Umar Ahmad Profile picture
Apr 23 10 tweets 6 min read Twitter logo Read on Twitter
1/ Are you a bioinformatics researcher looking for powerful tools to analyse your data? Check out @Bioconductor ! Here are some of my favorite packages for #bioinformatics analyses. Image
2/ First up: #DESeq2 by @mikelove. This package provides a method for differential gene expression analysis of RNA-seq data. It's widely used and highly cited in the field, and it's perfect for identifying genes that are differentially expressed between samples.
3/ Next, I recommend #edgeR. Like DESeq2, edgeR is a package for differential gene expression analysis of RNA-seq data. It's particularly useful for smaller sample sizes and can detect differential expression with greater sensitivity.
4/ For #singlecell analysis, I recommend #scater. This package provides a suite of functions for quality control, visualisation, and analysis of single-cell RNA-seq data. It can help you identify cell subpopulations and explore their gene expression patterns.
5/ If you're working with ChIP-seq data, check out #ChIPseeker. This package provides tools for annotating and visualising genomic regions enriched by ChIP-seq. It can help you identify enriched transcription factor binding sites and their target genes.
6/ Another great package for ChIP-seq analysis is #DiffBind. It provides methods for differential binding analysis, allowing you to identify #genomic regions that are differentially bound between experimental conditions.
7/ For methylation analysis, I recommend the #methylKit package. It provides tools for identifying differentially methylated regions and visualising methylation patterns across the genome.
8/ Finally, in #bioinformatics, we have #clusterProfiler. This package provides tools for functional enrichment analysis of gene clusters. It can help you identify biological #pathways and processes that are overrepresented in your data.
9/ These are just a few examples of the many powerful tools available in @Bioconductor for #bioinformatics analyses. Whether you're working with RNA-seq, ChIP-seq, single-cell data, or something else entirely, there's a package for you! #bioinformatics #datascience #opensource
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More from @babasaraki1

Apr 23
1/ If you're new to #bioinformatics and looking to start learning, there are a ton of great resources out there to help you get started. Here are some sites, #Github repos, and books to check out:
2/ First up, the website has a ton of resources for learning bioinformatics, including tutorials, forums, and #software tools. Check it out here:
3/ Next, the Github repository Awesome Bioinformatics is a great place to find curated lists of resources, including #tutorials, #courses, and #software tools. Check it out here:…
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Apr 23
1/ If you're interested in learning #bioinformatics as a #novice, you're in the right place! Bioinformatics is a field that combines biology, computer science, and statistics to analyse large scale biological data. Here are some resources to get you started:-
2/ First, you'll need to learn some basic biology. #KhanAcademy has a comprehensive series of videos on biology that can help you understand the fundamentals. Check it out here:
3/ Next, you'll need to learn some basic #programming skills. #Codecademy has a great course on #Python, which is a popular programming language in bioinformatics. Check it out here:…
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