Get data
: Get pathway and network dataIntegration data
: Integration between pathway and network dataPathway summary indexes
: Score for each pathwayPathway cross-talk indexes
: Score for pairwise pathwaysSelection of pathway cross-talk
: Selection of pathway cross-talkIPPI
: Driver genes for each pathwayVisualization
: Gene interactions and pathwaysMotivation:
New technologies have made possible to identify marker gene signatures. However, gene expression-based signatures present some limitations because they do not consider metabolic role of the genes and are affected by genetic heterogeneity across patient cohorts. Considering the activity of entire pathways rather than the expression levels of individual genes can be a way to exceed these limits (Cancer Genome Atlas Research Network and others 2012).
This tool StarBioTrek
presents some methodologies to measure pathway activity and cross-talk among pathways integrating also the information of network and TCGA data. New measures are under development.
To install use the code below.
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install("StarBioTrek")
Get data
: Get pathway and network dataSELECT_path_species
: Select the pathway database and species of interestThe user can select the pathway database and species of interest using some functions implemented in graphite (Sales G, et al. 2012)
library(graphite)
sel<-pathwayDatabases()
species | database |
---|---|
athaliana | kegg |
athaliana | pathbank |
athaliana | reactome |
btaurus | kegg |
btaurus | reactome |
celegans | kegg |
celegans | reactome |
cfamiliaris | kegg |
cfamiliaris | reactome |
dmelanogaster | kegg |
dmelanogaster | reactome |
drerio | kegg |
drerio | reactome |
ecoli | kegg |
ecoli | pathbank |
ggallus | kegg |
ggallus | reactome |
hsapiens | biocarta |
hsapiens | humancyc |
hsapiens | kegg |
hsapiens | nci |
hsapiens | panther |
hsapiens | pathbank |
hsapiens | pharmgkb |
hsapiens | reactome |
hsapiens | smpdb |
mmusculus | kegg |
mmusculus | pathbank |
mmusculus | reactome |
rnorvegicus | kegg |
rnorvegicus | pathbank |
rnorvegicus | reactome |
scerevisiae | kegg |
scerevisiae | pathbank |
scerevisiae | reactome |
sscrofa | kegg |
sscrofa | reactome |
xlaevis | kegg |
GetData
: Searching pathway data for downloadThe user can easily search pathways data and their genes using the GetData
function. It can download pathways from several databases and species using the following parameters:
species="hsapiens"
pathwaydb="kegg"
path<-GetData(species,pathwaydb)
## [1] "Querying............. Glycolysis / Gluconeogenesis 1 of 303 pathways"
## [1] "Querying............. Citrate cycle (TCA cycle) 2 of 303 pathways"
## [1] "Querying............. Pentose phosphate pathway 3 of 303 pathways"
## [1] "Querying............. Pentose and glucuronate interconversions 4 of 303 pathways"
## [1] "Querying............. Fructose and mannose metabolism 5 of 303 pathways"
## [1] "Querying............. Galactose metabolism 6 of 303 pathways"
## [1] "Querying............. Ascorbate and aldarate metabolism 7 of 303 pathways"
## [1] "Querying............. Fatty acid biosynthesis 8 of 303 pathways"
## [1] "Querying............. Fatty acid elongation 9 of 303 pathways"
## [1] "Querying............. Fatty acid degradation 10 of 303 pathways"
## [1] "Querying............. Synthesis and degradation of ketone bodies 11 of 303 pathways"
## [1] "Querying............. Steroid biosynthesis 12 of 303 pathways"
## [1] "Querying............. Primary bile acid biosynthesis 13 of 303 pathways"
## [1] "Querying............. Ubiquinone and other terpenoid-quinone biosynthesis 14 of 303 pathways"
## [1] "Querying............. Steroid hormone biosynthesis 15 of 303 pathways"
## [1] "Querying............. Oxidative phosphorylation 16 of 303 pathways"
## [1] "Querying............. Arginine biosynthesis 17 of 303 pathways"
## [1] "Querying............. Purine metabolism 18 of 303 pathways"
## [1] "Querying............. Caffeine metabolism 19 of 303 pathways"
## [1] "Querying............. Pyrimidine metabolism 20 of 303 pathways"
## [1] "Querying............. Alanine, aspartate and glutamate metabolism 21 of 303 pathways"
## [1] "Querying............. Glycine, serine and threonine metabolism 22 of 303 pathways"
## [1] "Querying............. Cysteine and methionine metabolism 23 of 303 pathways"
## [1] "Querying............. Valine, leucine and isoleucine degradation 24 of 303 pathways"
## [1] "Querying............. Lysine degradation 25 of 303 pathways"
## [1] "Querying............. Arginine and proline metabolism 26 of 303 pathways"
## [1] "Querying............. Histidine metabolism 27 of 303 pathways"
## [1] "Querying............. Tyrosine metabolism 28 of 303 pathways"
## [1] "Querying............. Phenylalanine metabolism 29 of 303 pathways"
## [1] "Querying............. Tryptophan metabolism 30 of 303 pathways"
## [1] "Querying............. Phenylalanine, tyrosine and tryptophan biosynthesis 31 of 303 pathways"
## [1] "Querying............. beta-Alanine metabolism 32 of 303 pathways"
## [1] "Querying............. Taurine and hypotaurine metabolism 33 of 303 pathways"
## [1] "Querying............. Phosphonate and phosphinate metabolism 34 of 303 pathways"
## [1] "Querying............. Selenocompound metabolism 35 of 