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PubMed2006

Pathway analysis using random forests classification and regression.

MOTIVATION: Although numerous methods have been developed to better capture biological information from microarray data, commonly used single gene-based methods neglect interactions among genes and leave room for other novel approaches. For example, most classification and regression methods for microarray data are based on the whole set of genes and have not made use of pathway information. Pathway-based analysis in microarray studies may lead to more informative and relevant knowledge for biological researchers. RESULTS: In this paper, we describe a pathway-based classification and regression method using Random Forests to analyze gene expression data. The proposed methods allow researchers to rank important pathways from externally available databases, discover important genes, find pathway-based outlying cases and make full use of a continuous outcome variable in the regression setting. We also compared Random Forests with other machine learning methods using several datasets and found that Random Forests classification error rates were either the lowest or the second-lowest. By combining pathway information and novel statistical methods, this procedure represents a promising computational strategy in dissecting pathways and can provide biological insight into the study of microarray data. AVAILABILITY: Source code written in R is available from http://bioinformatics.med.yale.edu/pathway-analysis/rf.htm.

Algorithms↗
PubMed2002

Metabolic pathway analysis of a recombinant yeast for rational strain development.

Elementary mode analysis has been used to study a metabolic pathway model of a recombinant Saccharomyces cerevisiae system that was genetically engineered to produce the bacterial storage compound poly-beta-hydroxybutyrate (PHB). The model includes biochemical reactions from the intermediary metabolism and takes into account cellular compartmentalization as well as the reversibility/irreversibility of the reactions. The reaction network connects the production and/or consumption of eight external metabolites including glucose, acetate, glycerol, ethanol, PHB, CO(2), succinate, and adenosine triphosphate (ATP). Elementary mode analysis of the wild-type S. cerevisiae system reveals 241 unique reaction combinations that balance the eight external metabolites. When the recombinant PHB pathway is included, and when the reaction model is altered to simulate the experimental conditions when PHB accumulates, the analysis reveals 20 unique elementary modes. Of these 20 modes, 7 produce PHB with the optimal mode having a theoretical PHB carbon yield of 0.67. Elementary mode analysis was also used to analyze the possible effects of biochemical network modifications and altered culturing conditions. When the natively absent ATP citrate-lyase activity is added to the recombinant reaction network, the number of unique modes increases from 20 to 496, with 314 of these modes producing PHB. With this topological modification, the maximum theoretical PHB carbon yield increases from 0.67 to 0.83. Adding a transhydrogenase reaction to the model also improves the theoretical conversion of substrate into PHB. The recombinant system with the transhydrogenase reaction but without the ATP citrate-lyase reaction has an increase in PHB carbon yield from 0.67 to 0.71. When the model includes both the ATP citrate-lyase reaction and the transhydrogenase reaction, the maximum theoretical carbon yield increases to 0.84. The reaction model was also used to explore the possibility of producing PHB under anaerobic conditions. In the absence of oxygen, the recombinant reaction network possesses two elementary modes capable of producing PHB. Interestingly, both modes also produce ethanol. Elementary mode analysis provides a means of deconstructing complex metabolic networks into their basic functional units. This information can be used for analyzing existing pathways and for the rational design of further modifications that could improve the system's conversion of substrate into product.

ATP Citrate (pro-S)-Lyase↗
PubMed2025

Gene and pathway analysis of genome-wide genetic associations of bladder cancer.

BACKGROUND: Although genetic variants associated with bladder cancer (BCa) risk have been identified through hypothesis-driven and genome-wide association studies, a systematic understanding of BCa genetic susceptibility at the gene and pathway levels remains to be achieved. MATERIALS AND METHODS: In this 2-stage functional genomics study, we used 5 independent tools for genome-wide gene mapping and ranking based on BCa genome-wide association studies summary statistics, followed by a meta-analysis of gene-level significance p values, to obtain a consensus gene ranking in terms of association with BCa. Subsequently, we performed preranked gene-set enrichment analysis to identify the functional pathways involved in BCa genetic susceptibility. Joint analysis with gene-set enrichment analysis, based on somatic alteration frequency, was performed to explore the pathway-level relationships between genetic susceptibility and somatic alterations in BCa. RESULTS: Other than the well-known BCa genes (such as FGFR3, MYC, TERT, CCNE1, and TP63), we additionally prioritized a set of novel genes likely to be genetically implicated in BCa development, including SETD2, a possible tumor suppressor gene involved in chromatin remodeling. We further demonstrated convergence between genetic associations and somatic alterations at both the gene (eg, FGFR3 and TERT) and pathway levels (eg, cell cycle and chromatin modification), as well as functional ontologies specifically implicated in germline predisposition to BCa (eg, CD8/TCR signaling, immune checkpoints, and cytokine signaling). CONCLUSIONS: We identified several novel genes associated with BCa and demonstrated that genetic variants contribute to the development of BCa by affecting antitumor immunity, response to toxic exposure, and RNA and protein homeostasis and synergizing with somatic alterations in various cancer-related pathways.

