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      Patched 1 expression in Merkel cell carcinoma

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          limma powers differential expression analyses for RNA-sequencing and microarray studies

          limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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            Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.

            The recently released Infinium HumanMethylation450 array (the '450k' array) provides a high-throughput assay to quantify DNA methylation (DNAm) at ∼450 000 loci across a range of genomic features. Although less comprehensive than high-throughput sequencing-based techniques, this product is more cost-effective and promises to be the most widely used DNAm high-throughput measurement technology over the next several years. Here we describe a suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data. The software is structured to easily adapt to future versions of the technology. We include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale. We show how our software provides a powerful and flexible development platform for future methods. We also illustrate how our methods empower the technology to make discoveries previously thought to be possible only with sequencing-based methods. http://bioconductor.org/packages/release/bioc/html/minfi.html. khansen@jhsph.edu; rafa@jimmy.harvard.edu Supplementary data are available at Bioinformatics online.
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              Targeting the Hedgehog pathway in cancer.

              Several key signalling pathways, such as Hedgehog, Notch, Wnt and BMP-TGFbeta-Activin (bone morphogenetic protein-transforming growth factor-beta-Activin), are involved in most processes essential to the proper development of an embryo. It is also becoming increasingly clear that these pathways can have a crucial role in tumorigenesis when reactivated in adult tissues through sporadic mutations or other mechanisms. We will focus here on the Hedgehog pathway, which is abnormally activated in most basal cell carcinomas, and discuss potential therapeutic opportunities offered by the progress made in understanding this signalling pathway.
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                Author and article information

                Contributors
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                Journal
                The Journal of Dermatology
                J. Dermatol.
                Wiley
                0385-2407
                1346-8138
                January 2021
                November 12 2020
                January 2021
                : 48
                : 1
                : 64-74
                Affiliations
                [1 ]Department of Dermatology Skin Cancer Center Ruhr‐University Bochum BochumGermany
                [2 ]National Reference Center for Papilloma‐ and Polyomaviruses Institute of Virology University of Cologne CologneGermany
                [3 ]Department of Dermatology Translational Skin Cancer ResearchGerman Cancer Consortium (DKTK) Partner Site Essen/DüsseldorfUniversity Duisburg‐Essen EssenGermany
                [4 ]Deutsches Krebsforschungszentrum (DKFZ) Heidelberg Germany
                Article
                10.1111/1346-8138.15611
                © 2021

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