303 pathways"
## [1] "Querying............. D-Glutamine and D-glutamate metabolism 36 of 303 pathways"
## [1] "Querying............. Glutathione metabolism 37 of 303 pathways"
## [1] "Querying............. Starch and sucrose metabolism 38 of 303 pathways"
## [1] "Querying............. N-Glycan biosynthesis 39 of 303 pathways"
## [1] "Querying............. Mucin type O-glycan biosynthesis 40 of 303 pathways"
## [1] "Querying............. Mannose type O-glycan biosynthesis 41 of 303 pathways"
## [1] "Querying............. Amino sugar and nucleotide sugar metabolism 42 of 303 pathways"
## [1] "Querying............. Glycosaminoglycan degradation 43 of 303 pathways"
## [1] "Querying............. Glycosaminoglycan biosynthesis - chondroitin sulfate / dermatan sulfate 44 of 303 pathways"
## [1] "Querying............. Glycosaminoglycan biosynthesis - heparan sulfate / heparin 45 of 303 pathways"
## [1] "Querying............. Glycerolipid metabolism 46 of 303 pathways"
## [1] "Querying............. Inositol phosphate metabolism 47 of 303 pathways"
## [1] "Querying............. Glycosylphosphatidylinositol (GPI)-anchor biosynthesis 48 of 303 pathways"
## [1] "Querying............. Glycerophospholipid metabolism 49 of 303 pathways"
## [1] "Querying............. Ether lipid metabolism 50 of 303 pathways"
## [1] "Querying............. Arachidonic acid metabolism 51 of 303 pathways"
## [1] "Querying............. Linoleic acid metabolism 52 of 303 pathways"
## [1] "Querying............. alpha-Linolenic acid metabolism 53 of 303 pathways"
## [1] "Querying............. Sphingolipid metabolism 54 of 303 pathways"
## [1] "Querying............. Glycosphingolipid biosynthesis - lacto and neolacto series 55 of 303 pathways"
## [1] "Querying............. Glycosphingolipid biosynthesis - globo and isoglobo series 56 of 303 pathways"
## [1] "Querying............. Glycosphingolipid biosynthesis - ganglio series 57 of 303 pathways"
## [1] "Querying............. Pyruvate metabolism 58 of 303 pathways"
## [1] "Querying............. Glyoxylate and dicarboxylate metabolism 59 of 303 pathways"
## [1] "Querying............. Propanoate metabolism 60 of 303 pathways"
## [1] "Querying............. Butanoate metabolism 61 of 303 pathways"
## [1] "Querying............. One carbon pool by folate 62 of 303 pathways"
## [1] "Querying............. Thiamine metabolism 63 of 303 pathways"
## [1] "Querying............. Riboflavin metabolism 64 of 303 pathways"
## [1] "Querying............. Vitamin B6 metabolism 65 of 303 pathways"
## [1] "Querying............. Nicotinate and nicotinamide metabolism 66 of 303 pathways"
## [1] "Querying............. Pantothenate and CoA biosynthesis 67 of 303 pathways"
## [1] "Querying............. Biotin metabolism 68 of 303 pathways"
## [1] "Querying............. Lipoic acid metabolism 69 of 303 pathways"
## [1] "Querying............. Folate biosynthesis 70 of 303 pathways"
## [1] "Querying............. Retinol metabolism 71 of 303 pathways"
## [1] "Querying............. Porphyrin and chlorophyll metabolism 72 of 303 pathways"
## [1] "Querying............. Terpenoid backbone biosynthesis 73 of 303 pathways"
## [1] "Querying............. Nitrogen metabolism 74 of 303 pathways"
## [1] "Querying............. Sulfur metabolism 75 of 303 pathways"
## [1] "Querying............. Aminoacyl-tRNA biosynthesis 76 of 303 pathways"
## [1] "Querying............. Metabolism of xenobiotics by cytochrome P450 77 of 303 pathways"
## [1] "Querying............. Drug metabolism - cytochrome P450 78 of 303 pathways"
## [1] "Querying............. Drug metabolism - other enzymes 79 of 303 pathways"
## [1] "Querying............. Biosynthesis of unsaturated fatty acids 80 of 303 pathways"
## [1] "Querying............. EGFR tyrosine kinase inhibitor resistance 81 of 303 pathways"
## [1] "Querying............. Endocrine resistance 82 of 303 pathways"
## [1] "Querying............. Antifolate resistance 83 of 303 pathways"
## [1] "Querying............. Platinum drug resistance 84 of 303 pathways"
## [1] "Querying............. Ribosome biogenesis in eukaryotes 85 of 303 pathways"
## [1] "Querying............. RNA transport 86 of 303 pathways"
## [1] "Querying............. mRNA surveillance pathway 87 of 303 pathways"
## [1] "Querying............. RNA degradation 88 of 303 pathways"
## [1] "Querying............. Homologous recombination 89 of 303 pathways"
## [1] "Querying............. Fanconi anemia pathway 90 of 303 pathways"
## [1] "Querying............. MAPK signaling pathway 91 of 303 pathways"
## [1] "Querying............. ErbB signaling pathway 92 of 303 pathways"
## [1] "Querying............. Ras signaling pathway 93 of 303 pathways"
## [1] "Querying............. Rap1 signaling pathway 94 of 303 pathways"
## [1] "Querying............. Calcium signaling pathway 95 of 303 pathways"
## [1] "Querying............. cGMP-PKG signaling pathway 96 of 303 pathways"
## [1] "Querying............. cAMP signaling pathway 97 of 303 pathways"
## [1] "Querying............. Cytokine-cytokine receptor interaction 98 of 303 pathways"
## [1] "Querying............. Chemokine signaling pathway 99 of 303 pathways"
## [1] "Querying............. NF-kappa B signaling pathway 100 of 303 pathways"
## [1] "Querying............. HIF-1 signaling pathway 101 of 