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#rnaseq — Public Fediverse posts

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  1. Today we just added 4195 human gene expression studies to the dee2.io data resource -- that is ~200k samples. We're still running way behind what is released by NCBI, but with the current prices of computer parts we're doing the best we can with the limited funding we got.
    #rnaseq #bioinformatics #genomics

  2. Today we just added 4195 human gene expression studies to the dee2.io data resource -- that is ~200k samples. We're still running way behind what is released by NCBI, but with the current prices of computer parts we're doing the best we can with the limited funding we got.
    #rnaseq #bioinformatics #genomics

  3. Today we just added 4195 human gene expression studies to the dee2.io data resource -- that is ~200k samples. We're still running way behind what is released by NCBI, but with the current prices of computer parts we're doing the best we can with the limited funding we got.
    #rnaseq #bioinformatics #genomics

  4. Today we just added 4195 human gene expression studies to the dee2.io data resource -- that is ~200k samples. We're still running way behind what is released by NCBI, but with the current prices of computer parts we're doing the best we can with the limited funding we got.
    #rnaseq #bioinformatics #genomics

  5. Today we just added 4195 human gene expression studies to the dee2.io data resource -- that is ~200k samples. We're still running way behind what is released by NCBI, but with the current prices of computer parts we're doing the best we can with the limited funding we got.
    #rnaseq #bioinformatics #genomics

  6. Pipeline release! nf-core/scrnaseq v4.2.0 - 4.2.0!
    Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligners and empty-droplet detection
    Please see the changelog: github.com/nf-core/scrnaseq/re

    #10xgenomics #10xgenomics #alevin #bustools #cellranger #kallisto #rnaseq #singlecell #starsolo #nfcore #openscience #nextflow #bioinformatics

  7. Pipeline release! nf-core/scrnaseq v4.2.0 - 4.2.0!
    Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligners and empty-droplet detection
    Please see the changelog: github.com/nf-core/scrnaseq/re

    #10xgenomics #10xgenomics #alevin #bustools #cellranger #kallisto #rnaseq #singlecell #starsolo #nfcore #openscience #nextflow #bioinformatics

  8. Pipeline release! nf-core/scrnaseq v4.2.0 - 4.2.0!
    Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligners and empty-droplet detection
    Please see the changelog: github.com/nf-core/scrnaseq/re

    #10xgenomics #10xgenomics #alevin #bustools #cellranger #kallisto #rnaseq #singlecell #starsolo #nfcore #openscience #nextflow #bioinformatics

  9. Pipeline release! nf-core/scrnaseq v4.2.0 - 4.2.0!
    Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligners and empty-droplet detection
    Please see the changelog: github.com/nf-core/scrnaseq/re

    #10xgenomics #10xgenomics #alevin #bustools #cellranger #kallisto #rnaseq #singlecell #starsolo #nfcore #openscience #nextflow #bioinformatics

  10. Pipeline release! nf-core/scrnaseq v4.2.0 - 4.2.0!
    Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligners and empty-droplet detection
    Please see the changelog: github.com/nf-core/scrnaseq/re

    #10xgenomics #10xgenomics #alevin #bustools #cellranger #kallisto #rnaseq #singlecell #starsolo #nfcore #openscience #nextflow #bioinformatics

  11. 6/ Lastly, in nature.com/articles/s41592-023. the observed sensitivity deficits stem from three sources: (1) poor annotation of 3′ gene ends; (2) issues with intronic read incorporation; and (3) gene overlap-derived read loss. #singlecell #RNAseq

  12. 6/ Lastly, in nature.com/articles/s41592-023. the observed sensitivity deficits stem from three sources: (1) poor annotation of 3′ gene ends; (2) issues with intronic read incorporation; and (3) gene overlap-derived read loss. #singlecell #RNAseq

  13. 6/ Lastly, in nature.com/articles/s41592-023. the observed sensitivity deficits stem from three sources: (1) poor annotation of 3′ gene ends; (2) issues with intronic read incorporation; and (3) gene overlap-derived read loss. #singlecell #RNAseq

