usefullinks

IDR Chip-seq: https://hbctraining.github.io/Intro-to-ChIPseq/lessons/07_handling-replicates-idr.html

Remap 2020: http://remap.univ-amu.fr/

About transcriptome based rna-seq:

https://cgatoxford.wordpress.com/2016/08/17/why-you-should-stop-using-featurecounts-htseq-or-cufflinks2-and-start-using-kallisto-salmon-or-sailfish/

Using binder with R:

https://github.com/alan-turing-institute/the-turing-way/blob/master/workshops/boost-research-reproducibility-binder/workshop-presentations/zero-to-binder-r.md

Recount3: http://rna.recount.bio/

Snakemake checkpoints: http://ivory.idyll.org/blog/2021-snakemake-checkpoints.html

conda env on hpc: https://kb.iu.edu/d/axgp#conda-init

Reproducible toolkit: https://rdmkit.elixir-europe.org/index.html

Interoperability platform: https://elixir-europe.org/platforms/interoperability

workflow hub: https://workflowhub.eu/

guide to reproducible research: https://the-turing-way.netlify.app/reproducible-research/reproducible-research.html

galaxy admin: https://github.com/galaxyproject/admin-training

fastq repo: ftp://ftp.sra.ebi.ac.uk/vol1/fastq/

kahoot: kahoot.it / kahoot.com

Elixir train the trainer: https://docs.google.com/document/d/1ZkwDJDii5nHFPDsiMto-Fwyw9W1od9IHDzJL_t-uuR8/edit#

ATAC-Seq video: https://www.youtube.com/watch?v=VZFUu_cJxyI

CookieCutter: https://medium.com/worldsensing-techblog/project-templates-and-cookiecutter-6d8f99a06374

Multi-omics workshop: https://uppsala.instructure.com/courses/52162/pages/schedule

Authorships: https://credit.niso.org/ http://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authors-and-contributors.html https://publicationethics.org/authorship

Publication ethics: https://www.councilscienceeditors.org/resource-library/editorial-policies/white-paper-on-publication-ethics/

EMBL open science: https://www.embl.org/internal-information/wp-content/uploads/2021/12/open-science-implementation-guidelines.pdf

The Declaration on Research Assessment: https://sfdora.org/

Multi-stages singularity by Francesco: https://git.embl.de/tabaro/snakemake-pipelines/-/blob/main/singularity/Singularity.bedtools

singularity CI by Francesco: https://git.embl.de/tabaro/snakemake-pipelines/-/blob/main/.gitlab-ci.yml

singularity CI by IT: https://git.embl.de/grp-itservices/singularity-reg/-/blob/master/.gitlab-ci.yml

spatial-transcriptomics: https://www.nature.com/articles/s41587-021-01006-2#Sec9 https://www.nature.com/articles/s41586-019-1049-y https://biofam.github.io/MOFA2/MEFISTO.html https://squidpy.readthedocs.io/en/stable/auto_tutorials/tutorial_seqfish.html https://github.com/spacetx/starfish#starfish-scalable-pipelines-for-image-based-transcriptomics

Graphical access with x2go: https://wiki.embl.de/cluster/Env#Graphical_Access

Workflowhub: https://about.workflowhub.eu/

Workflows community initiative: https://workflows.community/

Look at docker recipe: https://git.embl.de/kaspar/learnr-project

Awsome pipelines repository: https://github.com/pditommaso/awesome-pipeline

Nextflow tutorial to start with: https://sateeshperi.github.io/nextflow_varcal/nextflow/

Nextflow tutorials: https://nf-co.re/docs/usage/nextflow

About managing a core: https://www.researchcomputingteams.org/resources

JBrowse 2: https://jbrowse.org/jb2/

Visual integration tool for exploration of spatial single cell experiments: http://vitessce.io/

human body at single-cell resolution: https://hubmapconsortium.org/

psupertime: supervised pseudotime analysis for time-series single-cell RNA-seq data https://academic.oup.com/bioinformatics/article/38/Supplement_1/i290/6617492