Bladder cancer↗
PubMed2002

In silico metabolic pathway analysis and design: succinic acid production by metabolically engineered Escherichia coli as an example.

The intracellular metabolic fluxes can be calculated by metabolic flux analysis, which uses a stoichiometric model for the intracellular reactions along with mass balances around the intracellular metabolites. In this study, we have constructed in silico metabolic pathway network of Escherichia coli consisting of 301 reactions and 294 metabolites. Metabolic flux analyses were carried out to estimate flux distributions to achieve the maximum in silico yield of succinic acid in E. coli. The maximum in silico yield of succinic acid was only 83% of its theoretical yield. The lower in silico yield of succinic acid was found to be due to the insufficient reducing power, which could be increased to its theoretical yield by supplying more reducing power. Furthermore, the optimal metabolic pathways for the production of succinic acid could be proposed based on the results of metabolic flux analyses. In the case of succinic acid production, it was found that pyruvate carboxylation pathway should be used rather than phosphoenolpyruvate carboxylation pathway for its optimal production in E. coli. Then, the in silico optimal succinic acid pathway was compared with conventional succinic acid pathway through minimum set of wet experiments. The results of wet experiments indicate that the pathway predicted by in silico analysis is more efficient than conventional pathway.

Computational Biology↗
PubMed2026

Comprehensive Genomic Profiling Timeliness Beyond Laboratory Turnaround Time: A Patient-Facing Pathway Analysis.

AIM: We evaluated the timeliness of the patient-facing comprehensive genomic profiling (CGP) pathway by separating laboratory and post-laboratory intervals within an expert panel-mediated process, using direct disclosure of results to patients as the endpoint. METHODS: This single-center retrospective study included adult CGP test episodes performed under government-funded cancer genomic medicine at a Japanese university hospital between October 2019 and November 2025. The primary outcome was patient-centered turnaround time (TAT), defined as the interval from informed consent to direct disclosure of the CGP result to the patient. Laboratory TAT and pathway intervals were summarized descriptively, and laboratory TAT was compared across assays. RESULTS: Among 882 CGP test episodes, median laboratory TAT was 14 days (interquartile range [IQR], 12-16) among 871 evaluable episodes. Among 828 evaluable episodes, median patient-centered TAT was 41 days (IQR 35-45). The laboratory analysis retained observed long intervals, including a maximum of 72 days; no episode was excluded solely because laboratory TAT exceeded 56 days. These findings indicate that laboratory TAT was only one component of the longer consent-to-disclosure pathway. CONCLUSION: In this routine-care CGP pathway, patient-facing timeliness depended on the full process from consent to direct patient disclosure. Patient-centered TAT should be monitored alongside laboratory TAT as a care-delivery measure.

comprehensive genomic profiling↗
PubMed2006

A pathway analysis of poly(I:C)-induced global gene expression change in human peripheral blood mononuclear cells.

To gain global pathway perspective of ex vivo viral infection models using human peripheral blood mononuclear cells (PBMCs), we conducted expression analysis on PBMCs of healthy donors. RNA samples were collected at 3 and 24 h after PBMCs were challenged with the Toll-like receptor-3 (TLR3) agonist polyinosinic acid-polycytidylic acid [poly(I:C)] and analyzed by internally developed cDNA microarrays and TaqMan PCR. Our results demonstrate that poly(I:C) challenge can elicit certain gene expression changes, similar to acute viral infection. Hierarchical clustering revealed distinct immediate early, early-to-late, and late gene regulation patterns. The early responses were innate immune responses that involve TLR3, the NF-kappaB-dependent pathway, and the IFN-stimulated pathway, whereas the late responses were mostly cell-mediated immune response that involve activation of cell adhesion, cell mobility, and phagocytosis. Overall, our results expanded the utilities of this ex vivo model, which could be used to screen molecules that can modulate viral stress-induced inflammation, in particular those mediated via TLRs.

