Discover and read the best of Twitter Threads about #bioinformatics

Most recents (24)

There was little online material to learn bioinformatics 10 years ago when I started.

I curated ten resources to learn bioinformatics for FREE 🧵👇
1/ Data Analysis for the Life Sciences Series buff.ly/3Z7F1ha by Rafa at DFCI. you can find the courses on Edx buff.ly/3mapP4m
2/ buff.ly/3SDZasD Applied Computational Genomics Course at UU
Read 12 tweets
I need to raise awareness about an important point in #scRNAseq data analysis, which, in my opinion, is not acknowledged enough:

‼️In practice, most cell type assignment methods will fail on totally novel cell types. Biological/expert curation is necessary!

Here's one example👇
Last year, together with @LabPolyak @harvardmed, we published a study in which we did something totally awesome: we experimentally showed how a TGFBR1 inhibitor drug 💊 prevents breast tumor initiation in two different rat models!

Here's a detailed thread on this paper:
As you can imagine, this is a big thing. Treating tumors is already hard, preventing them is even harder!

Obviously, the most burning question for us then became: what is the drug actually doing to prevent tumor initiation?

Or, what is different in treated vs. control cells?
Read 17 tweets
🚨New #SpatialTranscriptomics #Bioinformatics data resource out in @naturemethods.

SODB, a platform with >2,400 manually curated spatial experiments from >25 spatial omics technologies & interactive analytical modules.

This🧵will walk you through all the features of SODB [1/33] Image
First, some background.

Spatial technologies complement classical genomics by also providing information about spatial context & tissue organization in:

- embriogenesis
- disease development
- normal tissue homeostasis

The field has exploded 🔥 in the past 2 years. [2/33] Image
But, data from different studies is stored in different configurations/repositories, such as:

- GEO
- zenodo
- fig share
- SingleCellPortal
- IONPath for MIBI
- 10XGenomics website

This makes data sharing & re-analysis challenging.

Databases exist, but have limitations. [3/33]
Read 33 tweets
1/ My favourite gene has 15 transcripts, which one should I use for further analysis? To report the position of variants? To design primers for? 🤯

This #tweetorial will show you how to filter and prioritise transcripts… 🧵

#genomics #bioinformatics #Ensembltraining 🧬 Screenshot of the transcript table of the LAMA3 gene in the
2/ To start, look for the #canonical tag in the flags column of the transcript table. The canonical transcript is based on conservation, expression, concordance with @appris_cnio and @uniprot, length, clinically important variants and completeness. Screenshot of the transcript table of the LAMA3 gene in the
3/ Many Ensembl #canonical transcripts will also be the #MANESelect, which is our collaboration with @NCBI. These transcripts match perfectly with RefSeq transcripts, so are the best to report variant location. Screenshot of the transcript table of the LAMA3 gene in the
Read 8 tweets
I want to talk today about a methodological issue in #genomics research that has been around a long time but is still a major problem.
The reason is that today I reviewed another manuscript that has this exact problem.
First some background.
In genomics research we often do profiling of how genes are switched on and off in disease and development, and in these profiling tests we identify dozens to thousands of genes that could play a role in those processes
Gene names don’t tell us about their function. We could dig into the literature on them, but the lists are so big it takes too long. So we often use tools to summarise whether genes belonging to certain functional groups are over-represented. Image
Read 24 tweets
Find a great team for junior #Bioinformatics folks. A thread…

1/N
0. Why the right team?

Your life long work habits form in your first 1-2 roles. They’re so hard to change (and find folks who will invest in that change). Please find the right team to se your self up for life long work success. Here’s what I’d look for going back in time.
1. No more than five people.

You need very focused mentorship, and a large team won’t do that. You need to see a variety of approaches to solve problems, effectively organize your time, and execute on projects. Soft+hard skills. Your team are your wingmen.
Read 9 tweets
The science of #immunotherapy can cure a patient's otherwise incurable cancer.

But sometimes immunotherapy fails completely

Shockingly, we hardly know why.

A meta-analysis of #Genomics & #Transcriptomics in >1,000 immunotherapy-treated patients aims to better understand why🧵
This 2021 @CellCellPress paper is one of the best #DataScience #Bioinformatics resources out there for understanding the genetic determinants of response to immune checkpoint inhibitors (ICIs).

cell.com/cell/fulltext/…
Some context:

PD-1 & PD-L1 inhibitors are examples of ICIs.

