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?? ?? ?It’s the final day of Mantle’s 12 Days of Bioinformatics! We’re wrapping up our series with a deep dive into visualizing flow cytometry data. Using Python and FCSparser, you can seamlessly convert complex flow cytometry data into tabular formats for analysis, machine learning, and visualization. Learn how to transform FCS files into pandas DataFrames and create plots like forward scatter (FSC) vs. side scatter (SSC)—key steps in analyzing cell populations. ?? For more information, visit our guide here: ???https://lnkd.in/gYXcdr4P Thank you for joining us on this journey to make bioinformatics more accessible, efficient, and fun. Here’s to advancing science together in the year ahead! 2??0??2??5????? #Bioinformatics #FlowCytometry #Python #DataAnalysis

?? Day 11 of 12 Days of Bioinformatics!??? Today, we’re exploring?Declarative Plotting in Python—easily create beautiful visualizations to communicate your data. From Seaborn to Holoviews, declarative plotting simplifies exploratory data analysis and makes presentation-ready figures easier than ever. Check out the article for comparisons across popular libraries and see how declarative plotting can streamline your workflow: ?? https://lnkd.in/gbkUuCTQ One more day to go in our bioinformatics journey—stay tuned for the finale!??? ?? ? #Bioinformatics #DataVisualization #Python

?? Day 10 of 12 Days of Bioinformatics! ?? Today, we’re diving into visualizing an image series with Python. Using tools like Holoviews and Bokeh, you can easily create interactive displays for microscopy or time-lapse imaging data—all without needing to write JavaScript or complex callbacks. Check out the article for a step-by-step guide: ?? https://lnkd.in/gRRcRDqZ

???? Day 9 of the 12 Days of Bioinformatics: Cell Tracking Made Simple ???? Cell tracking is a powerful technique for understanding cell behavior over time, whether you’re studying development, migration, or response to treatment. With MantleBio’s cell tracking workflow, you can easily analyze time-lapse imaging data, quantify cell trajectories, and extract meaningful insights. Check out the full workflow here: https://lnkd.in/gDJEtcTQ Stay tuned for Day 10 as we continue our bioinformatics journey! #Bioinformatics #CompBio #DataAnalysis

?? Day 8 of the 12 Days of Bioinformatics: Fluorescence Quantification with MantleBio ?? With this fluorescence quantification workflow, you can easily quantify the concentration of labeled molecules in segmented regions. We leverage the scikit-image?package in Python to make processing standardized, reliable, and reproducible. Get started here: https://lnkd.in/gnFNAkkS Explore other workflows here: https://lnkd.in/g3_CxP9J #Bioinformatics #LifeSciences #FluorescenceQuantification

??????For day 7 of the 12 days of bioinformatics, we're zooming into the world of image analysis with CellProfiler.??? CellProfiler is a powerful tool for extracting quantitative data from biological images. What can you do with it? ?? High-Throughput Screening (HTS): Easily analyze large image volumes to quantify changes in cell morphology, viability, and other phenotypic traits. Ideal for understanding compound effects at scale. ?? Fluorescence Microscopy Analysis: Measure fluorescence intensity and distribution to study protein localization, gene expression, and signaling pathways. Precision insights into complex cellular processes await! ?? Developmental Biology: Track changes in cell populations and structures over time to uncover developmental mechanisms and abnormalities—providing a deeper understanding of growth at the cellular level. The CellProfiler workflow on Mantle makes it easy to quantify biological images reproducibly, automatically, and at high-throughput. ???Explore the full documentation here: https://lnkd.in/egVspwrJ #Bioinformatics #CellProfiler #ImageAnalysis #DataScience #HighThroughputScreening #FluorescenceMicroscopy

?? Day 6 of the 12 Days of Bioinformatics! ?? On day 3 we explored preprocessing spatial transcriptomics data. Today, we're taking it a step further with tertiary analysis! Easily create heatmaps, spatial feature plots, and other visualizations—all without the need for installation or setup. Whether you're an experienced bioinformatician or new to the field, this enables easy and reproducible end-to-end analysis for your spatial transcriptomics studies. ???Revisit preprocessing workflows: https://lnkd.in/gPwSt-aC ???Dive into visualizations: https://lnkd.in/gsMDtSX8 #Bioinformatics #SpatialTranscriptomics

?????Day 5 of 12 Days of Bioinformatics: Bulk RNA-seq Analysis with Scanpy????? Welcome back to our bioinformatics journey! Today, we're diving into bulk RNA sequencing (RNA-seq) analysis using the powerful Scanpy toolkit. ??????Scanpy offers efficient data processing and advanced analytical capabilities. It's a fantastic option for those looking to explore complex transcriptomic landscapes. While Scanpy is often associated with single-cell RNA-seq, this workflow showcases its versatility in handling bulk RNA-seq data, too! Key Applications: ???Disease Mechanism Studies:?Explore differential gene expression between healthy and diseased tissues to uncover molecular mechanisms of diseases like cancer and neurodegenerative disorders. ???Biomarker Discovery:?Identify potential biomarkers for disease diagnosis and prognosis by pinpointing genes differentially expressed in specific conditions. ???Drug Response and Toxicology:?Assess the impact of treatments on gene expression to aid in drug development and safety assessments. This workflow is perfect for researchers eager to apply advanced computational techniques to bulk RNA-seq data. Whether you're into functional genomics or drug response studies, this guide has you covered! Check out the full workflow here: https://lnkd.in/gS5WmPeD ???Stay tuned for more bioinformatics insights as we continue our 12-day series. ?? #Bioinformatics #RNAseq #Scanpy #DataAnalysis

No offense to other types of sequencing data—but I think there’s something ???magical ???about seeing data come to life. ?? That’s why I love ???spatial transcriptomics ???—and why it’s the focus of Day 3?? of bioinformatics. What else makes spatial transcriptomics wonderful? ??It’s advancing our understanding of cancer and the tumor microenvironment ??It’s uncovering key insights into developmental biology and how organisms grow and change ??It’s driving new techniques in precision medicine, enabling highly targeted treatments With Mantle, processing 10X Visium spatial transcriptomics data is effortless—run Spaceranger Count without setup, and for free. Learn more: https://lnkd.in/gn_nF4qT ??What breakthroughs in life sciences do you find magical? #SpatialTranscriptomics #Bioinformatics #GeneExpression

Only a few years ago, "DNA sequencing" and "Illumina" were practically synonyms. But for Day 4?? of MantleBio’s 12 Days of Bioinformatics ??, we’re excited to feature processing sequencing data from the Element Biosciences AVITI! ???New innovators in the DNA sequencing market, like Element Biosciences, are making novel techniques possible and more science accessible. The AVITI sequencer offers high-quality, cost-effective sequencing with flexible configurations, providing researchers with new options for their genomic workflows. ???Mantle makes it easy to run Element’s Bases2Fastq pipeline, enabling seamless conversion of AVITI sequencing base call files into FASTQ format. This workflow is ready-to-run, so you can focus on the science, not the setup. Check out our docs to learn more and get started: https://lnkd.in/gFhNdD6m What are your favorite recent innovations in DNA sequencing? #Genomics #Bioinformatics #SequencingData #MantlePlatform #ElementBiosciences