Identifying differentially expressed genes (DEG) is a fundamental step in studies that perform genome wide expression profiling. Typically, DEG are identified by univariate approaches such as ...Significance Analysis of Microarrays (SAM) or Linear Models for Microarray Data (LIMMA) for processing cDNA microarrays, and differential gene expression analysis based on the negative binomial distribution (DESeq) or Empirical analysis of Digital Gene Expression data in R (edgeR) for RNA-seq profiling.
Here we present a new geometrical multivariate approach to identify DEG called the Characteristic Direction. We demonstrate that the Characteristic Direction method is significantly more sensitive than existing methods for identifying DEG in the context of transcription factor (TF) and drug perturbation responses over a large number of microarray experiments. We also benchmarked the Characteristic Direction method using synthetic data, as well as RNA-Seq data. A large collection of microarray expression data from TF perturbations (73 experiments) and drug perturbations (130 experiments) extracted from the Gene Expression Omnibus (GEO), as well as an RNA-Seq study that profiled genome-wide gene expression and STAT3 DNA binding in two subtypes of diffuse large B-cell Lymphoma, were used for benchmarking the method using real data. ChIP-Seq data identifying DNA binding sites of the perturbed TFs, as well as known drug targets of the perturbing drugs, were used as prior knowledge silver-standard for validation. In all cases the Characteristic Direction DEG calling method outperformed other methods. We find that when drugs are applied to cells in various contexts, the proteins that interact with the drug-targets are differentially expressed and more of the corresponding genes are discovered by the Characteristic Direction method. In addition, we show that the Characteristic Direction conceptualization can be used to perform improved gene set enrichment analyses when compared with the gene-set enrichment analysis (GSEA) and the hypergeometric test.
The application of the Characteristic Direction method may shed new light on relevant biological mechanisms that would have remained undiscovered by the current state-of-the-art DEG methods. The method is freely accessible via various open source code implementations using four popular programming languages: R, Python, MATLAB and Mathematica, all available at: http://www.maayanlab.net/CD.
Abstract
While gene expression data at the mRNA level can be globally and accurately measured, profiling the activity of cell signaling pathways is currently much more difficult. eXpression2Kinases ...(X2K) computationally predicts involvement of upstream cell signaling pathways, given a signature of differentially expressed genes. X2K first computes enrichment for transcription factors likely to regulate the expression of the differentially expressed genes. The next step of X2K connects these enriched transcription factors through known protein-protein interactions (PPIs) to construct a subnetwork. The final step performs kinase enrichment analysis on the members of the subnetwork. X2K Web is a new implementation of the original eXpression2Kinases algorithm with important enhancements. X2K Web includes many new transcription factor and kinase libraries, and PPI networks. For demonstration, thousands of gene expression signatures induced by kinase inhibitors, applied to six breast cancer cell lines, are provided for fetching directly into X2K Web. The results are displayed as interactive downloadable vector graphic network images and bar graphs. Benchmarking various settings via random permutations enabled the identification of an optimal set of parameters to be used as the default settings in X2K Web. X2K Web is freely available from http://X2K.cloud.
Identification of differentially expressed genes is an important step in extracting knowledge from gene expression profiling studies. The raw expression data from microarray and other high-throughput ...technologies is deposited into the Gene Expression Omnibus (GEO) and served as Simple Omnibus Format in Text (SOFT) files. However, to extract and analyze differentially expressed genes from GEO requires significant computational skills.
Here we introduce GEO2Enrichr, a browser extension for extracting differentially expressed gene sets from GEO and analyzing those sets with Enrichr, an independent gene set enrichment analysis tool containing over 70 000 annotated gene sets organized into 75 gene-set libraries. GEO2Enrichr adds JavaScript code to GEO web-pages; this code scrapes user selected accession numbers and metadata, and then, with one click, users can submit this information to a web-server application that downloads the SOFT files, parses, cleans and normalizes the data, identifies the differentially expressed genes, and then pipes the resulting gene lists to Enrichr for downstream functional analysis. GEO2Enrichr opens a new avenue for adding functionality to major bioinformatics resources such GEO by integrating tools and resources without the need for a plug-in architecture. Importantly, GEO2Enrichr helps researchers to quickly explore hypotheses with little technical overhead, lowering the barrier of entry for biologists by automating data processing steps needed for knowledge extraction from the major repository GEO.