ICI is a type of immunotherapy that un-blocks the immune system & allows it to mount attacks🤺

It does it by inhibiting checkpoints (s.a. PD-1 & PD-L1): proteins that keep the immune system from attacking its own self
Read 28 tweets
Learning R is an essential step for practicing Bioinformatics.
Here are 10 resources that will help you with R... 👇🧵

#Rstats #Bioinformatics #Biology #programming
(1). R for Data Science: r4ds.had.co.nz
Covers various topics for data analysis, visualization and programming with R
(2). An Introduction to R: cran.r-project.org/doc/manuals/R-…

An R manual from CRAN that covers basic and advanced R topics
Read 12 tweets
1/4 "Using #PEPMatch, a newly developed #bioinformatics package which predicts #peptide similarity within specific #amino #acid mismatching parameters consistent with published #MHC binding capacity,..."

nature.com/articles/s4159…
2/4 "... we discovered that #nucleocapsid #protein shares significant overlap with 22 #multiple #sclerosis (#MS)-associated proteins, including #myelin #proteolipid #protein (#PLP). 

#MultipleSclerosis
3/4 "Further computational evaluation demonstrated that this #overlap may have #critical #implications for #Tcell responses in #multiple #sclerosis (#MS) patients and is likely unique to #SARSCoV2 among the major #human #coronaviruses."
Read 4 tweets
Bench to bedside series: Lung COPD part 1/3
Respiratory histology (via @drawittoknowit)
Health & COPD Lung @TheLancet
#4KMedEd #meded #foamed #medtwitter #MedEd #MedTwitter #Pulmtwitter #scRNAseq #Bioinformatics
Bench to bedside series: Lung COPD part 3/3
#scRNAseq paper: Human distal airways contain a multipotent secretory cell that can regenerate alveoli
1. RASCs (new cell-type) + #stemcell properties in distal airways 2. faulty RASC-to-AT2 transformation in COPD
#Bioinformatics #MedEd
Read 4 tweets
#Bioinformatics is a field that involves using computers and other technological tools to analyze and interpret biological data, such as DNA sequences or protein structures. It is an interdisciplinary field that combines biology, computer science, and information technology.
Some basic concepts in bioinformatics include:
DNA sequences: The sequence of nucleotides (A, C, G, and T) in DNA determines an organism's genetic information. Bioinformatics tools are used to analyze and compare sequences to understand how they differ between organisms and how they can be used to study biological processes.
Read 8 tweets
Healthy Lung vs. Lung with Chronic Obstructive Pulmonary Disease (COPD)
h/t @PatologCritica
#4KMedEd #meded #foamed #medtwitter #MedEd #MedTwitter #Pulmtwitter #lung #COPD #INNOMed

Bench to bedside series: Lung COPD part 1/3
Respiratory histology (via @drawittoknowit)
Health & COPD Lung @TheLancet
#4KMedEd #meded #foamed #medtwitter #MedEd #MedTwitter #Pulmtwitter #scRNAseq #Bioinformatics
Read 5 tweets
1/ Are you ready for 🎄🎅Chirstmas #Tweetorial? Whether you need the sequence for a single exon or whole #genome we got you covered! In the spirit of #Christmas, we will use Vitis vinifera 🍇 🍷in our example
#genomics #bioinformatics #Ensembltraining
2/ If you need the sequence of a single #gene, you can search for the gene symbol or ID from Ensembl homepage and click on ‘Sequence’ in the menu on the left
3/ From this page, you can download the sequence of the gene by clicking on the blue ‘Download Sequence’ button just above the sequence display.
Read 10 tweets
Our immune system is essential in keeping us healthy.

But the immune system also changes profoundly as we age.

Why is that? Could we prevent it?

Let's see how #singlecell biology can help us better understand #immune #aging

🧵👇
First, some background.

Everybody knows that the immune system is hugely complex.

#singlecell sequencing has (arguably) done more for the immune system than for other health applications.

Via #scRNAseq, we discovered & characterized crazily detailed immune cell phenotypes. Image
Such detailed phenotypes have been found in both healthy and diseased tissues.