303 pathways"
## [1] "Querying............. FoxO signaling pathway 102 of 303 pathways"
## [1] "Querying............. Phosphatidylinositol signaling system 103 of 303 pathways"
## [1] "Querying............. Sphingolipid signaling pathway 104 of 303 pathways"
## [1] "Querying............. Phospholipase D signaling pathway 105 of 303 pathways"
## [1] "Querying............. Neuroactive ligand-receptor interaction 106 of 303 pathways"
## [1] "Querying............. Cell cycle 107 of 303 pathways"
## [1] "Querying............. Oocyte meiosis 108 of 303 pathways"
## [1] "Querying............. p53 signaling pathway 109 of 303 pathways"
## [1] "Querying............. Sulfur relay system 110 of 303 pathways"
## [1] "Querying............. SNARE interactions in vesicular transport 111 of 303 pathways"
## [1] "Querying............. Autophagy - other 112 of 303 pathways"
## [1] "Querying............. Mitophagy - animal 113 of 303 pathways"
## [1] "Querying............. Autophagy - animal 114 of 303 pathways"
## [1] "Querying............. Protein processing in endoplasmic reticulum 115 of 303 pathways"
## [1] "Querying............. Endocytosis 116 of 303 pathways"
## [1] "Querying............. Phagosome 117 of 303 pathways"
## [1] "Querying............. Peroxisome 118 of 303 pathways"
## [1] "Querying............. mTOR signaling pathway 119 of 303 pathways"
## [1] "Querying............. PI3K-Akt signaling pathway 120 of 303 pathways"
## [1] "Querying............. AMPK signaling pathway 121 of 303 pathways"
## [1] "Querying............. Apoptosis 122 of 303 pathways"
## [1] "Querying............. Longevity regulating pathway 123 of 303 pathways"
## [1] "Querying............. Longevity regulating pathway - multiple species 124 of 303 pathways"
## [1] "Querying............. Ferroptosis 125 of 303 pathways"
## [1] "Querying............. Necroptosis 126 of 303 pathways"
## [1] "Querying............. Cellular senescence 127 of 303 pathways"
## [1] "Querying............. Cardiac muscle contraction 128 of 303 pathways"
## [1] "Querying............. Adrenergic signaling in cardiomyocytes 129 of 303 pathways"
## [1] "Querying............. Vascular smooth muscle contraction 130 of 303 pathways"
## [1] "Querying............. Wnt signaling pathway 131 of 303 pathways"
## [1] "Querying............. Notch signaling pathway 132 of 303 pathways"
## [1] "Querying............. Hedgehog signaling pathway 133 of 303 pathways"
## [1] "Querying............. TGF-beta signaling pathway 134 of 303 pathways"
## [1] "Querying............. Axon guidance 135 of 303 pathways"
## [1] "Querying............. VEGF signaling pathway 136 of 303 pathways"
## [1] "Querying............. Apelin signaling pathway 137 of 303 pathways"
## [1] "Querying............. Osteoclast differentiation 138 of 303 pathways"
## [1] "Querying............. Hippo signaling pathway 139 of 303 pathways"
## [1] "Querying............. Hippo signaling pathway - multiple species 140 of 303 pathways"
## [1] "Querying............. Focal adhesion 141 of 303 pathways"
## [1] "Querying............. ECM-receptor interaction 142 of 303 pathways"
## [1] "Querying............. Cell adhesion molecules (CAMs) 143 of 303 pathways"
## [1] "Querying............. Adherens junction 144 of 303 pathways"
## [1] "Querying............. Tight junction 145 of 303 pathways"
## [1] "Querying............. Gap junction 146 of 303 pathways"
## [1] "Querying............. Signaling pathways regulating pluripotency of stem cells 147 of 303 pathways"
## [1] "Querying............. Complement and coagulation cascades 148 of 303 pathways"
## [1] "Querying............. Platelet activation 149 of 303 pathways"
## [1] "Querying............. Antigen processing and presentation 150 of 303 pathways"
## [1] "Querying............. Renin-angiotensin system 151 of 303 pathways"
## [1] "Querying............. Toll-like receptor signaling pathway 152 of 303 pathways"
## [1] "Querying............. NOD-like receptor signaling pathway 153 of 303 pathways"
## [1] "Querying............. RIG-I-like receptor signaling pathway 154 of 303 pathways"
## [1] "Querying............. Cytosolic DNA-sensing pathway 155 of 303 pathways"
## [1] "Querying............. C-type lectin receptor signaling pathway 156 of 303 pathways"
## [1] "Querying............. JAK-STAT signaling pathway 157 of 303 pathways"
## [1] "Querying............. Natural killer cell mediated cytotoxicity 158 of 303 pathways"
## [1] "Querying............. IL-17 signaling pathway 159 of 303 pathways"
## [1] "Querying............. Th1 and Th2 cell differentiation 160 of 303 pathways"
## [1] "Querying............. Th17 cell differentiation 161 of 303 pathways"
## [1] "Querying............. T cell receptor signaling pathway 162 of 303 pathways"
## [1] "Querying............. B cell receptor signaling pathway 163 of 303 pathways"
## [1] "Querying............. Fc epsilon RI signaling pathway 164 of 303 pathways"
## [1] "Querying............. Fc gamma R-mediated phagocytosis 165 of 303 pathways"
## [1] "Querying............. TNF signaling pathway 166 of 303 pathways"
## [1] "Querying............. Leukocyte transendothelial migration 167 of 303 pathways"
## [1] "Querying............. Intestinal immune network for IgA production 168 of 303 pathways"
## [1] "Querying............. Circadian