About using nextflow: https://www.reddit.com/r/bioinformatics/comments/sc8e0i/does_everyone_use_nextflow_thesedays/?utm_source=share&utm_medium=web2x&context=3

spacemake: https://academic.oup.com/gigascience/article/doi/10.1093/gigascience/giac064/6646447?login=true

--------------------- Aug 2022

Neuroscience Cloud Analysis As a Service: https://www.biorxiv.org/content/10.1101/2020.06.11.146746v2 http://www.neurocaas.org/analyses/

Choose your statistical test: https://www.statstest.com/

Collection of singularities: https://depot.galaxyproject.org/singularity/

open ebench: https://openebench.bsc.es/benchmarking

Workflow finder: https://australianbiocommons.github.io/2_1_workflows.html

GitHub Actions Tutorial - Basic Concepts and CI/CD Pipeline with Docker: https://www.youtube.com/watch?v=R8_veQiYBjI

Dockerhub best practices: https://www.docker.com/blog/best-practices-for-using-docker-hub-for-ci-cd/

Publishing docker images with github actions: https://docs.github.com/en/actions/publishing-packages/publishing-docker-images

snakemake tutorial: https://edcarp.github.io/2022-11-08_ed-dash_workflows-snakemake/

Nextflow tutorial: https://edcarp.github.io/2023-01-24_ed-dash_workflows-nextflow/

10 things for Curating Reproducible and FAIR Research: https://curating4reproducibility.org/10things/

Preventing a file from being modified on pull request using github CI: https://docs.github.com/en/actions/using-workflows/triggering-a-workflow#accessing-and-using-event-properties

Running a workflow only if a previous one succeeded on github CI: https://docs.github.com/en/actions/using-workflows/events-that-trigger-workflows#running-a-workflow-based-on-the-conclusion-of-another-workflow

The github check API: https://docs.github.com/en/rest/guides/getting-started-with-the-checks-api

Amazon workshop: http://slchen-lab-training.s3-website-ap-southeast-1.amazonaws.com/01-hpc-overview.html

https://www.frontiersin.org/articles/10.3389/fncir.2020.00025/full https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008565 https://cns2020online.sched.com/event/cslO/w2-s07-online-methods-for-real-time-analysis-of-calcium-imaging-data https://cbmm.mit.edu/learning-hub/tutorials/computational-tutorial/calcium-imaging-data-cell-extraction https://www.ml.cmu.edu/research/joint_phd_dissertations/Zhou-Pengcheng-thesis-cnbc-2016.pdf https://www.cnsorg.org/ https://www.cnsorg.org/committees https://www.youtube.com/channel/UCqz8NIG24tV1HHCkKidA4Nw/videos https://neurostars.org/ https://neurostars.org/g/OCNSStudentSig https://www.cnsorg.org/newsletter

https://git.embl.de/tabaro/snakemake-playground

FAIR Computational Workflows: https://direct.mit.edu/dint/article/2/1-2/108/10003/FAIR-Computational-Workflows

Tess training material: https://tess.elixir-europe.org/

Single-cell on galaxy: https://singlecell.usegalaxy.eu/

AWS and scientific computing: https://www.noahlebovic.com/aws-doesnt-make-sense-for-scientific-computing/

Tutorial by Sarah Kasper on Biostatistics: https://www.ebi.ac.uk/training/online/courses/biostatistics-introduction/

Resources for RNA-seq processed data: https://maayanlab.cloud/archs4/index.html

Babraham training material: https://www.bioinformatics.babraham.ac.uk/training.html

fastqscreen: https://www.bioinformatics.babraham.ac.uk/projects/fastq_screen/

UX toolkit for Life Sciences: https://uxls.org/

The perfect team by Google: 1 & 2

Python visualization (comparison):