I wrote several threads about this topic and find it to be one of the most foundational & fascinating progresses that have happened in biomedicine in the past 10 years.
Read 28 tweets
Prokaryotic genome annotation is an important process in understanding the function and biology of bacteria and other prokaryotes.
Here are the top 10 pipelines for prokaryotic genome annotation🧵: #bioinformatics #DataScience #Genomics #Linux
#1: RAST (Rapid Annotation using Subsystems Technology) - a web-based tool for annotating bacterial and archaeal genomes rast.nmpdr.org
#2: Prokka - a fast, reliable, and easy-to-use annotation tool for bacterial and archaeal genomes github.com/tseemann/prokka
Read 12 tweets
Top 10 GitHub repositories for #RNAseq data analysis:

A thread 🧵:
Tuxedo Protocols: github.com/broadinstitute…
This repository contains a collection of protocols and tools for analyzing RNAseq data, including alignment, quantification, and differential expression analysis. (1/10)
RNASeq Workflow: github.com/gringer/RNASeq…
This repository contains a workflow for analyzing RNAseq data using the R programming language, including quality control, alignment, and differential expression analysis. (2/10)
Read 12 tweets
🧵#Bioinformatics in #drug #discovery and development, a THREAD🧵🧵:
#Bioinformatics is playing an increasingly important role in the discovery and development of new #drugs. In this thread, we'll explore how #bioinformatics is being used to identify new targets for drug intervention and optimize drug design.
One key aspect of #bioinformatics in drug discovery is the identification of potential #drug #targets.
Read 12 tweets
🧵#Bioinformatics and its impact on #healthcare, a THREAD🧵🧵:
#Bioinformatics is the application of #computational techniques to the analysis of #biological data, such as #DNA sequences and #protein #structures.
In #healthcare, #bioinformatics is used to gain insights into the #genetic basis of diseases, and to develop new #diagnostic tests and #treatments.
Read 11 tweets
Are you interested in learning about #bioinformatics and working with #genomic data? Here's a detailed #learning path to get you started:
To build a strong foundation in biology, you'll need to learn about:
The #structure and #function of #cells, including the various #organelles and their roles in the cell. This will help you understand how cells work and how they carry out essential functions such as #metabolism and #energy production.
Read 12 tweets
🧵🧵 THREAD: #Bioinformatics applications - a deep dive into #pipelines and #workflows 🧵🧵
1. #Bioinformatics is the application of #computational techniques to the #analysis of #biological #data, such as #sequences, #structures, and #interactions, and is an essential field of modern biology and medicine.
2. #Bioinformatics has many exciting applications in various fields, such as #genetics, #genomics, #proteomics, and #metabolomics, that can provide new insights into the workings of living systems, and can help to advance science and society.
Read 8 tweets
🧵🧵 THREAD: 9 tips for successful #bioinformatics #projects 🧵🧵
1. Start by defining the aim, scope, and objectives of your project, and by identifying the #biological and #computational questions you want to answer.
2. Identify the #data sources, types, and formats, that are relevant and available for your project, and evaluate their quality, quantity, and suitability.
Read 11 tweets
🧵🧵 THREAD: #Bioinformatics and #AlphaFold 🧵🧵
1. #AlphaFold is a deep learning system developed by #DeepMind, to predict the 3D #structure of #proteins from their #aminoacid sequence.
2. #AlphaFold has been applied and tested extensively in the biennial #CASP (Critical Assessment of protein Structure Prediction) experiment, and has achieved state-of-the-art performance.
Read 9 tweets
#singlecell analysis is revolutionizing medicine and changing the way we look at disease.

New perspective article just out🚨@NatureMedicine reflecting on @humancellatlas: informative for both #singlecell lovers❤️& skeptiks🤔

Let's map out where the field stands & what is next🧵
First, some context.

The genomics single cell field has started out 1-2 decades ago with a huge promise:

"Find the missing link between genes, diseases and therapies. This will bring completely novel therapeutics to the market & cure disease."
The underlying logic is straigtforward:

1. the cell is the main unit of living organisms
⬇️
2. cells break down in disease
⬇️
3. understanding cells helps understand how & why they break
⬇️
4. this helps with engineering new therapeutics
⬇️
5. new therapeutics will cure disease
Read 13 tweets
🧵🧵 THREAD: 10 reasons why #bioinformaticians should use #Nextflow 🧵🧵
1. #Nextflow is an open-source platform for #bioinformatics #pipelines and #workflows, designed to make them #scalable, #reproducible, and #portable.
2. #Nextflow allows #bioinformaticians to write their #pipelines and #workflows in a simple and expressive domain-specific language, called #Nextflow Script.
Read 11 tweets

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