Cluster Analysis↗
PubMed1998

Motor pathway analysis in HAM/TSP using magnetic stimulation and F-waves.

BACKGROUND: Tropical Spastic Paraparesis/HTLV-I Associated Myelopathy (HAM/TSP) is a chronic, progressive myelopathy endemic to the Caribbean. In HAM/TSP, peripheral motor pathways have been assessed using electromyography and nerve conduction studies; central motor pathways have been assessed to a limited extent using electrocortical stimulation. We used magnetic cortical stimulation (a painless alternative to electrocortical stimulation) and F-wave analysis to study conduction in the central and peripheral motor pathways in 18 HTLV-I seropositive, Jamaican TSP patients (ages 29-70 years; duration of symptoms 3-20 years) and 22 normal controls. METHODS: Magnetic cortical stimulation was effected using a 9 cm diameter undamped MES10 coil. F-waves and M-responses were elicited by electrical stimulation of the ulnar nerve at the wrist, and deep peroneal stimulation at the knee. Stimulation and recording of response latencies in abductor digitii minimi (ADM) and tibialis anterior (TA) were carried out using a Cadwell Excel system. RESULTS: With cortical stimulation, response latencies (TMCTs) to ADM and TA were prolonged in the patients relative to controls. F-wave and M-response latencies were unaffected, suggesting no peripheral pathology. Latency (CMCT) between cortex and lumbar cord was significantly prolonged; that between cortex and C7/T1, also, but less markedly (P < 0.0005). Amplitudes of cortically evoked responses were significantly reduced only in the lower limbs (TA). CMCT increased as the disease progressed from mild to moderate, thereafter remaining largely unchanged. CONCLUSIONS: Meta-analysis of interlaboratory control data revealed no significant differences in TMCTs between our controls and others studied using similar techniques. The observations are consistent with pathology affecting mainly the thoracolumbar cord in HAM/TSP.

Adult↗
PubMed2005

Inflammatory pathway analysis using a high content screening platform.

High content cellular screening assays are useful tools to investigate the interplay between signaling pathways and offer valuable platforms to determine the mode of action, potency, and selectivity of potential drug candidates in a biological setting. We describe a cell-based multiplex fluorescent imaging assay that permits concurrent detection and quantification of the distribution of nuclear factor kappaB (NFkappaB) p65/RelA and phosphorylated forms of p38 and c-Jun between the cytosol and nucleus. Cellular screening, data acquisition, and data interpretation were conducted on the ArrayScan HCS Reader (Cellomics Inc., Pittsburgh, PA). A significant window between untreated and interleukin-1alpha (IL-1alpha) stimulated HeLa cells for all three targets was achieved with low variability. Staining specificity was confirmed with blocking peptides and pharmacological inhibition of p38, c-Jun-N-terminal kinase (JNK), and inhibitory kappaB kinase 2, and channel bleed-through was eliminated or counterbalanced by the use of fixed exposure times together with careful reporter channel selection. The JNK inhibitor SP600125 was used as a demonstration compound because in addition to inhibiting nuclear accumulation of phosphorylated c-Jun it reduced nuclear translocation of phosphorylated p38 and NFkappaB p65/RelA in a dose-dependent manner, indicating a lack of SP600125 selectivity. This was supported by RNA interference where co-transfection of small interfering RNA targeting both JNK1 and JNK2, to limit signaling redundancy, significantly inhibited IL-1alpha-stimulated translocation of phosphorylated c-Jun without altering phosphorylated p38 and NFkappaB p65/RelA redistribution. This image analysis application is a valuable and information-rich screening tool to investigate compound selectivity and/or cross-talk between key signaling pathways involved in the inflammatory response.

Anthracenes↗
PubMed1990

Fragment pathway analysis using automated tandem mass spectrometry on an ion-trap mass spectrometer.

A "key-sequence" procedure is presented for the automated tandem mass spectrometric analysis of compounds on a Finnigan ion-trap mass spectrometer. This allows fragmentation pathways of a range of masses or even a complete spectrum to be prepared automatically, obviating the tiresome preparation and optimization of individual scan-editor files. The procedure is limited by the speed of the driving computer; an "IBM-AT", for example, permits more than 10 mass units to be scanned per minute. It is calibrated with perfluorotributylamine and methyl stearate is used to demonstrate its results. The Finnigan ion-trap "programming option" is necessary for implementation of the procedure.