GEO2Enrichr is an open source tool, freely available for installation as browser extensions at the Chrome Web Store and FireFox Add-ons. Documentation and a browser independent web application can be found at http://amp.pharm.mssm.edu/g2e/.
avi.maayan@mssm.edu.
Fully Homomorphic Encryption (FHE) allows computing on encrypted data, enabling secure offloading of computation to untrusted servers. Though it provides ideal security, FHE is expensive when ...executed in software, 4 to 5 orders of magnitude slower than computing on unencrypted data. These overheads are a major barrier to FHE's widespread adoption.;
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We present F1, the first FHE accelerator that is programmable, i.e., capable of executing full FHE programs. F1 builds on an in-depth architectural analysis of the characteristics of FHE computations that reveals acceleration opportunities. F1 is a wide-vector processor with novel functional units deeply specialized to FHE primitives, such as modular arithmetic, number-theoretic transforms, and structured permutations.;
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Due to the static nature of FHE computations, F1 uses an exposed ISA, requiring novel compilation techniques to statically schedule all compute and data movement. We design a compiler that efficiently maps FHE programs onto F1 hardware and maximizes reuse of on-chip data, helping to reduce data movement bottlenecks. The compiler leverages F1's explicitly managed scratchpad to decouple computation from data movement, a necessary ingredient in achieving high performance given the large size of FHE operands.;
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We evaluate F1 using cycle-accurate simulation and RTL synthesis. F1 is the first system to accelerate complete FHE programs, and outperforms state-of-the-art software implementations by gmean 6,500x and by up to 17,000x. These speedups counter most of FHE's overheads and enable new applications, like real-time private deep learning in the cloud.
S.M.
After the very successful ECC-Book on `E-conomy` this new report of the European Communication Council (ECC) analyzes from various perspectives the profound societal and economical change of the ...media economy, initiated by digitalization and networking. Against the background of the current media history, it highlights for example the role of the Internet hype as a pathfinder in a modified media society. The key question is concerned with how the medial future will be like. The report examines effects and new perspectives in the area of economy, society, and politics. The aspects of behavior, business models, legal and regulation questions, self-conception of society and media economy are mooted by international authors to enhance the reader`s understanding of the medial future and to disclose options for action.
Abstract Background Local failure after radical prostatectomy (RP) is common in patients with cancer extending beyond the capsule. Three prospectively randomized trials demonstrated an advantage for ...adjuvant radiotherapy (ART) compared with a wait-and-see (WS) policy. Objective To determine the efficiency of ART after a 10-yr follow-up in the ARO 96–02 study. Design, setting, and participants After RP, 388 patients with pT3 pN0 prostate cancer (PCa) were randomized to WS or three-dimensional conformal ART with 60 Gy. The present analysis focuses on intent-to-treat patients who achieved an undetectable prostate-specific antigen after RP (ITT2 population)—that is, 159 WS plus 148 ART men. Outcome measurements and statistical analysis The primary end point of the study was progression-free survival (PFS) (events: biochemical recurrence, clinical recurrence, or death). Outcomes were compared by log-rank test. Cox regression analysis served to identify variables influencing the course of disease. Results and limitations The median follow-up was 111 mo for ART and 113 mo for WS. At 10 yr, PFS was 56% for ART and 35% for WS ( p < 0.0001). In pT3b and R1 patients, the rates for WS even dropped to 28% and 27%, respectively. Of all 307 ITT2 patients, 15 died from PCa, and 28 died for other or unknown reasons. Neither metastasis-free survival nor overall survival was significantly improved by ART. However, the study was underpowered for these end points. The worst late sequelae in the ART cohort were one grade 3 and three grade 2 cases of bladder toxicity and two grade 2 cases of rectum toxicity. No grade 4 events occurred. Conclusions Compared with WS, ART reduced the risk of (biochemical) progression with a hazard ratio of 0.51 in pT3 PCa. With only one grade 3 case of late toxicity, ART was safe. Patient summary Precautionary radiotherapy counteracts relapse after surgery for prostate cancer with specific risk factors.
Local failure after radical prostatectomy (RP) is common in patients with cancer extending beyond the capsule. Two randomized trials demonstrated an advantage for adjuvant radiotherapy (RT) compared ...with a wait-and-see policy. We conducted a randomized, controlled clinical trial to compare RP followed by immediate RT with RP alone for patients with pT3 prostate cancer and an undetectable prostate-specific antigen (PSA) level after RP.
