Bioinformatics notes

Bioinformatics learning and data analysis tips and tricks. Please, contribute and get in touch!

Table of content

• Awesome
  • Notes by Ming Tang
• Pipelines
• Courses
• Videos

Genomics notes

• RNA-seq notes
• scRNA-seq notes
• ChIP-seq notes
• Methylation notes
• scATAC-seq notes
• SNP notes
• Hi-C tools
• Hi-C data
• scHi-C notes
• Cancer notes
• Immuno notes

See MDmisc notes for other programming and genomics-related notes.

Awesome

• The complete assembly of human genome (haploid CHM13 cell line). 3.055 billion base pairs, no gaps for all 22 chromosomes plus ChrX, new genes. Resolving ribosomal rDNA sequences. PacBio, Oxford Nanopore, other technologies. The Telomere-to-Telomere (T2T) consortium, UCSC, NCBI PRJNA559484, GitHub with download links to FASTA, gff3, liftover chains

  • Nurk, Sergey, Sergey Koren, Arang Rhie, Mikko Rautiainen, Andrey V. Bzikadze, Alla Mikheenko, Mitchell R. Vollger et al. "The complete sequence of a human genome." bioRxiv (2021).

• Milestones in Genomic Sequencing by Nature, 2000-2021 period, interactive infographics

• Genome Coordinate Cheat Sheet

• Awesome-Bioinformatics - A curated list of awesome Bioinformatics libraries and software, by Daniel Cook and community-contributed

• awosome-bioinformatics - A curated list of resources for learning bioinformatics

• awesome-cancer-variant-databases - A community-maintained repository of cancer clinical knowledge bases and databases focused on cancer variants, by Sean Davis and community-maintained

• awesome-single-cell - List of software packages for single-cell data analysis, including RNA-seq, ATAC-seq, etc. By Sean Davis and community-maintained

• awesome-alternative-splicing - Alternative splicing resources

• awesome-10x-genomics - List of tools and resources related to the 10x genomics GEMCode/Chromium system, by Johan Dahlberg and community-contributed

• awesome-multi-omics - List of software packages for multi-omics analysis, by Mike Love and community-maintained

• awesome-bioinformatics-benchmarks - A curated list of bioinformatics bench-marking papers and resources

• awesome_genome_browsers - genome browsers and genomic visualization tools. By David McGaughey

• awesome-expression-browser - A curated list of software and resources for exploring and visualizing (browsing) expression data, and more. By Federico Marini and community-maintained

• awesome-genome-visualization - A list of interesting genome browser or genome-browser-like implementations. By Colin Diesh

• awesome-microbes - List of software packages (and the people developing these methods) for microbiome (16S), metagenomics (WGS, Shot-gun sequencing), and pathogen identification/detection/characterization. By Steve Tsang and community-contributed

• Bedtools Cheatsheet

• sandbox.bio - an interactive bedtools tutorial developed by the Quinlan Lab

• biotools - A massive collection of references on the topics of bioinformatics, sequencing technologies, programming, machine learning, and more. By John Didion

• For all your seq... DNA & RNA - Illumina flyer with infographics of all sequencing-by-synthesis technologies. RNA and DNA versions

• Learning Bioinformatics At Home

• List of software/websites/databases/other stuff for genome engineering

• multimodal-scRNA-seq - Figure depicting the breadth of multimodal scRNA-seq technologies. References to technology-specific papers

• SequencEnG - Hierarchical summary of 66 sequencing technologies, computational algorithms, references to papers.

  • Zhang, Y., Manjunath, M., Kim, Y., Heintz, J., and Song, J.S. (2019). SequencEnG: an interactive knowledge base of sequencing techniques. Bioinformatics 35, 1438–1440.

• OmniPath: intra- & intercellular signaling knowledge - a database of molecular biology prior knowledge, combines data from more than 100 resources. Interface to R, Python, more.

• The Leek group guide to genomics papers- Jeff Leek recommended list of genomics papers

Notes by Ming Tang

• Unix, R and python tools for genomics and data science - links and references to many computational biology resources, by Ming Tang

• bioinformatics-one-liners - collection of bioinformatics-genomics bash one liners, using awk, sed etc., by Ming Tang

• RNA-seq-analysis - RNAseq analysis notes, by Ming Tang

• ChIP-seq-analysis - ChIP-seq analysis notes, by Ming Tang

• DNA-seq-analysis - Notes on whole exome and whole genome sequencing analysis, by Ming Tang

• DNA-methylation-analysis - DNA methylation analysis notes from Ming Tang

• scATAC-seq-analysis-notes - single-cell ATAC-seq notes, by Ming Tang

Pipelines

• List of bioinformatics tools developed by IHEC Int'l Human Epigenome Consortium researchers - tools for all types of genomic analyses

• Learning Nextflow in 2020 - Materials to learn NextFlow

• Nextflow Tower - management of Nextflow data pipelines. Video overview

• nf-core - a framework for Nextflow-based pipeline creation, community-driven. Integrated with Conda, Docker, Biocontainers. Scalable to a cloud level. Pipeline assemblers: Flowcraft, Pipeliner. nf-core GitHub. All pipelines are on the nf-core hub.

