aPEAch: Automated Pipeline for End-to-End Analysis of Epigenomic and Transcriptomic Data.

With the advent of next-generation sequencing (NGS), experimental techniques that capture the biological significance of DNA loci or RNA molecules have emerged as fundamental tools for studying the epigenome and transcriptional regulation on a genome-wide scale. The volume of the generated data and the underlying complexity regarding their analysis highlight the need for robust and easy-to-use computational analytic methods that can streamline the process and provide valuable biological insights. Our solution, aPEAch, is an automated pipeline that facilitates the end-to-end analysis of both DNA- and RNA-sequencing assays, including small RNA sequencing, from assessing the quality of the input sample files to answering meaningful biological questions by exploiting the rich information embedded in biological data.

Transcriptomic meta-analysis characterizes molecular commonalities between psoriasis and obesity.

Despite the abundance of epidemiological evidence for the high comorbid rate between psoriasis and obesity, systematic approaches to common inflammatory mechanisms have not been adequately explored. We performed a meta-analysis of publicly available RNA-sequencing datasets to unveil putative mechanisms that are postulated to exacerbate both diseases, utilizing both late-stage, disease-specific meta-analyses and consensus gene co-expression network (cWGCNA). Single-gene meta-analyses reported several common inflammatory mechanisms fostered by the perturbed expression profile of inflammatory cells.

Transcriptional repression of lncRNA and miRNA subsets mediated by LRF during erythropoiesis.

Non-coding RNA (ncRNA) species, mainly long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have been currently imputed for lesser or greater involvement in human erythropoiesis. These RNA subsets operate within a complex circuit with other epigenetic components and transcription factors (TF) affecting chromatin remodeling during cell differentiation. Lymphoma/leukemia-related (LRF) TF exerts higher occupancy on DNA CpG rich sites and is implicated in several differentiation cell pathways and erythropoiesis among them and also directs the epigenetic regulation of hemoglobin transversion from fetal (HbF) to adult (HbA) form by intervening in the γ-globin gene repression.

Pharmacogenetic Analysis of the rs2910164 and rs767649 Polymorphisms and Response to Anti-TNF Treatment in Patients with Crohn's Disease and Psoriasis.

The clinical heterogeneity regarding the response profile of the antitumor necrosis factor (anti-TNF) in patients with Crohn's disease (CD) and psoriasis (PsO) is attributed, amongst others, to genetic factors that influence the regulatory mechanisms which orchestrate the inflammatory response. Here, we investigated the possible associations between the rs2910164 and rs767649 variants and the response to anti-TNF therapy in a Greek cohort of 103 CD and 100 PsO patients. We genotyped 103 CD patients and 100 PsO patients via the PCR-RFLP method, utilizing the de novo formation of a restriction site for the SacI enzyme considering the rs2910164, while Tsp45I was employed for the rs767649 variant.

DeepTSS: multi-branch convolutional neural network for transcription start site identification from CAGE data.

Background: The widespread usage of Cap Analysis of Gene Expression (CAGE) has led to numerous breakthroughs in understanding the transcription mechanisms. Recent evidence in the literature, however, suggests that CAGE suffers from transcriptional and technical noise. Regardless of the sample quality, there is a significant number of CAGE peaks that are not associated with transcription initiation events.

Machine-Learning-Assisted Analysis of TCR Profiling Data Unveils Cross-Reactivity between SARS-CoV-2 and a Wide Spectrum of Pathogens and Other Diseases.

During the last two years, the emergence of SARS-CoV-2 has led to millions of deaths worldwide, with a devastating socio-economic impact on a global scale. The scientific community's focus has recently shifted towards the association of the T cell immunological repertoire with COVID-19 progression and severity, by utilising T cell receptor sequencing (TCR-Seq) assays. The Multiplexed Identification of T cell Receptor Antigen (MIRA) dataset, which is a subset of the immunoACCESS study, provides thousands of TCRs that can specifically recognise SARS-CoV-2 epitopes.

Contribution of the Environment, Epigenetic Mechanisms and Non-Coding RNAs in Psoriasis.

Despite the increasing research and clinical interest in the predisposition of psoriasis, a chronic inflammatory skin disease, the multitude of genetic and environmental factors involved in its pathogenesis remain unclear. This complexity is further exacerbated by the several cell types that are implicated in Psoriasis's progression, including keratinocytes, melanocytes and various immune cell types. The observed interactions between the genetic substrate and the environment lead to epigenetic alterations that directly or indirectly affect gene expression.

Gene Expression Meta-Analysis of Potential Shared and Unique Pathways between Autoimmune Diseases under Anti-TNFα Therapy.

While anti-TNFα has been established as an effective therapeutic approach for several autoimmune diseases, results from clinical trials have uncovered heterogeneous patients' response to therapy. Here, we conducted a meta-analysis on the publicly available gene expression cDNA microarray datasets that examine the differential expression observed in response to anti-TNFα therapy with psoriasis (PsO), inflammatory bowel disease (IBD) and rheumatoid arthritis (RA). Five disease-specific meta-analyses and a single combined random-effects meta-analysis were performed through the restricted maximum likelihood method.

DIANA-miRGen v4: indexing promoters and regulators for more than 1500 microRNAs.

Deregulation of microRNA (miRNA) expression plays a critical role in the transition from a physiological to a pathological state. The accurate miRNA promoter identification in multiple cell types is a fundamental endeavor towards understanding and characterizing the underlying mechanisms of both physiological as well as pathological conditions. DIANA-miRGen v4 (www.

Multi-branch Convolutional Neural Network for Identification of Small Non-coding RNA genomic loci.

Genomic regions that encode small RNA genes exhibit characteristic patterns in their sequence, secondary structure, and evolutionary conservation. Convolutional Neural Networks are a family of algorithms that can classify data based on learned patterns. Here we present MuStARD an application of Convolutional Neural Networks that can learn patterns associated with user-defined sets of genomic regions, and scan large genomic areas for novel regions exhibiting similar characteristics.

Solving the transcription start site identification problem with ADAPT-CAGE: a Machine Learning algorithm for the analysis of CAGE data.

Cap Analysis of Gene Expression (CAGE) has emerged as a powerful experimental technique for assisting in the identification of transcription start sites (TSSs). There is strong evidence that CAGE also identifies capping sites along various other locations of transcribed loci such as splicing byproducts, alternative isoforms and capped molecules overlapping introns and exons. We present ADAPT-CAGE, a Machine Learning framework which is trained to distinguish between CAGE signal derived from TSSs and transcriptional noise.

A Cosine Similarity-Based Method to Infer Variability of Chromatin Accessibility at the Single-Cell Level.

Cellular identity between generations of developing cells is propagated through the epigenome particularly via the accessible parts of the chromatin. It is now possible to measure chromatin accessibility at single-cell resolution using single-cell assay for transposase accessible chromatin (scATAC-seq), which can reveal the regulatory variation behind the phenotypic variation. However, single-cell chromatin accessibility data are sparse, binary, and high dimensional, leading to unique computational challenges.