After RP, 192 men were randomly assigned to a wait-and-see policy, and 193 men were assigned to immediate postoperative RT. Eligible patients had pT3 pN0 tumors. Patients who did not achieve an undetectable PSA after RP were excluded from treatment according to random assignment (n = 78; 20%). Of the remaining 307 patients, 34 patients on the RT arm did not receive RT and five patients on the wait-and-see arm received RT. Therefore, 114 patients underwent RT and 154 patients were treated with a wait-and-see policy. The primary end point was biochemical progression-free survival.
Biochemical progression-free survival after 5 years in patients with undetectable PSA after RP was significantly improved in the RT group (72%; 95% CI, 65% to 81%; v 54%, 95% CI, 45% to 63%; hazard ratio = 0.53; 95% CI, 0.37 to 0.79; P = .0015). On univariate analysis, Gleason score more than 6 and less than 7, PSA before RP, tumor stage, and positive surgical margins were predictors of outcome. The rate of grade 3 to 4 late adverse effects was 0.3%.
Adjuvant RT for pT3 prostate cancer with postoperatively undetectable PSA significantly reduces the risk of biochemical progression. Further follow-up is needed to assess the effect on metastases-free and overall survival.
The ARO 96-02 trial primarily compared wait-and-see (WS, arm A) with adjuvant radiation therapy (ART, arm B) in prostate cancer patients who achieved an undetectable prostate-specific antigen (PSA) ...after radical prostatectomy (RP). Here, we report the outcome with up to 12 years of follow-up of patients who retained a post-RP detectable PSA and received salvage radiation therapy (SRT, arm C).
For the study, 388 patients with pT3-4pN0 prostate cancer with positive or negative surgical margins were recruited. After RP, 307 men achieved an undetectable PSA (arms A + B). In 78 patients the PSA remained above thresholds (median 0.6, range 0.05-5.6 ng/mL). Of the latter, 74 consented to receive 66 Gy to the prostate bed, and SRT was applied at a median of 86 days after RP. Clinical relapse-free survival, metastasis-free survival, and overall survival were determined by the Kaplan-Meier method.
Patients with persisting PSA after RP had higher preoperative PSA values, higher tumor stages, higher Gleason scores, and more positive surgical margins than did patients in arms A + B. For the 74 patients, the 10-year clinical relapse-free survival rate was 63%. Forty-three men had hormone therapy; 12 experienced distant metastases; 23 patients died. Compared with men who did achieve an undetectable PSA, the arm-C patients fared significantly worse, with a 10-year metastasis-free survival of 67% versus 83% and overall survival of 68% versus 84%, respectively. In Cox regression analysis, Gleason score ≥8 (hazard ratio HR 2.8), pT ≥ 3c (HR 2.4), and extraprostatic extension ≥2 mm (HR 3.6) were unfavorable risk factors of progression.
A persisting PSA after prostatectomy seems to be an important prognosticator of clinical progression for pT3 tumors. It correlates with a higher rate of distant metastases and with worse overall survival. A larger prospective study is required to determine which patient subgroups will benefit most from which treatment option.
Fully Homomorphic Encryption (FHE) allows computing on encrypted data, enabling secure offloading of computation to untrusted servers. Though it provides ideal security, FHE is expensive when ...executed in software, 4 to 5 orders of magnitude slower than computing on unencrypted data. These overheads are a major barrier to FHE’s widespread adoption.
We present F1, the first FHE accelerator that is programmable, i.e., capable of executing full FHE programs. F1 builds on an in-depth architectural analysis of the characteristics of FHE computations that reveals acceleration opportunities. F1 is a wide-vector processor with novel functional units deeply specialized to FHE primitives, such as modular arithmetic, number-theoretic transforms, and structured permutations. This organization provides so much compute throughput that data movement becomes the key bottleneck. Thus, F1 is primarily designed to minimize data movement. Hardware provides an explicitly managed memory hierarchy and mechanisms to decouple data movement from execution. A novel compiler leverages these mechanisms to maximize reuse and schedule off-chip and on-chip data movement.
We evaluate F1 using cycle-accurate simulation and RTL synthesis. F1 is the first system to accelerate complete FHE programs, and outperforms state-of-the-art software implementations by gmean 5,400 × and by up to 17,000 ×. These speedups counter most of FHE’s overheads and enable new applications, like real-time private deep learning in the cloud.
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