rhythm 169 of 303 pathways"
## [1] "Querying............. Circadian entrainment 170 of 303 pathways"
## [1] "Querying............. Thermogenesis 171 of 303 pathways"
## [1] "Querying............. Long-term potentiation 172 of 303 pathways"
## [1] "Querying............. Synaptic vesicle cycle 173 of 303 pathways"
## [1] "Querying............. Neurotrophin signaling pathway 174 of 303 pathways"
## [1] "Querying............. Retrograde endocannabinoid signaling 175 of 303 pathways"
## [1] "Querying............. Glutamatergic synapse 176 of 303 pathways"
## [1] "Querying............. Cholinergic synapse 177 of 303 pathways"
## [1] "Querying............. Serotonergic synapse 178 of 303 pathways"
## [1] "Querying............. GABAergic synapse 179 of 303 pathways"
## [1] "Querying............. Dopaminergic synapse 180 of 303 pathways"
## [1] "Querying............. Long-term depression 181 of 303 pathways"
## [1] "Querying............. Olfactory transduction 182 of 303 pathways"
## [1] "Querying............. Taste transduction 183 of 303 pathways"
## [1] "Querying............. Phototransduction 184 of 303 pathways"
## [1] "Querying............. Inflammatory mediator regulation of TRP channels 185 of 303 pathways"
## [1] "Querying............. Regulation of actin cytoskeleton 186 of 303 pathways"
## [1] "Querying............. Insulin signaling pathway 187 of 303 pathways"
## [1] "Querying............. Insulin secretion 188 of 303 pathways"
## [1] "Querying............. GnRH signaling pathway 189 of 303 pathways"
## [1] "Querying............. Ovarian steroidogenesis 190 of 303 pathways"
## [1] "Querying............. Progesterone-mediated oocyte maturation 191 of 303 pathways"
## [1] "Querying............. Estrogen signaling pathway 192 of 303 pathways"
## [1] "Querying............. Melanogenesis 193 of 303 pathways"
## [1] "Querying............. Prolactin signaling pathway 194 of 303 pathways"
## [1] "Querying............. Thyroid hormone synthesis 195 of 303 pathways"
## [1] "Querying............. Thyroid hormone signaling pathway 196 of 303 pathways"
## [1] "Querying............. Adipocytokine signaling pathway 197 of 303 pathways"
## [1] "Querying............. Oxytocin signaling pathway 198 of 303 pathways"
## [1] "Querying............. Glucagon signaling pathway 199 of 303 pathways"
## [1] "Querying............. Regulation of lipolysis in adipocytes 200 of 303 pathways"
## [1] "Querying............. Renin secretion 201 of 303 pathways"
## [1] "Querying............. Aldosterone synthesis and secretion 202 of 303 pathways"
## [1] "Querying............. Relaxin signaling pathway 203 of 303 pathways"
## [1] "Querying............. Cortisol synthesis and secretion 204 of 303 pathways"
## [1] "Querying............. Parathyroid hormone synthesis, secretion and action 205 of 303 pathways"
## [1] "Querying............. Type II diabetes mellitus 206 of 303 pathways"
## [1] "Querying............. Insulin resistance 207 of 303 pathways"
## [1] "Querying............. Non-alcoholic fatty liver disease (NAFLD) 208 of 303 pathways"
## [1] "Querying............. AGE-RAGE signaling pathway in diabetic complications 209 of 303 pathways"
## [1] "Querying............. Cushing syndrome 210 of 303 pathways"
## [1] "Querying............. Type I diabetes mellitus 211 of 303 pathways"
## [1] "Querying............. Maturity onset diabetes of the young 212 of 303 pathways"
## [1] "Querying............. Aldosterone-regulated sodium reabsorption 213 of 303 pathways"
## [1] "Querying............. Endocrine and other factor-regulated calcium reabsorption 214 of 303 pathways"
## [1] "Querying............. Vasopressin-regulated water reabsorption 215 of 303 pathways"
## [1] "Querying............. Proximal tubule bicarbonate reclamation 216 of 303 pathways"
## [1] "Querying............. Salivary secretion 217 of 303 pathways"
## [1] "Querying............. Gastric acid secretion 218 of 303 pathways"
## [1] "Querying............. Pancreatic secretion 219 of 303 pathways"
## [1] "Querying............. Carbohydrate digestion and absorption 220 of 303 pathways"
## [1] "Querying............. Fat digestion and absorption 221 of 303 pathways"
## [1] "Querying............. Bile secretion 222 of 303 pathways"
## [1] "Querying............. Vitamin digestion and absorption 223 of 303 pathways"
## [1] "Querying............. Mineral absorption 224 of 303 pathways"
## [1] "Querying............. Cholesterol metabolism 225 of 303 pathways"
## [1] "Querying............. Alzheimer disease 226 of 303 pathways"
## [1] "Querying............. Parkinson disease 227 of 303 pathways"
## [1] "Querying............. Amyotrophic lateral sclerosis (ALS) 228 of 303 pathways"
## [1] "Querying............. Huntington disease 229 of 303 pathways"
## [1] "Querying............. Prion diseases 230 of 303 pathways"
## [1] "Querying............. Cocaine addiction 231 of 303 pathways"
## [1] "Querying............. Amphetamine addiction 232 of 303 pathways"
## [1] "Querying............. Morphine addiction 233 of 303 pathways"
## [1] "Querying............. Alcoholism 234 of 303 pathways"
## [1] "Querying............. Bacterial invasion of epithelial cells 235 of 303 pathways"
## [1] "Querying............. Vibrio cholerae infection 236 of 303 pathways"