Mass Spectrometry↗
PubMed2026

Global downstream BMP15 pathway analysis in human ovarian granulosa cells reveals novel genetic variations associated with primary ovarian insufficiency.

OBJECTIVES: Primary ovarian insufficiency (POI) is a fertility disorder with a well-established genetic component, but many cases still remain idiopathic. Approximately 1.5-12% of patients with POI can carry a variant in the BMP15 gene, depending on the population and the diagnostic criteria. We hypothesize that genetic variations within pathways downstream of BMP15 activity in ovarian granulosa cells (GCs) may contribute to unexplained cases of POI. The main goal of this study is to identify novel variants associated with POI in genes induced by BMP15 in GCs. STUDY DESIGN: Primary cultures of human GCs were stimulated with recombinant human BMP15. Microarray analysis profiled the BMP15-induced transcriptome in GCs. Validation was achieved by qPCR and immunoblot. Further, target exome sequencing of the differentially expressed genes was performed on 64 women with early POI onset in search of novel variants. MAIN OUTCOME MEASURES: Transcriptome profiling of human GCs stimulated with BMP15 and target exome sequencing in women with early onset of POI. RESULTS: Transcriptome analysis revealed significant upregulation of 19 genes (p&#xa0;<&#xa0;0.05). Ontology analysis of these genes converged towards two main pathways: TGF-beta signaling and regulation of stem cell pluripotency. Target exome sequencing identified six novel rare variants in five BMP15-induced genes (SAMD11, SMAD6, ID1, USP35, GPCR137C) in 9 of the 64 women with early POI (14%). CONCLUSIONS: BMP15 action in human ovarian GCs defines TGF-beta signaling and pluripotency fate in ovarian follicles. In addition, this study uncovers new potential candidate genes for the pathogenesis of POI.

Humans↗
PubMed2000

Pathway analysis in metabolic databases via differential metabolic display (DMD).

MOTIVATION: A number of metabolic databases are available electronically, some with features for querying and visualizing metabolic pathways and regulatory networks. We present a unifying, systematic approach based on PETRI nets for storing, displaying, comparing, searching and simulating such nets from a number of different sources. RESULTS: Information from each data source is extracted and compiled into a PETRI net. Such PETRI nets then allow to investigate the (differential) content in metabolic databases, to map and integrate genomic information and functional annotations, to compare sequence and metabolic databases with respect to their functional annotations, and to define, generate and search paths and pathways in nets. We present an algorithm to systematically generate all pathways satisfying additional constraints in such PETRI nets. Finally, based on the set of valid pathways, so-called differential metabolic displays (DMDs) are introduced to exhibit specific differences between biological systems, i.e. different developmental states, disease states, or different organisms, on the level of paths and pathways. DMDs will be useful for target finding and function prediction, especially in the context of the interpretation of expression data.

Algorithms↗
PubMed2004

Molecular characterization and IFN signal pathway analysis of Carassius auratus CaSTAT1 identified from the cultured cells in response to virus infection.

Type I interferon (IFN) exerts its pleiotropic effects mainly through the JAK-STAT signaling pathway, which is presently best described in mammals. By subtractive suppression hybridization, two fish signaling factors, JAK1 and STAT1, had been identified in the IFN-induced crucian carp Carassius auratus L. blastulae embryonic (CAB) cells after treatment with UV-inactivated grass carp hemorrhagic virus (GCHV). Further, the full-length cDNA of STAT1, termed CaSTAT1, was obtained. It contains 2926 bp and encodes a protein of 718 aa. CaSTAT1 is most similar to rat STAT1 with 59% identity overall and displays all highly conserved domains that the STAT family possesses. Like human STAT1beta, it lacks the C-terminus acting as transcriptional activation domain in mammals. By contrast, only a single transcript was detected in virus-induced CAB cells. Expression analysis showed that CaSTAT1 could be activated by stimulation of CAB cells with poly I:C, active GCHV, UV-inactivated GCHV or CAB IFN, and displayed diverse expression patterns similar to that of mammalian STAT1. Additionally, the expression of an antiviral gene CaMx1 was also induced under the same conditions, and expression difference between CaSTAT1 and CaMx1 was revealed by induction of CAB IFN. These results provide molecular evidence supporting the notion that the fish IFN signaling transduction pathway is similar to that in mammals. Fish IFN exerts its multiple functions, at least antiviral action, through a JAK-STAT pathway.