  14. 6/ Lastly, in nature.com/articles/s41592-023. the observed sensitivity deficits stem from three sources: (1) poor annotation of 3′ gene ends; (2) issues with intronic read incorporation; and (3) gene overlap-derived read loss. #singlecell #RNAseq

  15. 6/ Lastly, in nature.com/articles/s41592-023. the observed sensitivity deficits stem from three sources: (1) poor annotation of 3′ gene ends; (2) issues with intronic read incorporation; and (3) gene overlap-derived read loss. #singlecell #RNAseq

  16. Pipeline release! nf-core/scnanoseq v1.3.0 - nf-core/scnanoseq v1.3.0 - Steel Elephant!
    Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics
    Please see the changelog: github.com/nf-core/scnanoseq/r

    #10xgenomics #longreadsequencing #nanopore #rnaseq #rnaseq #scrnaseq #singlecell #nfcore #openscience #nextflow #bioinformatics

  17. Pipeline release! nf-core/scnanoseq v1.3.0 - nf-core/scnanoseq v1.3.0 - Steel Elephant!
    Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics
    Please see the changelog: github.com/nf-core/scnanoseq/r

    #10xgenomics #longreadsequencing #nanopore #rnaseq #rnaseq #scrnaseq #singlecell #nfcore #openscience #nextflow #bioinformatics

  18. Pipeline release! nf-core/scnanoseq v1.3.0 - nf-core/scnanoseq v1.3.0 - Steel Elephant!
    Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics
    Please see the changelog: github.com/nf-core/scnanoseq/r

    #10xgenomics #longreadsequencing #nanopore #rnaseq #rnaseq #scrnaseq #singlecell #nfcore #openscience #nextflow #bioinformatics

  19. Pipeline release! nf-core/scnanoseq v1.3.0 - nf-core/scnanoseq v1.3.0 - Steel Elephant!
    Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics
    Please see the changelog: github.com/nf-core/scnanoseq/r

    #10xgenomics #longreadsequencing #nanopore #rnaseq #rnaseq #scrnaseq #singlecell #nfcore #openscience #nextflow #bioinformatics

  20. Pipeline release! nf-core/scnanoseq v1.3.0 - nf-core/scnanoseq v1.3.0 - Steel Elephant!
    Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics
    Please see the changelog: github.com/nf-core/scnanoseq/r

    #10xgenomics #longreadsequencing #nanopore #rnaseq #rnaseq #scrnaseq #singlecell #nfcore #openscience #nextflow #bioinformatics

  21. Pipeline release! nf-core/differentialabundance v2.0.0 - v2.0.0 - 2026-06-23!
    Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq
    Please see the changelog: github.com/nf-core/differentia

    #atacseq #chipseq #deseq2 #differentialabundance #differentialexpression #gsea #limma #microarray #rnaseq #shiny #nfcore #openscience #nextflow #bioinformatics

  22. Pipeline release! nf-core/differentialabundance v2.0.0 - v2.0.0 - 2026-06-23!
    Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq
    Please see the changelog: github.com/nf-core/differentia

    #atacseq #chipseq #deseq2 #differentialabundance #differentialexpression #gsea #limma #microarray #rnaseq #shiny #nfcore #openscience #nextflow #bioinformatics

  23. Pipeline release! nf-core/differentialabundance v2.0.0 - v2.0.0 - 2026-06-23!
    Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq
    Please see the changelog: github.com/nf-core/differentia

    #atacseq #chipseq #deseq2 #differentialabundance #differentialexpression #gsea #limma #microarray #rnaseq #shiny #nfcore #openscience #nextflow #bioinformatics

  24. Pipeline release! nf-core/differentialabundance v2.0.0 - v2.0.0 - 2026-06-23!
    Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq
    Please see the changelog: github.com/nf-core/differentia

    #atacseq #chipseq #deseq2 #differentialabundance #differentialexpression #gsea #limma #microarray #rnaseq #shiny #nfcore #openscience #nextflow #bioinformatics

  25. Pipeline release! nf-core/differentialabundance v2.0.0 - v2.0.0 - 2026-06-23!
    Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq
    Please see the changelog: github.com/nf-core/differentia