## [1] "Querying............. Epithelial cell signaling in Helicobacter pylori infection 237 of 303 pathways"
## [1] "Querying............. Pathogenic Escherichia coli infection 238 of 303 pathways"
## [1] "Querying............. Shigellosis 239 of 303 pathways"
## [1] "Querying............. Salmonella infection 240 of 303 pathways"
## [1] "Querying............. Pertussis 241 of 303 pathways"
## [1] "Querying............. Legionellosis 242 of 303 pathways"
## [1] "Querying............. Leishmaniasis 243 of 303 pathways"
## [1] "Querying............. Chagas disease (American trypanosomiasis) 244 of 303 pathways"
## [1] "Querying............. African trypanosomiasis 245 of 303 pathways"
## [1] "Querying............. Malaria 246 of 303 pathways"
## [1] "Querying............. Toxoplasmosis 247 of 303 pathways"
## [1] "Querying............. Amoebiasis 248 of 303 pathways"
## [1] "Querying............. Staphylococcus aureus infection 249 of 303 pathways"
## [1] "Querying............. Tuberculosis 250 of 303 pathways"
## [1] "Querying............. Hepatitis C 251 of 303 pathways"
## [1] "Querying............. Hepatitis B 252 of 303 pathways"
## [1] "Querying............. Measles 253 of 303 pathways"
## [1] "Querying............. Human cytomegalovirus infection 254 of 303 pathways"
## [1] "Querying............. Influenza A 255 of 303 pathways"
## [1] "Querying............. Human papillomavirus infection 256 of 303 pathways"
## [1] "Querying............. Human T-cell leukemia virus 1 infection 257 of 303 pathways"
## [1] "Querying............. Kaposi sarcoma-associated herpesvirus infection 258 of 303 pathways"
## [1] "Querying............. Herpes simplex infection 259 of 303 pathways"
## [1] "Querying............. Epstein-Barr virus infection 260 of 303 pathways"
## [1] "Querying............. Human immunodeficiency virus 1 infection 261 of 303 pathways"
## [1] "Querying............. Pathways in cancer 262 of 303 pathways"
## [1] "Querying............. Transcriptional misregulation in cancer 263 of 303 pathways"
## [1] "Querying............. Viral carcinogenesis 264 of 303 pathways"
## [1] "Querying............. Chemical carcinogenesis 265 of 303 pathways"
## [1] "Querying............. Proteoglycans in cancer 266 of 303 pathways"
## [1] "Querying............. MicroRNAs in cancer 267 of 303 pathways"
## [1] "Querying............. Colorectal cancer 268 of 303 pathways"
## [1] "Querying............. Renal cell carcinoma 269 of 303 pathways"
## [1] "Querying............. Pancreatic cancer 270 of 303 pathways"
## [1] "Querying............. Endometrial cancer 271 of 303 pathways"
## [1] "Querying............. Glioma 272 of 303 pathways"
## [1] "Querying............. Prostate cancer 273 of 303 pathways"
## [1] "Querying............. Thyroid cancer 274 of 303 pathways"
## [1] "Querying............. Basal cell carcinoma 275 of 303 pathways"
## [1] "Querying............. Melanoma 276 of 303 pathways"
## [1] "Querying............. Bladder cancer 277 of 303 pathways"
## [1] "Querying............. Chronic myeloid leukemia 278 of 303 pathways"
## [1] "Querying............. Acute myeloid leukemia 279 of 303 pathways"
## [1] "Querying............. Small cell lung cancer 280 of 303 pathways"
## [1] "Querying............. Non-small cell lung cancer 281 of 303 pathways"
## [1] "Querying............. Breast cancer 282 of 303 pathways"
## [1] "Querying............. Hepatocellular carcinoma 283 of 303 pathways"
## [1] "Querying............. Gastric cancer 284 of 303 pathways"
## [1] "Querying............. Central carbon metabolism in cancer 285 of 303 pathways"
## [1] "Querying............. Choline metabolism in cancer 286 of 303 pathways"
## [1] "Querying............. Asthma 287 of 303 pathways"
## [1] "Querying............. Autoimmune thyroid disease 288 of 303 pathways"
## [1] "Querying............. Inflammatory bowel disease (IBD) 289 of 303 pathways"
## [1] "Querying............. Systemic lupus erythematosus 290 of 303 pathways"
## [1] "Querying............. Rheumatoid arthritis 291 of 303 pathways"
## [1] "Querying............. Allograft rejection 292 of 303 pathways"
## [1] "Querying............. Graft-versus-host disease 293 of 303 pathways"
## [1] "Querying............. Hypertrophic cardiomyopathy (HCM) 294 of 303 pathways"
## [1] "Querying............. Arrhythmogenic right ventricular cardiomyopathy (ARVC) 295 of 303 pathways"
## [1] "Querying............. Dilated cardiomyopathy (DCM) 296 of 303 pathways"
## [1] "Querying............. Viral myocarditis 297 of 303 pathways"
## [1] "Querying............. Fluid shear stress and atherosclerosis 298 of 303 pathways"
## [1] "Querying............. Valine, leucine and isoleucine biosynthesis 299 of 303 pathways"
## [1] "Querying............. D-Arginine and D-ornithine metabolism 300 of 303 pathways"
## [1] "Querying............. Neomycin, kanamycin and gentamicin biosynthesis 301 of 303 pathways"
## [1] "Querying............. Protein digestion and absorption 302 of 303 pathways"
## [1] "Querying............. Nicotine addiction 303 of 303 pathways"
GetPathData
: Get genes inside pathwaysThe user can identify the genes inside the pathways of interest
pathway_ALLGENE<-GetPathData(path_ALL=path[1:3])
GetPathNet
: Get interacting genes inside pathwaysGetPathNet
generates a list of interacting genes for each pathway
