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The dataset contains raw and intermediated files, and scripts required to reproduce the results associated with the manuscript "Assigning transcriptomic subtypes to CLL samples using nanopore RNA-sequencing and self-organizing maps". Here, we demonstrate that integrating publicly available short-read data with in-house generated ONT data, along with the application of machine learning approaches, enables the characterization of the CLL transcriptome landscape, the identification of clinically ...
Creator: Arsen Arakelyan
Submitter: Lana Karapetyan
This is a supplementary dataset with raw data, scripts, and complete analysis results for the paper "Supervised projection of high-dimensional genome-wide expression on SOM transcriptome landscapes".
The archive contains three folders:
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"Simdata" folder contains data, scripts, and results of performance evaluation of extension SOM and supervised SOM with simulated data.
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"IBD" - folder contains data, scripts, and results of analysis of Inflammatory bowel disease datasets.
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"BC" - folder ...
Creators: Maria Nikoghosyan, Suren Davitavyan, Hans Binder, Arsen Arakelyan
Submitter: Lana Karapetyan
This is the submission accompanying the "Telomere Maintenance Pathways in Lower-Grade Gliomas: Insights from Genetic Subtypes and Telomere Length Dynamics" paper.
The dataset contains the TCGA and CGGA LGG
The dataset is organized as follows:
Folder "CGGA_LGG_IDH_subtype_mean_vis" - The CGGAL GG data IDH subtype pathway visualization and CSV data. Folder "Long_Short_telomeres_path_vis" - The TCGA LGG data ALT and TEL pathway visualization for Long and Short telomeres mean values. Folder ...
Creators: Arsen Arakelyan, Meline Hakobyan, Hans Binder
Submitter: Arsen Arakelyan
Sequencing raw data.
Creators: Arsen Arakelyan, Siras Hakobyan
Submitter: Arsen Arakelyan
This dataset provides data necessary to replicate the results of the time-perturbation analysis of gene expression in health and mental disorders. The corresponding code is available in the GitHub repository under the https://github.com/susieavagyan/BrainExp-TemporalDynamics link.
Creator: Arsen Arakelyan
Submitter: Arsen Arakelyan
This dataset provides data necessary to replicate the results of the time-perturbation analysis of gene expression in health and mental disorders. The corresponding code is available in the GitHub repository under the https://github.com/susieavagyan/BrainExp-TemporalDynamics link.
Creator: Arsen Arakelyan
Submitter: Arsen Arakelyan