Pinned Repositories
500lines
500 Lines or Less
academicpages.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
advanced-r-statistical-programming-and-data-models
Source Code for 'Advanced R Statistical Programming and Data Models' by Matt Wiley and Joshua F. Wiley
alignment-nf
Whole Exome/Whole Genome Sequencing alignment pipeline
arriba
Fast and accurate gene fusion detection from RNA-Seq data
Awesome-Bioinformatics
2018 Recommended Papers to Read in Bioinformatics as Voted by Bioinformaticians
awesome-pipeline
A curated list of awesome pipeline toolkits inspired by Awesome Sysadmin
bamsurgeon
tools for adding mutations to existing .bam files, used for testing mutation callers
batch-adjust-warning-reports
Wolf_et_al_Cell_2019
UVB-induced tumor heterogeneity diminishes immune response in melanoma
yf0205's Repositories
yf0205/advanced-r-statistical-programming-and-data-models
Source Code for 'Advanced R Statistical Programming and Data Models' by Matt Wiley and Joshua F. Wiley
yf0205/Awesome-Bioinformatics
2018 Recommended Papers to Read in Bioinformatics as Voted by Bioinformaticians
yf0205/bamsurgeon
tools for adding mutations to existing .bam files, used for testing mutation callers
yf0205/bioinformatics
:microscope: Path to a free self-taught education in Bioinformatics!
yf0205/brcarepred
yf0205/cbioportal
cBioPortal for Cancer Genomics
yf0205/ChIP-seq-analysis
ChIP-seq analysis notes from Tommy Tang
yf0205/circlize
Circular visualization in R
yf0205/cs-video-courses
List of Computer Science courses with video lectures.
yf0205/django-locallibrary-tutorial
Local Library website written in Django; example for the MDN server-side development Django module: https://developer.mozilla.org/en-US/docs/Learn/Server-side/Django.
yf0205/dplyr
dplyr: A grammar of data manipulation
yf0205/gatk
Official code repository for GATK versions 4 and up
yf0205/gdc-dnaseq-cwl
CWL for GDC DNASeq workflows
yf0205/ggstatsplot
Collection of functions to enhance ggplot2 plots with results from statistical tests.
yf0205/ImmuneResistance
This resource provides the code developed in the study of Jerby-Arnon _et al. "Single-cell RNA-seq of melanoma ecosystems reveals sources of T cell exclusion linked to immunotherapy clinical outcomes".
yf0205/learn-python3
Learn Python 3 Sample Code
yf0205/m6A-seq_analysis_workflow
A pipeline to process m6A-seq data and down stream analysis.
yf0205/methylKit
R package for DNA methylation analysis
yf0205/MIRACUM-Pipe
yf0205/proxyee-down
http下载工具，基于http代理，支持多连接分块下载
yf0205/r4ds
R for data science
yf0205/RiboCode
release version
yf0205/rnacocktail
yf0205/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.
yf0205/scSeqR
scSeqR (Single Cell Sequencing R package) is an interactive R package to works with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq and CITE-seq). As some research studies require a more attuned forms of normalization or spike-in normalization in some cases, scSeqR allows the users to chose from multiple normalization methods and correcting for dropouts (nonzero events counted as zero). Because some of the cell types are more challenging to work with, scSeqR also allows the users to choose from different clustering algorithms (i.e. ward.D, kmeans, ward.D2, hierarchical, etc.) and indexing methods (i.e. silhouette, ccc, kl, gap-stats, etc.) to adjust for sensitivity and stringency in order to find less or more subpopulations of cell types to design both unsupervised and supervised models to best suit your research. scSeqR provides 2D and 3D interactive visualizations, differential expression analysis, filters based on cells and genes, cell helth and cell cycle, merging, normalizing for dropouts and batch differences, pathway analysis, cell type prediction and tools to find marker genes for clusters and conditions. scSeqR inputs single cell data in 10X format, large numeric matrix files and data frames.
yf0205/ssGSEA2.0
Single sample Gene Set Enrichment analysis (ssGSEA) and PTM Enrichment Analysis (PTM-SEA)
yf0205/TCGAmutations
R data package for pre-compiled somatic mutations from TCGA cohorts (from Broad Firehose and TCGA MC3 Project)
yf0205/tidyr
Easily tidy data with spread and gather functions.
yf0205/TumorType-WGS
Classifying tumor types based on Whole Genome Sequencing (WGS) data
yf0205/UpSetR
An R implementation of the UpSet set visualization technique published by Lex, Gehlenborg, et al..