😎 A curated list of software and resources for exploring and visualizing (browsing) expression data 😎
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Updated
Apr 26, 2024
😎 A curated list of software and resources for exploring and visualizing (browsing) expression data 😎
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
This repository contains the implementation for "Towards Biologically Plausible and Private Gene Expression Data Generation" (accepted at PoPETs 2024)
Integrative approach to feature selection combining weighted LASSO and prior biological knowldge
Simple (effin') Enrichment Analysis in R
orthomap is a python package to extract orthologous maps (in other words the evolutionary age of a given orthologous group) from OrthoFinder/eggNOG results. Orthomap results (gene ages per orthogroup) can be further used to calculate weigthed expression data (transcriptome evolutionary index) from scRNA sequencing objects.
R package for de novo pathway enrichment using KeyPathwayMiner
This is a R package that intends to perform all the features possible by tensor decomposition based unsupervised feature extraction
add any phylogenetically based transcriptome evolutionary index (TEI) to single-cell data objects
Recurrent Variational Auto gene encoder
TissUUmaps is a browser-based tool for fast visualization and exploration of millions of data points overlaying a tissue sample. TissUUmaps can be used as a web service or locally in your computer, and allows users to share regions of interest and local statistics.
The goal of iCTC is to detect whether peripheral blood cells have CTCs (circulating tumor cell) or not.
Deep learning methods for feature selection in gene expression autism data.
Scripts and data from "Towards a global investigation of transcriptomic signatures through co-expression networks and pathway knowledge for the identification of disease mechanisms"
Predicting the Probability or Occurrence of Relapse for Colorectal Cancer Patients using Gene Expression Data
SPOT - Swift Profiling Of Transcriptomes - a shiny app for gene ranking according to user-defined expression profiles
ROSeq - A rank based approach to modeling gene expression with filtered and normalized read count matrix. Takes in the complete filtered and normalized read count matrix, the location of the two sub-populations and the number of cores to be used.
Methods for training and interpreting deep radiogenomic neural networks
Arabidopsis EcoGEx (R-📦 + 🕸️-App)
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