Data files

oposSOM is a comprehensive data analysis software combining diversity analyses, biomarker selection, functional information mining, and visualization to the machine learning based ‘high-dimensional data portraying’.

Single-cell RNA sequencing of residual cells from 24 CAR T-cell infusion products.

nuc_ctDNA_process ImageJ 1.x macros and Matlab code for processing 3D nuclear classification and quantification. This repo is designed to help you recreate the methods use in the associated publication. Please don't hesitate to contact if you have questions. Happy to debug, update, etc if there's need.

Lif files: Use ImageJ 1.x macro in fiji folder to process lif files for subsequent ilastik and Matlab processing. Works with 3 channel data (DAPI, DIC, Rh-Red-X) and 4 channel data (DAPI, Cy5, ...

Bud dormancy is a critical survival strategy for perennial plants in temperate climates to endure winter, involving complex transcriptional reprogramming. While previous studies have investigated gene expression during discrete phases of the grapevine bud annual cycle, a holistic understanding requires an integrated, season-wide analysis. We conducted a meta-analysis by combining and reexamining the transcriptomic data from two seminal studies on grapevine bud development. Using Self-Organizing ...

The cited in the main text supporting Supplementary Figures and Data can be downloaded at https://doi.org/10.5281/zenodo.15624414 and the datasets can be downloaded using the following accession numbers GSE272168 for the left ventricle RNAseq dataset and GSE300189 for the right ventricle RNAseq dataset. Any additional datasets used and/or analyzed in this study are available from the corresponding authors upon request at the reasonable timeframe. Preprocessed raw gene expression count matrices ...

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 ...

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:

1. "Simdata" folder contains data, scripts, and results of performance evaluation of extension SOM and supervised SOM with simulated data.

2. "IBD" - folder contains data, scripts, and results of analysis of Inflammatory bowel disease datasets.

3. "BC" - folder ...