04721 Synaptic vesicle cycle
9643 hsa04612 Antigen processing and presentation
17786 hsa05120 Epithelial cell signaling in Helicobacter pylori infection
11194 hsa05140 Leishmaniasis
12845 hsa05132 Salmonella infection
20378 hsa05322 Systemic lupus erythematosus
12582 hsa04640 Hematopoietic cell lineage
19500 hsa05323 Rheumatoid arthritis
3509 hsa05145 Toxoplasmosis
19024 hsa04380 Osteoclast differentiation
6143 hsa04514 Cell adhesion molecules (CAMs)
16694 hsa04145 Phagosome
4809 hsa05164 Influenza A
20210 hsa05152 Tuberculosis
success pathwaySize pvalues Bonfer NA
21215 4 hsa04966 27 4.626e-05 5.55120e-03
18308 4 hsa05310 27 4.626e-05 5.55120e-03
4972 5 hsa05330 34 4.964e-06 5.95680e-04
10482 6 hsa05332 36 2.372e-07 2.84640e-05
17452 9 hsa00380 39 7.336e-12 8.80320e-10
6942 6 hsa04940 40 4.567e-07 5.48040e-05
10428 5 hsa04672 44 1.830e-05 2.19600e-03
12316 6 hsa05144 45 9.416e-07 1.12992e-04
17913 4 hsa00280 46 3.866e-04 4.63920e-02
19585 6 hsa05110 50 1.785e-06 2.14200e-04
17542 8 hsa05150 50 2.699e-09 3.23880e-07
17491 5 hsa00310 51 3.802e-05 4.56240e-03
5006 7 hsa05130 53 1.151e-07 1.38120e-05
18680 6 hsa05416 55 3.163e-06 3.79560e-04
10366 8 hsa05321 62 1.586e-08 1.90320e-06
7727 5 hsa04721 63 1.062e-04 1.27440e-02
9643 6 hsa04612 65 8.506e-06 1.02072e-03
17786 5 hsa05120 68 1.530e-04 1.83600e-02
11194 11 hsa05140 68 1.761e-12 2.11320e-10
12845 5 hsa05132 84 4.136e-04 4.96320e-02
20378 7 hsa05322 84 2.826e-06 3.39120e-04
12582 6 hsa04640 85 4.012e-05 4.81440e-03
19500 19 hsa05323 85 3.680e-24 4.41600e-22
3509 7 hsa05145 111 1.813e-05 2.17560e-03
19024 7 hsa04380 125 3.925e-05 4.71000e-03
6143 7 hsa04514 139 7.744e-05 9.29280e-03
16694 31 hsa04145 147 5.853e-40 7.02360e-38
4809 7 hsa05164 163 2.103e-04 2.52360e-02
20210 15 hsa05152 168 7.503e-13 9.00360e-11
sigora documentation built on Aug. 24, 2019, 1:04 a.m.
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Description Usage Arguments Value References See Also Examples
View source: R/genesFromRandomPathways.R
Description
This function first randomly selects a number (np) of pathways, then randomly selects a number (ng) of genes that are associated with at least one of the selected pathways. The function can be used to compare Sigora's performance to traditional overrepresentation tests.
Usage
1 | genesFromRandomPathways(seed = 1234, GPSrepo, np, ng)
|
Arguments
seed |
A random seed. |
GPSrepo |
A signature repository (created by ..) or one of the precompiled options. |
np |
How many pathways to select. |
ng |
Number of genes to be selected. |
Value
selectedPathways |
A vector containing the "np" originally selected pathways. |
genes |
A vector containing the "ng" selected genes from selectedPathways. |
References
Foroushani AB, Brinkman FS and Lynn DJ (2013).“Pathway-GPS and SIGORA: identifying relevant pathways based on the over-representation of their gene-pair signatures.”PeerJ, 1
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## select 50 genes from 3 human KEGG pathways
a1<-genesFromRandomPathways(seed=12345,kegH,3,50)
## originally selected pathways:
a1[["selectedPathways"]]
## what are the genes
a1[["genes"]]
## sigora's results
sigoraRes <- sigora(GPSrepo =kegH, queryList = a1[["genes"]],
level = 4)
## compare to traditional methods results:
oraRes <- ora(a1[["genes"]],kegH)
dim(oraRes)
oraRes
|
Example output
### randomly selected pathways are:
hsa04145
hsa05323
hsa00380
[1] "hsa04145" "hsa05323" "hsa00380"
[1] "ENSG00000090339" "ENSG00000204267" "ENSG00000167553" "ENSG00000019169"
[5] "ENSG00000116039" "ENSG00000105953" "ENSG00000115008" "ENSG00000082781"
[9] "ENSG00000117410" "ENSG00000137124" "ENSG00000150337" "ENSG00000242574"
