Amit Rupani

1/ Even in the era of single-cell RNAseq, bulk-RNAseq data are still very valuable. 10 tools/papers related to bulk-RNAseq deconvolution.🧵

Incredible resource: analysis of Whole Genome Sequencing data on 10,478 cancer patients spanning 35 types identifies 330 candidate driver genes, including 74 new drivers. TP53 is a driver in 29‼️tumor types, followed by PIK3CA(18), ARID1A(16) & PTEN (14) nature.com/articles/s4158…

Evolution of delayed resistance to #immunotherapy in a #melanoma #responder: "37 tumor samples over 9 years from a patient with metastatic melanoma with complete clinical response to ICB followed by delayed recurrence and death" nature.com/articles/s4159…

Our multimodal model to combine TCR sequences with scRNA-seq is finally out. The most interesting part for me was observing a clear case where the combination of TCR sequence and cell state (RNA) preserved both clonotype and cell type information, leading to a more holistic cell representation that captures phenotype and functionality. We also decompose the contribution and importance of each modality. This was a really fun project spearheaded by @DrostFelix, whose amazing perseverance during a long review period, and collaboration with @schubert_benni and other fantastic collaborators, made it possible. Read the paper :nature.com/articles/s4146…

The human chromosomes are numbered incorrectly (The fourth in an irregular series of threads about #Bioinformatics.) As most people know, 22 of our chromosomes are numbered from longest to shortest, plus we have X and Y... 1/6

A major problem with cell-free tumor DNA to detect cancer (Liquid biopsy) is its very low quantity. Today @NatureMedicine use of #AI to overcome that issue with impressive results for radical signal-to-noise enrichment nature.com/articles/s4159… free access rdcu.be/dKNOx

SeqCAT: Sequence Conversion and Analysis Toolbox academic.oup.com/nar/advance-ar…

“NK cells are well-positioned to steal the immunotherapy spotlight away from T cells” nature.com/articles/d4158…

VILOCA: Sequencing quality-aware haplotype reconstruction and mutation calling for short- and long-read data biorxiv.org/content/10.110…

Figeno: multi-region genomic figures with long-read support. #GenomicsData #LongReads #FigureGenerator #PublicationGradeFigures #Bioinformatics academic.oup.com/bioinformatics…

MultiRNAflow: integrated analysis of temporal RNA-seq data with multiple biological conditions academic.oup.com/bioinformatics…

Unravelling undiagnosed rare disease cases by HiFi long-read genome sequencing. #RareDiseases @Solve_RD #HiFi #LongReads @PacBio @medrxivpreprint @ahoischen medrxiv.org/content/10.110…

Precise identification of cell states altered in disease using healthy single-cell references | Nature Genetics nature.com/articles/s4158…

LotOfCells: data visualization and statistics of single cell metadata biorxiv.org/content/10.110…

We analyzed all 5734 of the available WGS samples from The Cancer Genome Atlas, and find far, far smaller numbers of microbes than previous reports that appeared (with great fanfare) in @Nature and @CellCellPress. With @YuchenGe1 et al biorxiv.org/content/10.110…

The future of rapid and automated single-cell data analysis using reference mapping cell.com/cell/fulltext/…

chatomics! new blog post: Common mistakes when analyzing single-cell RNAseq data divingintogeneticsandgenomics.com/post/common-mi…

Empowering bioinformatics communities with Nextflow and nf-core biorxiv.org/cgi/content/sh… #biorxiv_bioinfo

Cancer therapy with antibodies: many approved and many more to come nature.com/articles/s4156…

Highly Effective Batch Effect Correction Method for RNA-seq Count Data biorxiv.org/content/10.110…