WGLab/dragonstar2019

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WGLab/dragonstar2019

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dragonstar2019

This GitHub repository contains lecture slides as well as the computing exercises for the 2019 Dragon Star Bioinformatics course. This is a five-day course with the theme "Genomics of Human Diseases". The content of the course is described below:

Day 1

Genomic technologies in disease studies: Course slide, Computing exercise (in Chinese)

NGS data formats and variant calling: Course slide, Computing exercise
Day 2

Alignment of short/long-read sequencing data: Course slide, Computing exercise

Genome assembly by short/long-read sequencing: Course slide, Computing exercise
Day 3

Detection of structural variants in human diseases: Course slide, Computing exercise

Annotation and phenotype-driven interpretation of genetic variants: Course slide, Computing exercise 1 Computing exercise 2
Day 4

SNP and Sequencing-based genome-wide association studies (GWAS): Course slide, Computing exercise

Rare variants and de novo variants association studies: Course slide, Computing exercise

Introduction to cloud computing in bioinformatics
Day 5

RNA-Seq in human diseases: Course slide, Computing exercise

Deep Learning in sequencing data analysis: Course slide

Artificial intelligence and somatic variant analysis

Housekeeping issues and acknowledgements are given here.

doc-ANNOVAR

Documentation for the ANNOVAR software

InterVar

A bioinformatics software tool for clinical interpretation of genetic variants by the 2015 ACMG-AMP guideline

DeepMod

DeepMod: a deep-learning tool for genomic-scale, strand-sensitive and single-nucleotide based detection of DNA modifications

NanoCaller

Variant calling tool for long-read sequencing data

PennCNV

Copy number vaiation detection from SNP arrays

biocluster

Tutorial on building a computing cluster for bioinformatics

phenolyzer

phenotype-based prioritization of candidate genes for human diseases

Bioformer

Bioformer: an efficient BERT model for biomedical text mining

VirTect

Detection of viruses from RNA-Seq on human samples

Phen2Gene

Phenotype driven gene prioritization for HPO

CancerVar

Clinical interpretation of somatic mutations in cancer

LIQA

Long-read Isoform Quantification and Analysis

NanoMod

NanoMod: a computational tool to detect DNA modifications using Nanopore long-read sequencing data

EHR-Phenolyzer

A pipeline that takes clinical notes from EHRs and generate phenotype terms, then generate ranked gene list

RepeatHMM

a hidden Markov model to infer simple repeats from genome sequences

DeepMod2

DNA 5mC methylation detection from Dorado or Guppy basecalled Oxford Nanopore reads

Jupyter Notebook

SeqMule

Automated human exome/genome variants detection from FASTQ files

LongGF

A computational algorithm and software tool for fast and accurate detection of gene fusion by long-read transcriptome sequencing

Workshop_Annotation

Course materials for "Variants Annotate and Phenotype Analysis"

LinkedSV

GenGen

A set of software tools to facilitate GWAS analysis

DeepRepeat

An accurate repeat detection from Nanopore data using deep learning and image techniques

HadoopCNV

HadoopCNV is a MapReduce-based copy number variation caller for genome sequencing data

lncScore

A python package for the identification of lncRNA from the assembled novel transcripts

PhenoSV

PhenoSV: Interpretable phenotype-aware model for the prioritization of genes affected by structural variants.

PhenoGPT

Jupyter Notebook

GDP

Group lasso based Deep Neural Network for Cancer Prognosis

NanoRepeat

NanoRepeat: fast and accurate analysis of Short Tandem Repeats (STRs) from Oxford Nanopore sequencing data

icages

iCAGES (integrated CAncer GEnome Score) is an effective tool for prioritizing cancer driver genes for a patient

PennCNV2

A software package for detection of copy number alterations from tumor samples

LongReadSum

mutformer

A transformer model to predict pathogenic mutations

Jupyter Notebook

SVGen

Simulator for structural variants in various types of next-generation sequencing data

AmpBinner

A barcode demultiplexer for Oxford Nanopore long-read amplicon sequencing data

DELongSeq

iMEGES

integrated Mental-disorder Genome Score

UROBORUS

UROBORUS: circular RNA identification from RNA-Seq data

epilepsy-autism-multiplex-network

Jupyter Notebook

PhenCards

Development of phencards.org web server for one stop shop of phenotype information

PennCNV-Seq

Adaption of the original PennCNV algorithm for whole-genome sequencing data

uniline

Assembly-based analysis

kgev-neo4j

Jupyter Notebook

QuantitativeGenomics2022

w4CSeq

web server of 4C-Seq data analysis pipeline

NanoBinner

Phen2Gene2

Phen2Gene improved and optimized for pipelines

ContextSV

An alignment-based, generalized structural variant caller for long-read sequencing/mapping data

ASD_terminology

Jupyter Notebook

Project_Belka

Jupyter Notebook

QuantitativeGenomics2023

Materials for Quantitative Genomics 2023 workshop

SGAN

SGAN (Oncogenicity score prediction using Semi-supervised Generative Adversarial Networks)

Jupyter Notebook

QuantitativeGenomics2021

lncScore-Java

Prediction of lncRNA from RNA-Seq data

HTT-SNP-Phasing

icages-server

the iCAGES server running on Ruby on Rails

GestaltMML

Jupyter Notebook

SCOTCH

Single-Cell Omics for Transcriptome CHaracterization (SCOTCH): isoform-level characterization of gene expression through long-read single-cell RNA sequencing