pathway_net<-GetPathNet(path_ALL=path[1:3])
ConvertedIDgenes
: Get genes inside pathwaysThe user can convert the gene ID into GeneSymbol
pathway<-ConvertedIDgenes(path_ALL=path[1:10])
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## [1] "Mapping Uniprot ID to Gene Symbol, using convertIdentifiers of graphite package.......... Glycolysis / Gluconeogenesis 1 of 10 pathways"
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## [1] "Mapping Uniprot ID to Gene Symbol, using convertIdentifiers of graphite package.......... Citrate cycle (TCA cycle) 2 of 10 pathways"
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## [1] "Mapping Uniprot ID to Gene Symbol, using convertIdentifiers of graphite package.......... Pentose phosphate pathway 3 of 10 pathways"
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## [1] "Mapping Uniprot ID to Gene Symbol, using convertIdentifiers of graphite package.......... Pentose and glucuronate interconversions 4 of 10 pathways"
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## [1] "Mapping Uniprot ID to Gene Symbol, using convertIdentifiers of graphite package.......... Fructose and mannose metabolism 5 of 10 pathways"
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## [1] "Mapping Uniprot ID to Gene Symbol, using convertIdentifiers of graphite package.......... Galactose metabolism 6 of 10 pathways"
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## [1] "Mapping Uniprot ID to Gene Symbol, using convertIdentifiers of graphite package.......... Ascorbate and aldarate metabolism 7 of 10 pathways"
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## [1] "Mapping Uniprot ID to Gene Symbol, using convertIdentifiers of graphite package.......... Fatty acid biosynthesis 8 of 10 pathways"
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## [1] "Mapping Uniprot ID to Gene Symbol, using convertIdentifiers of graphite package.......... Fatty acid elongation 9 of 10 pathways"
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## [1] "Mapping Uniprot ID to Gene Symbol, using convertIdentifiers of graphite package.......... Fatty acid degradation 10 of 10 pathways"
getNETdata
: Searching network data for downloadYou can easily search human network data from GeneMania using the getNETdata
function (Warde-Farley D, et al. 2010).
The network category can be filtered using the following parameters:
The species can be filtered using the following parameters: * Arabidopsis_thaliana * Caenorhabditis_elegans * Danio_rerio * Drosophila_melanogaster * Escherichia_coli * Homo_sapiens * Mus_musculus * Rattus_norvegicus * Saccharomyces_cerevisiae
For default the organism is homo sapiens.
The example show the shared protein domain network for Saccharomyces_cerevisiae. For more information see SpidermiR
package.
organismID="Saccharomyces_cerevisiae"
netw<-getNETdata(network="SHpd",organismID)
## [1] "Downloading: http://genemania.org/data/current/Saccharomyces_cerevisiae/Shared_protein_domains.INTERPRO.txt ... reference n. 1 of 2"
## [1] "Downloading: http://genemania.org/data/current/Saccharomyces_cerevisiae/Shared_protein_domains.PFAM.txt ... reference n. 2 of 2"
## [1] "Preprocessing of the network n. 1 of 2"
## [1] "Preprocessing of the network n. 2 of 2"
Integration data
: Integration between pathway and network datapath_net
: Network of interacting genes for each pathway according a network type (PHint,COloc,GENint,PATH,SHpd)The function path_net
creates a network of interacting genes (downloaded from GeneMania) for each pathway. Interacting genes are genes belonging to the same pathway and the interaction is given from network chosen by the user, according the paramenters of the function getNETdata
.
The output will be a network of genes belonging to the same pathway.
lista_net<-pathnet(genes.by.pathway=pathway[1:5],data=netw)
## [1] "Glycolysis / Gluconeogenesis"
## [1] "Citrate cycle (TCA cycle)"
## [1] "Pentose phosphate pathway"
## [1] "Pentose and glucuronate interconversions"
## [1] "Fructose and mannose metabolism"
list_path_net
: List of interacting genes for each pathway (list of genes) according a network type (PHint,COloc,GENint,PATH,SHpd)The function list_path_net
creates a list of interacting genes for each pathway. Interacting genes are genes belonging to the same pathway and the interaction is given from network chosen by the user, according the paramenters of the function getNETdata
.
The output will be a list of genes belonging to the same pathway and those having an interaction in the network.
list_path<-listpathnet(lista_net=lista_net,pathway=pathway[1:5])
## [1] "List of genes interacting in the same pathway: Glycolysis / Gluconeogenesis"
## [1] "List of genes interacting in the same pathway: Citrate cycle (TCA cycle)"
## [1] "List of genes interacting in the same pathway: Pentose phosphate pathway"
## [1] "List of genes interacting in the same pathway: Pentose and glucuronate interconversions"
## [1] "List of genes interacting in the same pathway: Fructose and mannose metabolism"
Pathway summary indexes
: Score for each pathwayGE_matrix
: grouping gene expression profiles in pathwaysGet human KEGG pathway data and a gene expression matrix in order to obtain a matrix with the gene expression levels grouped by pathways.