Amino Acid Sequence↗
PubMed2026

Virtual reality physical education and adolescents' exercise interest and physical fitness: An explanatory sequential mixed-methods randomized trial with exploratory pathway analysis.

Traditional physical education (PE) faces declining student interest and limited fitness gains. Virtual reality (VR) offers immersive, gamified experiences, but evidence regarding its effectiveness and explanatory pathways remains limited. This explanatory sequential mixed-methods randomized trial assigned 360 adolescents (aged 13-16) from three middle schools to either VR-supported PE (n&#xa0;=&#xa0;180) or conventional PE (n&#xa0;=&#xa0;180) for 12&#xa0;weeks, with a 4-week follow-up. Outcomes included exercise interest (validated scale), physical fitness (coordination via MABC-2, cardiorespiratory endurance via the 20-m shuttle run, explosive power via the standing long jump, and speed via the 10-m sprint), and accelerometer-measured physical activity. The qualitative component involved 38 unique students: 32 completed individual semi-structured interviews, and six additional students participated only in focus groups. Three-level linear mixed-effects models and exploratory structural equation modeling were used. The VR group showed significantly greater improvements in exercise interest (d&#xa0;=&#xa0;0.78), coordination (d&#xa0;=&#xa0;0.62), cardiorespiratory endurance (d&#xa0;=&#xa0;0.55), and speed (d&#xa0;=&#xa0;0.48) than the control group (all p&#xa0;<&#xa0;0.001), but not in explosive power (d&#xa0;=&#xa0;0.12, p&#xa0;=&#xa0;0.148). Effects were partially retained at follow-up (interest d&#xa0;=&#xa0;0.65, coordination d&#xa0;=&#xa0;0.48, endurance d&#xa0;=&#xa0;0.42, and speed d&#xa0;=&#xa0;0.30), a pattern not fully consistent with a purely novelty-driven explanation. Exploratory mediation identified exercise interest as a statistically compatible explanatory pathway (indirect effect&#xa0;=&#xa0;0.34, 95% CI [0.22, 0.46]), although the timing of measurement precludes causal interpretation. Qualitative findings contextualized these results by highlighting immersion, feedback, self-efficacy, and perceived transfer. VR-supported PE may enhance adolescents' exercise interest and selected fitness dimensions, but its limited effect on explosive power and possible novelty contribution indicate that it should complement, rather than replace, conventional PE. Longer-term studies are needed.

Humans↗
PubMed2006

Multiple gene expression analyses in paraffin-embedded tissues by TaqMan low-density array: Application to hedgehog and Wnt pathway analysis in ovarian endometrioid adenocarcinoma.

Recent studies have shown the hedgehog and Wnt families of signaling proteins to be associated with tumor initiation, growth, and survival. However, these pathways remain unexplored in ovarian endometrioid adenocarcinoma (OEA). Here, we describe a novel TaqMan low-density array to examine the expression of 26 and 20 genes in the hedgehog and Wnt pathways, respectively, in six matched snap-frozen and formalin-fixed, paraffin-embedded (FPE) OEA specimens. Expression values were normalized to uninvolved ovarian epithelium. Gene expression in matched frozen and FPE tissues demonstrated significant concordance (r = 0.92, P < 0.0001). However, comparison of amplified and unamplified RNA from frozen OEA tissues revealed an altered molecular profile in amplified RNA. Amplification of RNA from FPE tissues was not successful. The expression of Desert hedgehog (DHH), Indian hedgehog (IHH), Hedge-hog interacting protein (HHIP), Wnt10B, Wnt9B, and Wnt inhibitory factor (WIF1) were tumor-specific with no detectable expression in normal ovarian epithelium. In addition, several genes were significantly (P < 0.025) down-regulated in OEA, including cyclin E2, Porcupine, c-Myc, and Axin 2 (4.8-, 3.6-, 2.9-, and 1.9-fold, respectively). TaqMan low-density array provides an effective multivariate technique for examining gene expression in RNA isolated from either snap-frozen or archival FPE tissues and can identify tumor-specific genes, possibly leading to novel treatments.

Animals↗
PubMed2002

Extreme pathway analysis of human red blood cell metabolism.