• https://streamlit.io/
• https://docs.bokeh.org/en/latest/
• https://altair-viz.github.io/
• https://dash.plotly.com/

Genomics and software engineering: https://news.ycombinator.com/item?id=33671264

sapling (git control): https://engineering.fb.com/2022/11/15/open-source/sapling-source-control-scalable/

About Free Open Source Software (FOSS): https://www.kooslooijesteijn.net/blog/why-is-free-open-source-software-badly-designed?pk_campaign=rss

Single-cell best practices: https://www.sc-best-practices.org/preamble.html

Scientific publishing with Quarto: https://quarto.org/

Here are some resources for teaching Bioinformatics:

• https://bio-it.embl.de/course-materials/
• https://tess.elixir-europe.org/materials
• https://elixir-fair-training.github.io/FAIR-training-handbook/
• https://www.mygoblet.org/training-materials/
• https://www.mygoblet.org/training-portal/
• https://www.ebi.ac.uk/training/on-demand
• https://www.bioinformatics.babraham.ac.uk/training.html
• https://training.galaxyproject.org/
• https://github.com/carpentries-incubator
• https://software-carpentry.org/lessons/
• https://github.com/gladstone-institutes/Bioinformatics-Workshops/wiki
• https://bioinformatics.sph.harvard.edu/training

Can Bioinformatics Work As Data Scientist? https://workwut.com/bioinformatics-work-data-scientist/

AWS genomics: https://aws.amazon.com/blogs/aws/introducing-amazon-omics-a-purpose-built-service-to-store-query-and-analyze-genomic-and-biological-data-at-scale/

spike-chip: https://academic.oup.com/nargab/article/3/3/lqab064/6329082

What Is the Key Best Practice for Collaborating with a Computational Biologist?: see here

T3E: a tool for characterising the epigenetic profile of transposable elements using ChIP-seq data: https://mobilednajournal.biomedcentral.com/articles/10.1186/s13100-022-00285-z

Learning git: https://docs.github.com/en/get-started/quickstart/set-up-git

18 repositories for developpers: See Tweet

Fundamentals of data visualization: https://clauswilke.com/dataviz/

Conda docker tutorial: https://kevalnagda.github.io/conda-docker-tutorial

Intro to containers: https://biocorecrg.github.io/CoursesCRG_Containers_Nextflow_May_2021/index.html

SeqCode: http://ldicrocelab.crg.eu/index.php

Change chrom names in bam files: http://lindenb.github.io/jvarkit/ConvertBamChromosomes.html

Galaxy tutorial on make and snakemake: https://training.galaxyproject.org/training-material/topics/data-science/tutorials/snakemake/tutorial.html

Web app with Flask: https://www.digitalocean.com/community/tutorials/how-to-make-a-web-application-using-flask-in-python-3

List comprehension in Python: https://www.w3schools.com/python/python_lists_comprehension.asp

BioGPT: https://github.com/microsoft/BioGPT

Bioinfo training materials: https://glittr.org/?per_page=25&sort_by=stargazers&sort_direction=desc

Bioconvert: https://www.biorxiv.org/content/10.1101/2023.03.13.532455v2.abstract

deepscatter: https://observablehq.com/@bmschmidt/arxiv

configure R in Vscode: https://code.visualstudio.com/docs/languages/r#_getting-started

libmamba: https://www.anaconda.com/blog/a-faster-conda-for-a-growing-community

Easeq: https://easeq.net/demo/

Human Pangenome Consortium release: https://www.embl.org/news/science/a-more-diverse-human-reference-genome/

Logistic regression clearly explained: https://www.youtube.com/watch?v=9zw76PT3tzs

why do we use sigmoids: https://www.youtube.com/watch?v=Aj7O9qRNJPY

Maximum likelihood clearly explained: https://www.youtube.com/watch?v=VOIhswqFWVc

Expectation-maximization clearly explained: https://www.youtube.com/watch?v=xy96ArOpntA&t=557s