Starting from a matrix of gene expression (rows are genes and columns are samples, TCGA data) the function GE_matrix
creates a profile of gene expression levels for each pathway given by the user:
list_path_gene<-GE_matrix(DataMatrix=tumo[,1:2],genes.by.pathway=pathway[1:10])
## [1] "Glycolysis / Gluconeogenesis"
## [1] "Citrate cycle (TCA cycle)"
## [1] "Pentose phosphate pathway"
## [1] "Pentose and glucuronate interconversions"
## [1] "Fructose and mannose metabolism"
## [1] "Galactose metabolism"
## [1] "Ascorbate and aldarate metabolism"
## [1] "Fatty acid biosynthesis"
## [1] "Fatty acid elongation"
## [1] "Fatty acid degradation"
GE_matrix_mean
:Get human KEGG pathway data and a gene expression matrix in order to obtain a matrix PXG (in the columns there are the pathways and in the rows there are genes) with the mean gene expression for only genes given containing in the pathways given in input by the user.
list_path_plot<-GE_matrix_mean(DataMatrix=tumo[,1:2],genes.by.pathway=pathway[1:10])
## [1] "Glycolysis_/ Gluconeogenesis"
## [1] "Citrate_cycle (TCA cycle)"
## [1] "Pentose_phosphate pathway"
## [1] "Pentose_and glucuronate interconversions"
## [1] "Fructose_and mannose metabolism"
## [1] "Galactose_metabolism"
## [1] "Ascorbate_and aldarate metabolism"
## [1] "Fatty_acid biosynthesis"
## [1] "Fatty_acid elongation"
## [1] "Fatty_acid degradation"
average
: Average of genes for each pathway starting from a matrix of gene expressionStarting from a matrix of gene expression (rows are genes and columns are samples, TCGA data) the function average
creates an average matrix (SXG: S are the samples and P the pathways) of gene expression for each pathway:
score_mean<-average(pathwayexpsubset=list_path_gene)
stdv
: Standard deviations of genes for each pathway starting from a matrix of gene expressionStarting from a matrix of gene expression (rows are genes and columns are samples, TCGA data) the function stdv
creates a standard deviation matrix of gene expression for each pathway:
score_st_dev<-stdv(gslist=list_path_gene)
Pathway cross-talk indexes
: Score for pairwise pathwayseucdistcrtlk
: Euclidean distance for cross-talk measureStarting from a matrix of gene expression (rows are genes and columns are samples, TCGA data) the function eucdistcrtlk
creates an euclidean distance matrix of gene expression for pairwise pathway.
score_euc_distance<-eucdistcrtlk(dataFilt=tumo[,1:2],pathway_exp=pathway[1:10])
dsscorecrtlk
: Discriminating score for cross-talk measureStarting from a matrix of gene expression (rows are genes and columns are samples, TCGA data) the function dsscorecrtlk
creates an discriminating score matrix for pairwise pathway as measure of cross-talk. Discriminating score is given by |M1-M2|/S1+S2 where M1 and M2 are mean and S1 and S2 standard deviation of expression levels of genes in a pathway 1 and and in a pathway 2 .
cross_talk_st_dv<-dsscorecrtlk(dataFilt=tumo[,1:2],pathway_exp=pathway[1:10])
Selection of pathway cross-talk
: Selection of pathway cross-talksvm_classification
: SVM classificationGiven the substantial difference in the activities of many pathways between two classes (e.g. normal and cancer), we examined the effectiveness to classify the classes based on their pairwise pathway profiles. This function is used to find the interacting pathways that are altered in a particular pathology in terms of Area Under Curve (AUC).AUC was estimated by cross-validation method (k-fold cross-validation, k=10).It randomly selected some fraction of TCGA data (e.g. nf= 60; 60% of original dataset) to form the training set and then assigned the rest of the points to the testing set (40% of original dataset). For each pairwise pathway the user can obtain using the methods mentioned above a score matrix ( e.g.dev_std_crtlk ) and can focus on the pairs of pathways able to differentiate a particular subtype with respect to the normal type.
nf <- 60
res_class<-svm_classification(TCGA_matrix=score_euc_dista[1:30,],nfs=nf,
normal=colnames(norm[,1:10]),tumour=colnames(tumo[,1:10]))
IPPI
: Driver genes for each pathwayThe function IPPI
, using pathways and networks data, calculates the driver genes for each pathway. Please see Cava et al. BMC Genomics 2017.
DRIVER_SP<-IPPI(pathax=pathway_matrix[,1:3],netwa=netw_IPPI[1:50000,])
Visualization
: Gene interactions and pathwaysStarBioTrek presents several functions for the preparation to the visualization of gene-gene interactions and pathway cross-talk using the qgraph package (S. Epskamp, et al. 2012). The function plotcrosstalk prepares the data:
formatplot<-plotcrosstalk(pathway_plot=pathway[1:6],gs_expre=tumo)
library(qgraph)
##
## Attaching package: 'qgraph'
## The following object is masked from 'package:graphite':
##
## pathways
## The following object is masked from 'package:StarBioTrek':
##
## pathways
qgraph(formatplot[[1]], minimum = 0.25, cut = 0.6, vsize = 5, groups = formatplot[[2]], legend = TRUE, borders = FALSE,layoutScale=c(0.8,0.8))
qgraph(formatplot[[1]],groups=formatplot[[2]], layout="spring", diag = FALSE,
cut = 0.6,legend.cex = 0.5,vsize = 6,layoutScale=c(0.8,0.8))
A circle can be generated using the function circleplot
(Walter W, et al. 2015). A score for each gene can be assigned.