    #atacseq #chipseq #deseq2 #differentialabundance #differentialexpression #gsea #limma #microarray #rnaseq #shiny #nfcore #openscience #nextflow #bioinformatics

  26. New co-authored manuscript on liver cancer multi-omics:

    Integrated Multi-omic Analyses Reveal Novel Gene-Metabolite Relationships in Human Steatohepatitic Hepatocellular Carcinoma
    Anspach et al., jlr.org/article/S0022-2275(26)

    8 patients, *paired samples* of cancer and adjacent normal!! (made the statistics so nice to work with and look for correlations between rna-seq and metabolomics).

    #Bioinformatics #Metabolomics #RNASeq

  27. New co-authored manuscript on liver cancer multi-omics:

    Integrated Multi-omic Analyses Reveal Novel Gene-Metabolite Relationships in Human Steatohepatitic Hepatocellular Carcinoma
    Anspach et al., jlr.org/article/S0022-2275(26)

    8 patients, *paired samples* of cancer and adjacent normal!! (made the statistics so nice to work with and look for correlations between rna-seq and metabolomics).

    #Bioinformatics #Metabolomics #RNASeq

  28. New co-authored manuscript on liver cancer multi-omics:

    Integrated Multi-omic Analyses Reveal Novel Gene-Metabolite Relationships in Human Steatohepatitic Hepatocellular Carcinoma
    Anspach et al., jlr.org/article/S0022-2275(26)

    8 patients, *paired samples* of cancer and adjacent normal!! (made the statistics so nice to work with and look for correlations between rna-seq and metabolomics).

    #Bioinformatics #Metabolomics #RNASeq

  29. New co-authored manuscript on liver cancer multi-omics:

    Integrated Multi-omic Analyses Reveal Novel Gene-Metabolite Relationships in Human Steatohepatitic Hepatocellular Carcinoma
    Anspach et al., jlr.org/article/S0022-2275(26)

    8 patients, *paired samples* of cancer and adjacent normal!! (made the statistics so nice to work with and look for correlations between rna-seq and metabolomics).

    #Bioinformatics #Metabolomics #RNASeq

  30. New co-authored manuscript on liver cancer multi-omics:

    Integrated Multi-omic Analyses Reveal Novel Gene-Metabolite Relationships in Human Steatohepatitic Hepatocellular Carcinoma
    Anspach et al., jlr.org/article/S0022-2275(26)

    8 patients, *paired samples* of cancer and adjacent normal!! (made the statistics so nice to work with and look for correlations between rna-seq and metabolomics).

    #Bioinformatics #Metabolomics #RNASeq

  31. When I first tried to assemble transcripts from #RNASeq data, I often wished for a handy overview of the #bioinformatics pipeline, from acquiring sequencer data to attaching descriptions to protein sequences. This video is my attempt to fill that gap, building upon our 2021 paper identifying proteins in #chia (Salvia hispanica) based on assembled transcript sequences. I hope you enjoy it!

    youtube.com/watch?v=ZtJWaWrTXyA

  32. When I first tried to assemble transcripts from #RNASeq data, I often wished for a handy overview of the #bioinformatics pipeline, from acquiring sequencer data to attaching descriptions to protein sequences. This video is my attempt to fill that gap, building upon our 2021 paper identifying proteins in #chia (Salvia hispanica) based on assembled transcript sequences. I hope you enjoy it!

    youtube.com/watch?v=ZtJWaWrTXyA

  33. When I first tried to assemble transcripts from #RNASeq data, I often wished for a handy overview of the #bioinformatics pipeline, from acquiring sequencer data to attaching descriptions to protein sequences. This video is my attempt to fill that gap, building upon our 2021 paper identifying proteins in #chia (Salvia hispanica) based on assembled transcript sequences. I hope you enjoy it!

    youtube.com/watch?v=ZtJWaWrTXyA

  34. When I first tried to assemble transcripts from #RNASeq data, I often wished for a handy overview of the #bioinformatics pipeline, from acquiring sequencer data to attaching descriptions to protein sequences. This video is my attempt to fill that gap, building upon our 2021 paper identifying proteins in #chia (Salvia hispanica) based on assembled transcript sequences. I hope you enjoy it!

