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bioinfo_100kownboy's Projects

rcodes icon rcodes

Codes used in scRNA-seq analysis.

rekcarc-tsc-uht icon rekcarc-tsc-uht

清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University

repaq icon repaq

repack Illumina format FASTQ to a smaller binary file (.rfq), which can be further compressed by xz (.rfq.xz)

requests icon requests

Python HTTP Requests for Humans™ ✨🍰✨

reseqtools icon reseqtools

A Toolkit for analyzing next-generation DNA Re-Sequencing data

rmejlbasbmp_2024 icon rmejlbasbmp_2024

Repository for the paper "The impact of package selection and versioning on single-cell RNA-seq analysis"

rnaseq_tutorial icon rnaseq_tutorial

Informatics for RNA-seq: A web resource for analysis on the cloud. Educational tutorials and working pipelines for RNA-seq analysis including an introduction to: cloud computing, critical file formats, reference genomes, gene annotation, expression, differential expression, alternative splicing, data visualization, and interpretation.

rodeo icon rodeo

A data science IDE for Python

sc-agespepca icon sc-agespepca

Single-cell analysis identify the age-associated divergent microenvironments and progression patterns in prostate cancer

scbreast_scrna_scatac_2024 icon scbreast_scrna_scatac_2024

Repository to store code used for the analyses presented in "Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic And Transcriptome Profiling"

sccancer icon sccancer

A package for automated processing of single cell RNA-seq data in cancer

sccomp icon sccomp

Testing differences in cell type proportions from single-cell data.

scdeal icon scdeal

Deep Transfer Learning of Drug Sensitivity by Integrating Bulk and Single-cell RNA-seq data

scell icon scell

Single-CELL rna-seq analysis software

scendo_scovar_2020 icon scendo_scovar_2020

This repository holds the scripts used to analyze the data presented in "A multi-omic single-cell landscape of human gynecologic malignancies", Regner et al., 2021

scevan icon scevan

R package that automatically classifies the cells in the scRNA data by segregating non-malignant cells of tumor microenviroment from the malignant cells. It also infers the copy number profile of malignant cells, identifies subclonal structures and analyses the specific and shared alterations of each subpopulation.

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