The development of high-throughput technologies and the resulting large-scale data sets have necessitated a systems approach to the analysis of metabolic networks. One way to approach the issue of complex metabolic function is through the calculation and interpretation of extreme pathways. Extreme pathways are a mathematically defined set of generating vectors that describe the conical steady-state solution space for flux distributions through an entire metabolic network. Herein, the extreme pathways of the well-characterized human red blood cell metabolic network were calculated and interpreted in a biochemical and physiological context. These extreme pathways were divided into groups based on such criteria as their cofactor and by-product production, and carbon inputs including those that 1) convert glucose to pyruvate; 2) interchange pyruvate and lactate; 3) produce 2,3-diphosphoglycerate that binds to hemoglobin; 4) convert inosine to pyruvate; 5) induce a change in the total adenosine pool; and 6) dissipate ATP. Additionally, results from a full kinetic model of red blood cell metabolism were predicted based solely on an interpretation of the extreme pathway structure. The extreme pathways for the red blood cell thus give a concise representation of red blood cell metabolism and a way to interpret its metabolic physiology.

2,3-Diphosphoglycerate↗
PubMed2006

Mining literature for a comprehensive pathway analysis: a case study for retrieval of homocysteine related genes for genetic and epigenetic studies.

Homocysteine is an independent risk factor for cardiovascular diseases. It is also known to be associated with a variety of complex disorders. While there are a large number of independent studies implicating homocysteine in isolated pathways, the mechanism of homocysteine induced adverse effects are not clear. Homocysteine-induced modulation of gene expression through alteration of methylation status or by hitherto unknown mechanisms is predicted to lead to several pathological conditions either directly or indirectly. In the present manuscript, using literature mining approach, we have identified the genes that are modulated directly or indirectly by an elevated level of homocysteine. These genes were then placed in appropriate pathways in an attempt to understand the molecular basis of homocysteine induced complex disorders and to provide a resource for selection of genes for polymorphism screening and analysis of mutations as well as epigenetic modifications in relation to hyperhomocysteinemia. We have identified 135 genes in 1137 abstracts that either modulate the levels of homocysteine or are modulated by elevated levels of homocysteine. Mapping the genes to their respective pathways revealed that an elevated level of homocysteine leads to the atherosclerosis either by directly affecting lipid metabolism and transport or via oxidative stress and/or Endoplasmic Reticulum (ER) stress. Elevated levels of homocysteine also decreases the bioavailability of nitric oxide and modulates the levels of other metabolites including S-adenosyl methionine and S-adenosyl homocysteine which may result in cardiovascular or neurological disorders. The ER stress emerges as the common pathway that relates to apoptosis, atherosclerosis and neurological disorders and is modulated by levels of homocysteine. The comprehensive network collated has lead to the identification of genes that are modulated by homocysteine indicating that homocysteine exerts its effect not only through modulating the substrate levels for various catalytic processes but also through regulation of expression of genes involved in complex diseases.

Animals↗
PubMed2006

Group testing for pathway analysis improves comparability of different microarray datasets.

MOTIVATION: The wide use of DNA microarrays for the investigation of the cell transcriptome triggered the invention of numerous methods for the processing of microarray data and lead to a growing number of microarray studies that examine the same biological conditions. However, comparisons made on the level of gene lists obtained by different statistical methods or from different datasets hardly converge. We aimed at examining such discrepancies on the level of apparently affected biologically related groups of genes, e.g. metabolic or signalling pathways. This can be achieved by group testing procedures, e.g. over-representation analysis, functional class scoring (FCS), or global tests. RESULTS: Three public prostate cancer datasets obtained with the same microarray platform (HGU95A/HGU95Av2) were analyzed. Each dataset was subjected to normalization by either variance stabilizing normalization (vsn) or mixed model normalization (MMN). Then, statistical analysis of microarrays was applied to the vsn-normalized data and mixed model analysis to the data normalized by MMN. For multiple testing adjustment the false discovery rate was calculated and the threshold was set to 0.05. Gene lists from the same method applied to different datasets showed overlaps between 42 and 52%, while lists from different methods applied to the same dataset had between 63 and 85% of genes in common. A number of six gene lists obtained by the two statistical methods applied to the three datasets was then subjected to group testing by Fisher's exact test. Group testing by GSEA and global test was applied to the three datasets, as well. Fisher's exact test followed by global test showed more consistent results with respect to the concordance between analyses on gene lists obtained by different methods and different datasets than the GSEA. However, all group testing methods identified pathways that had already been described to be involved in the pathogenesis of prostate cancer. Moreover, pathways recurrently identified in these analyses are more likely to be reliable than those from a single analysis on a single dataset.

Biomarkers, Tumor↗