Analysis of single-cell RNA sequencing data based on autoencoders.

BACKGROUND: Single-cell RNA sequencing (scRNA-Seq) experiments are gaining ground to study the molecular processes that drive normal development as well as the onset of different pathologies. Finding an effective and efficient low-dimensional representation of the data is one of the most important steps in the downstream analysis of scRNA-Seq data, as it could provide a better identification of known or putatively novel cell-types. Another step that still poses a challenge is the integration of different scRNA-Seq datasets. Though standard computational pipelines to gain knowledge from scRNA-Seq data exist, a further improvement could be achieved by means of machine learning approaches. RESULTS: Autoencoders (AEs) have been effectively used to capture the non-linearities among gene interactions of scRNA-Seq data, so that the deployment of AE-based tools might represent the way forward in this context. We introduce here scAEspy, a unifying tool that embodies: (1) four of the most advanced AEs, (2) two novel AEs that we developed on purpose, (3) different loss functions. We show that scAEspy can be coupled with various batch-effect removal tools to integrate data by different scRNA-Seq platforms, in order to better identify the cell-types. We benchmarked scAEspy against the most used batch-effect removal tools, showing that our AE-based strategies outperform the existing solutions. CONCLUSIONS: scAEspy is a user-friendly tool that enables using the most recent and promising AEs to analyse scRNA-Seq data by only setting up two user-defined parameters. Thanks to its modularity, scAEspy can be easily extended to accommodate new AEs to further improve the downstream analysis of scRNA-Seq data. Considering the relevant results we achieved, scAEspy can be considered as a starting point to build a more comprehensive toolkit designed to integrate multi single-cell omics.

Pedunculated and telangiectatic merkel cell carcinoma: an unusual clinical presentation.

Merkel cell carcinoma (MCC) is an uncommon aggressive neuroendocrine tumor of the skin that classically presents on chronic sun-damaged skin as a skin-colored, red or violaceous, firm and nontender papule or nodule with a smooth and shiny surface. Ulcerations can be observed very seldom and only in very advanced lesions. We present a unique case of a MCC presenting with two unusual clinical features: The Telangiectatic surface and the pedunculated aspect.

Dactylolysis spontanea or ainhum involving the big toe.

We describe the case of an Italian Caucasian man with ainhum involving both big toes. Ainhum or dactylolysis spontanea is characterized by the development of a constricting band around a toe, which progresses to spontaneous autoamputation. It usually affects the fifth toe bilaterally, but in rare cases other toes may be involved. The disease occurs in Black people living in tropical regions but occasionally has been reported in persons having fair skin.