[13] "ENSG00000170458" "ENSG00000007952" "ENSG00000108774" "ENSG00000102755"
[17] "ENSG00000164400" "ENSG00000250565" "ENSG00000258947" "ENSG00000102524"
[21] "ENSG00000153086" "ENSG00000196735" "ENSG00000237541" "ENSG00000241106"
[25] "ENSG00000116701" "ENSG00000159720" "ENSG00000135218" "ENSG00000143149"
[29] "ENSG00000259207" "ENSG00000005844" "ENSG00000078142" "ENSG00000227507"
[33] "ENSG00000150093" "ENSG00000241644" "ENSG00000121691" "ENSG00000162747"
[37] "ENSG00000167552" "ENSG00000109576" "ENSG00000178462" "ENSG00000164904"
[41] "ENSG00000104951" "ENSG00000115020" "ENSG00000185883" "ENSG00000152086"
[45] "ENSG00000113296" "ENSG00000106803" "ENSG00000119699" "ENSG00000112115"
[49] "ENSG00000111537" "ENSG00000197102"
pathwy.id description pvalues Bonferroni
6 hsa04145 Phagosome 1.959e-33 5.485e-31
18 hsa05332 Graft-versus-host disease 8.288e-24 2.321e-21
11 hsa05130 Pathogenic Escherichia coli infection 1.827e-19 5.116e-17
2 hsa00380 Tryptophan metabolism 3.736e-07 1.046e-04
12 hsa05145 Toxoplasmosis 3.122e-05 8.742e-03
successes PathwaySize N sample.size
6 21.43 815.48 350891 116.03
18 15.00 612.25 350891 116.03
11 16.44 1529.91 350891 116.03
2 4.58 170.73 350891 116.03
12 9.37 4744.94 350891 116.03
[1] 29 7
pathwyid description
21215 hsa04966 Collecting duct acid secretion
18308 hsa05310 Asthma
4972 hsa05330 Allograft rejection
10482 hsa05332 Graft-versus-host disease
17452 hsa00380 Tryptophan metabolism
6942 hsa04940 Type I diabetes mellitus
10428 hsa04672 Intestinal immune network for IgA production
12316 hsa05144 Malaria
17913 hsa00280 Valine, leucine and isoleucine degradation
19585 hsa05110 Vibrio cholerae infection
17542 hsa05150 Staphylococcus aureus infection
17491 hsa00310 Lysine degradation
5006 hsa05130 Pathogenic Escherichia coli infection
18680 hsa05416 Viral myocarditis
10366 hsa05321 Inflammatory bowel disease (IBD)
7727 hsa04721 Synaptic vesicle cycle
9643 hsa04612 Antigen processing and presentation
17786 hsa05120 Epithelial cell signaling in Helicobacter pylori infection
11194 hsa05140 Leishmaniasis
12845 hsa05132 Salmonella infection
20378 hsa05322 Systemic lupus erythematosus
12582 hsa04640 Hematopoietic cell lineage
19500 hsa05323 Rheumatoid arthritis
3509 hsa05145 Toxoplasmosis
19024 hsa04380 Osteoclast differentiation
6143 hsa04514 Cell adhesion molecules (CAMs)
16694 hsa04145 Phagosome
4809 hsa05164 Influenza A
20210 hsa05152 Tuberculosis
success pathwaySize pvalues Bonfer NA
21215 4 hsa04966 27 4.626e-05 5.55120e-03
18308 4 hsa05310 27 4.626e-05 5.55120e-03
4972 5 hsa05330 34 4.964e-06 5.95680e-04
10482 6 hsa05332 36 2.372e-07 2.84640e-05
17452 9 hsa00380 39 7.336e-12 8.80320e-10
6942 6 hsa04940 40 4.567e-07 5.48040e-05
10428 5 hsa04672 44 1.830e-05 2.19600e-03
12316 6 hsa05144 45 9.416e-07 1.12992e-04
17913 4 hsa00280 46 3.866e-04 4.63920e-02
19585 6 hsa05110 50 1.785e-06 2.14200e-04
17542 8 hsa05150 50 2.699e-09 3.23880e-07
17491 5 hsa00310 51 3.802e-05 4.56240e-03
5006 7 hsa05130 53 1.151e-07 1.38120e-05
18680 6 hsa05416 55 3.163e-06 3.79560e-04
10366 8 hsa05321 62 1.586e-08 1.90320e-06
7727 5 hsa04721 63 1.062e-04 1.27440e-02
9643 6 hsa04612 65 8.506e-06 1.02072e-03
17786 5 hsa05120 68 1.530e-04 1.83600e-02
11194 11 hsa05140 68 1.761e-12 2.11320e-10
12845 5 hsa05132 84 4.136e-04 4.96320e-02
20378 7 hsa05322 84 2.826e-06 3.39120e-04
12582 6 hsa04640 85 4.012e-05 4.81440e-03
19500 19 hsa05323 85 3.680e-24 4.41600e-22
3509 7 hsa05145 111 1.813e-05 2.17560e-03
19024 7 hsa04380 125 3.925e-05 4.71000e-03
6143 7 hsa04514 139 7.744e-05 9.29280e-03
16694 31 hsa04145 147 5.853e-40 7.02360e-38
4809 7 hsa05164 163 2.103e-04 2.52360e-02
20210 15 hsa05152 168 7.503e-13 9.00360e-11
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