  • Ewels, Philip, Alexander Peltzer, Sven Fillinger, Johannes Alneberg, Harshil Patel, Andreas Wilm, Maxime Garcia, Paolo Di Tommaso, and Sven Nahnsen. “Nf-Core: Community Curated Bioinformatics Pipelines.” Preprint. Bioinformatics, April 16, 2019.

• bcbio-nextgen - Validated, scalable, community developed variant calling and RNA-seq analysis. Documentation

Courses

• RNA-seq theory and analysis - theory and practical guidelines for RNA-seq data analysis, by Skyler Kuhn

• Data science for economists - from R, tidyverse to GitHub, web scraping, Docker, Google Cloud and more. By Grant McDermott

• Reproducible research and data analysis with Linux containers and Nextflow pipelines, GitHub

• Bioinformatics Coffee Hour - Short lessons from FAS Informatics coffee hour,data science, command line, R basics, Snakemake

• The Biostar Handbook: 2nd Edition - Biostar Handbook - bioinformatics survival guide. A practical overview for the data analysis methods of bioinformatics. From Unix/command line to each type of sequencing data ana analysis

• Beginner's Handbook to Next Generation Sequencing by GenoHub - omics technologies, experimental descriptions

• Computational Genomics with R book by Altuna Akalin. From R basics to different types of bioinformatics analyses. GitHub

• The Bioinformatics algorithms web site. Videos and Texts covering topics from biology to genome assembly algorithms, motif finding, sequence comparisons and more bioinformatics tasks and solutions. By Phillip Compeau and Pavel Pevzner

• Algorithms for DNA Sequencing - Ben Langmead's course material. Slides on GitHub, Python/Colab code examples, Youtube videos

• Applied Computational Genomics Course at UU by Aaron Quinlan. All slides on Google drive, Youtube videos for each lecture

• Introduction to Computational Biology course by Mike Love. GitHub

• Data Analysis in Genome Biology course by Thomas Girke. Bioinformatics of NGS data analysis GitHub

• Bioconductor for Genomic Data Science course by Kasper Hansen. Includes videos, code examples and lecture material. GitHub

• BPA-CSIRO Workshops - Cancer Genomics, Introduction to Next Generation Sequencing Hands-on Workshop. Links to topic-oriented GitHub repositories, PDF handouts. GitHub

• The Bioconductor 2018 Workshop Compilation, editors - Levi Waldron, Sean Davis, Marcel Ramos, Lori Shepherd, Martin Morgan. Task-oriented workshops covering a range of genomics/Bioconductor analyses. GitHub

• CSAMA - Course material for CSAMA: Statistical Data Analysis for Genome Scale Biology, by Bioconductor team. Lectures, Labs

• JHU EN.601.749: Computational Genomics: Applied Comparative Genomics course, by Michael Schatz. Links to similar courses there. Other courses by Michael

• JHU Data Science lab - several data science courses, links to topic-specific GitHub repositories, other resources

• CSE 549 - Introduction to Computational Biology by Steven Skiena. Includes video lectures. Another course: CSE 519 - Data Science

• DIYtranscriptomics.github.io - Course material for the "do-it-yourself" RNA-seq course, by Daniel Beiting. GitHub

• Informatics for RNA-seq: A web resource for analysis on the cloud by Griffith lab. All aspects of RNA-seq analysis

• RNA-seqlopedia - one long page of all steps of RNA-seq data analysis, from molecular biology to computational analysis, very detailed

• BaRC Hot Topics - lecture slides and handouts on all genomics topics, from Unix to microarray, sequencing, genomics and statistics

• Courses by Dr. Raghu Machiraju. Topics: data visualization, biomedical informatics, computer graphics, linked from the homepage. CSE5599-BMI7830 - biomedical informatics. CSE5544 – Introduction to Data Visualization

• alignment-and-variant-calling-tutorial - basic walk-throughs for alignment and variant calling from NGS sequencing data, PDF lecture, by Erik Garrison.

Videos

• Machine Learning in Genomics - Fall 2019 by Manolis Kellis. Course website

• Free online training in bioinformatics and biostatistics! by David Tabb. Various topics beyond genomics

• Bioconductor Workshop 2: RNA Seq and ChIP Seq Analysis - 6 hours workshop on RNA-seq and ChIP-seq technology and analysis by Levi Waldron and others

• Differential Splicing Analysis with RNA-Seq: Current Applications, Approaches, & Limitations - 1 hour overview of differential splicing analysis

• NHGRI_Genomics2016 - "Current Topics in Genome Analysis 2016" course - A lecture series covering contemporary areas in genomics and bioinformatics, slides

• MIT_SysBiol2014 - "Foundations of Computational and Systems Biology", slides

• Regulatory Genomics and Epigenomics - series of genomcs-oriented talks by Simons Institute. 26 videos, ~30min each.

• Foundations of Data Science — Spring 2016 - course from UC Berkeley. Instructor: John DeNero. Video and slides. This course is accompanied by other "connector" courses from UC Berkeley

• A Roadmap to the Living Genome by John Stamatoyannopoulos. An overview of cell type-specific (epi)genomic landscapes, visualization and analysis techniques, association and enrichment of disease-associated variants in regulatory regions.

• RNA-Seq Methods and Algorithms - short video course by Harold Pimentel, pseudoalignment, kallisto, sleuth, practical

• Integrating ENCODE Data With Your Research: An Interactive Survey of ENCODE Tools and Resources - set of short videos about ENCODE data and functionality