    youtube.com/watch?v=ZtJWaWrTXyA

  35. When I first tried to assemble transcripts from #RNASeq data, I often wished for a handy overview of the #bioinformatics pipeline, from acquiring sequencer data to attaching descriptions to protein sequences. This video is my attempt to fill that gap, building upon our 2021 paper identifying proteins in #chia (Salvia hispanica) based on assembled transcript sequences. I hope you enjoy it!

    youtube.com/watch?v=ZtJWaWrTXyA

  36. Eight frontier LLMs, one RNA-seq dataset. We had them reproduce a published Candida auris analysis by using Orbit to drive Galaxy.

    Six models independently replicated the original SCF1 downregulation finding—while their API costs varied 47× ($2.82–$131.83).

    Read what we learned: galaxyproject.org/news/2026-06

    #UseGalaxy #RNAseq #AI #LLM #Bioinformatics

  37. Eight frontier LLMs, one RNA-seq dataset. We had them reproduce a published Candida auris analysis by using Orbit to drive Galaxy.

    Six models independently replicated the original SCF1 downregulation finding—while their API costs varied 47× ($2.82–$131.83).

    Read what we learned: galaxyproject.org/news/2026-06

    #UseGalaxy #RNAseq #AI #LLM #Bioinformatics

  38. Eight frontier LLMs, one RNA-seq dataset. We had them reproduce a published Candida auris analysis by using Orbit to drive Galaxy.

    Six models independently replicated the original SCF1 downregulation finding—while their API costs varied 47× ($2.82–$131.83).

    Read what we learned: galaxyproject.org/news/2026-06

    #UseGalaxy #RNAseq #AI #LLM #Bioinformatics

  39. Eight frontier LLMs, one RNA-seq dataset. We had them reproduce a published Candida auris analysis by using Orbit to drive Galaxy.

    Six models independently replicated the original SCF1 downregulation finding—while their API costs varied 47× ($2.82–$131.83).

    Read what we learned: galaxyproject.org/news/2026-06

    #UseGalaxy #RNAseq #AI #LLM #Bioinformatics

  40. Eight frontier LLMs, one RNA-seq dataset. We had them reproduce a published Candida auris analysis by using Orbit to drive Galaxy.

    Six models independently replicated the original SCF1 downregulation finding—while their API costs varied 47× ($2.82–$131.83).

    Read what we learned: galaxyproject.org/news/2026-06

    #UseGalaxy #RNAseq #AI #LLM #Bioinformatics

  41. Pipeline release! nf-core/rnavar v1.3.0 - nf-core/rnavar 1.3.0 - Silent Nostromo!
    gatk4 RNA variant calling pipeline
    Please see the changelog: github.com/nf-core/rnavar/rele

    #gatk4 #rna #rnaseq #variantcalling #worflow #nfcore #openscience #nextflow #bioinformatics

  42. Pipeline release! nf-core/rnavar v1.3.0 - nf-core/rnavar 1.3.0 - Silent Nostromo!
    gatk4 RNA variant calling pipeline
    Please see the changelog: github.com/nf-core/rnavar/rele

    #gatk4 #rna #rnaseq #variantcalling #worflow #nfcore #openscience #nextflow #bioinformatics

  43. Pipeline release! nf-core/rnavar v1.3.0 - nf-core/rnavar 1.3.0 - Silent Nostromo!
    gatk4 RNA variant calling pipeline
    Please see the changelog: github.com/nf-core/rnavar/rele

    #gatk4 #rna #rnaseq #variantcalling #worflow #nfcore #openscience #nextflow #bioinformatics

  44. Pipeline release! nf-core/rnavar v1.3.0 - nf-core/rnavar 1.3.0 - Silent Nostromo!
    gatk4 RNA variant calling pipeline
    Please see the changelog: github.com/nf-core/rnavar/rele

    #gatk4 #rna #rnaseq #variantcalling #worflow #nfcore #openscience #nextflow #bioinformatics