formatplot<-plotcrosstalk(pathway_plot=pathway[1:6],gs_expre=tumo)
score<-runif(length(formatplot[[2]]), min=-10, max=+10)
circleplot(preplot=formatplot,scoregene=score)
sessionInfo()
## R version 3.5.3 (2019-03-11)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.6 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.8-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.8-bioc/R/lib/libRlapack.so
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## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] grid parallel stats4 stats graphics grDevices utils
## [8] datasets methods base
##
## other attached packages:
## [1] png_0.1-7 qgraph_1.6.1 org.Hs.eg.db_3.7.0
## [4] graphite_1.28.2 StarBioTrek_1.8.5 miRNAtap_1.16.0
## [7] AnnotationDbi_1.44.0 IRanges_2.16.0 S4Vectors_0.20.1
## [10] Biobase_2.42.0 BiocGenerics_0.28.0 BiocStyle_2.10.0
##
## loaded via a namespace (and not attached):
## [1] colorspace_1.4-1 rjson_0.2.20 class_7.3-15
## [4] rprojroot_1.3-2 htmlTable_1.13.1 corpcor_1.6.9
## [7] base64enc_0.1-3 fs_1.2.7 rstudioapi_0.10
## [10] lavaan_0.6-3 remotes_2.0.4 bit64_0.9-7
## [13] sqldf_0.4-11 splines_3.5.3 mnormt_1.5-5
## [16] knitr_1.22 glasso_1.10 pkgload_1.0.2
## [19] Formula_1.2-3 jsonlite_1.6 cluster_2.0.8
## [22] graph_1.60.0 BiocManager_1.30.4 compiler_3.5.3
## [25] httr_1.4.0 backports_1.1.4 assertthat_0.2.1
## [28] Matrix_1.2-17 lazyeval_0.2.2 cli_1.1.0
## [31] acepack_1.4.1 visNetwork_2.0.6 htmltools_0.3.6
## [34] prettyunits_1.0.2 tools_3.5.3 igraph_1.2.4
## [37] gtable_0.3.0 glue_1.3.1 reshape2_1.4.3
## [40] dplyr_0.8.0.1 rappdirs_0.3.1 Rcpp_1.0.1
## [43] nlme_3.1-139 gdata_2.18.0 psych_1.8.12
## [46] xfun_0.6 stringr_1.4.0 networkD3_0.4
## [49] ps_1.3.0 proto_1.0.0 testthat_2.0.1
## [52] ggm_2.3 gtools_3.8.1 devtools_2.0.2
## [55] MASS_7.3-51.3 MLmetrics_1.1.1 scales_1.0.0
## [58] BDgraph_2.58 huge_1.3.2 RColorBrewer_1.1-2
## [61] yaml_2.2.0 curl_3.3 pbapply_1.4-0
## [64] memoise_1.1.0 gridExtra_2.3 miRNAtap.db_0.99.10
## [67] ggplot2_3.1.1 rpart_4.1-15 latticeExtra_0.6-28
## [70] stringi_1.4.3 RSQLite_2.1.1 highr_0.8
## [73] desc_1.2.0 e1071_1.7-1 checkmate_1.9.1
## [76] caTools_1.17.1.2 pkgbuild_1.0.3 chron_2.3-53
## [79] d3Network_0.5.2.1 rlang_0.3.4 pkgconfig_2.0.2
## [82] bitops_1.0-6 evaluate_0.13 lattice_0.20-38
## [85] ROCR_1.0-7 purrr_0.3.2 htmlwidgets_1.3
## [88] bit_1.1-14 processx_3.3.0 tidyselect_0.2.5
## [91] plyr_1.8.4 magrittr_1.5 bookdown_0.9
## [94] R6_2.4.0 gplots_3.0.1.1 Hmisc_4.2-0
## [97] DBI_1.0.0 whisker_0.3-2 gsubfn_0.7
## [100] pillar_1.3.1 foreign_0.8-71 withr_2.1.2
## [103] abind_1.4-5 survival_2.44-1.1 nnet_7.3-12
## [106] tibble_2.1.1 crayon_1.3.4 fdrtool_1.2.15
## [109] KernSmooth_2.23-15 rmarkdown_1.12 jpeg_0.1-8
## [112] usethis_1.5.0 pbivnorm_0.6.0 data.table_1.12.2
## [115] blob_1.1.1 callr_3.2.0 digest_0.6.18
## [118] munsell_0.5.0 SpidermiR_1.12.1 sessioninfo_1.1.1
Cancer Genome Atlas Research Network and others. 2012. “Comprehensive Molecular Characterization of Human Colon and Rectal Cancer.” https://doi.org/10.1038/nature11252.
S. Epskamp, et al. 2012. “Qgraph Network Visualizations of Relationships in Psychometric Data.”
Sales G, et al. 2012. “Graphite - a Bioconductor Package to Convert Pathway Topology to Gene Network.” https://doi.org/10.1186/1471-2105-13-20.
Walter W, et al. 2015. “GOplot an R Package for Visually Combining Expression Data with Functional Analysis.”
Warde-Farley D, et al. 2010. “The GeneMANIA Prediction Server Biological Network Integration for Gene Prioritization and Predicting Gene Function.”