DOI: 10.6084/m9.figshare.25513528
title: scUTRquant SingleCellExperiment and SummarizedExperiment Objects

description: OverviewThis dataset contains R Bioconductor objects that have 3'UTR isoform counts quantified with the scUTRquant pipeline (https://doi.org/10.5281/zenodo.8118393). These objects are part of the minimum dataset required for verifying the analysis reported in Fansler et al., bioRxiv, 2023.Loading objectsThe objects can be loaded into R 4.2 using Bioconductor 3.16. A minimal Conda environment definition is provided for creating compatible environments. For example:<code>conda env create -n sce_bioc_3_16 -f envs/sce_bioc_3_16.min.yaml</code>The <b>.Rds</b> objects can be loaded with (for example):<code>sce &lt;- readRDS("sce/utrome_mm10_v2/bleckwehl21.txs.Rds")</code>DescriptionsThe objects are organized as follows:<code>envs</code> - Conda environment definitions<code>sce_bioc_3_16.full.yaml</code> - solved version for <code>osx-64</code> (for record only)<code>sce_bioc_3_16.min.yaml</code> - minimal version intended for reuse<code>sce</code> - SingleCellExperiment objects<code>gencode_vM25_pc_w500</code> - data quantified using truncated GENCODE vM25 protein coding transcripts<code>dahlin18.txs.Rds</code> - HSPCs from Dahlin et al., 2018<code>guo19.txs.Rds</code> - mESCs from Guo et al., 2019<code>tmuris.txs.Rds</code> - 10X Chromium 3' data from Tabula Muris <code>ximerakis19.txs.Rds</code> - aging brain samples from Ximerakis et al., 2019<code>utrome_hg38_v1</code> - data quantified using the Microwell-seq-derived annotation provided in scUTRquant<code>pbmc_10k_v3_fastq.txs.Rds</code> - 10X v3 kit demonstration 10K PBMCs<code>pbmc_1k_v2_fastq.txs.Rds</code> - 10X v2 kit demonstration 1K PBMCs<code>pbmc_1k_v3_fastq.txs.Rds</code> - 10X v3 kit demonstration 1K PBMCs<code>tsapiens.txs.full_annot.Rds</code> - 10X Chromium 3' data from Tabula Sapiens<code>utrome_mm10_v2</code> - data quantified using the Microwell-seq-derived annotation provided in scUTRquant<code>bleckwehl21.txs.Rds</code> - mESCs from Bleckwehl et al., 2021<code>guo19.txs.Rds</code> - mESCs from Guo et al., 2019<code>heart_10k_v3_fastq.txs.Rds</code> - 10X v3 kit demonstration 10K heart cells<code>heart_1k_v2_fastq.txs.Rds</code> - 10X v2 kit demonstration 1K heart cells<code>heart_1k_v3_fastq.txs.Rds</code> - 10X v3 kit demonstration 1K heart cells<code>merged.txs.full_annot.Rds</code> - combined atlas with annotations including HSPCs from Dahlin et al., 2018; mESCs from Guo et al., 2019; 10X Chromium 3' data from Tabula Muris; brain cells from Ximerakis et al., 2019<code>neuron_10k_v3_fastq.txs.Rds</code> - 10X v3 kit demonstration 10K neurons<code>neuron_1k_v2_fastq.txs.Rds</code> - 10X v2 kit demonstration 1K neurons<code>neuron_1k_v3_fastq.txs.Rds</code> - 10X v3 kit demonstration 1K neurons<code>se</code> - SummarizedExperiment objects of bulk 3'-seq or pseudobulk 10X Chromium 3' data<code>utrome_hg38_v1</code> - data quantified using the Microwell-seq-derived annotation provided in scUTRquant<code>kd6_essential_bulk_expressed.Rds</code> - K562 6-day essential Perturb-seq screen from Replogle et al., 2022<code>rd7_essential_bulk_expressed.Rds</code> - RPE1 7-day essential Perturb-seq screen from Replogle et al., 2022<code>utrome_mm10_v2</code> - data quantified using the Microwell-seq-derived annotation provided in scUTRquant<code>hspcs_bulk.txs.rds</code> - HSCs and MPPs from Sommerkamp et al., 2020Data Generation<b>UTRome Annotations</b>The annotations (kallisto indices) used in data quantification were generated in the pipelines:<code>gencode_vM25_pc_w500</code> - https://github.com/Mayrlab/txcutr-db (https://doi.org/10.5281/zenodo.8118405)<code>utrome_hg38_v1</code> - https://github.com/Mayrlab/hcl-utrome (https://doi.org/10.5281/zenodo.8118411)<code>utrome_mm10_v2</code> - https://github.com/Mayrlab/mca-utrome (https://doi.org/10.5281/zenodo.8118416)<b>Sample Sheets and Configurations</b>Sample sheets and configuration files for how the raw data were run in scUTRquant are available in the <code>scUTRquant-inputs</code> repository (https://doi.org/10.5281/zenodo.10901352).All raw data were run in scUTRquant (https://doi.org/10.5281/zenodo.8118393), with the exception of <code>hspcs_bulk.txs.rds</code> which used the pipeline at https://github.com/Mayrlab/sommerkamp20 (https://doi.org/10.5281/zenodo.10892210).<b>Post-processing Pipelines</b>Downstream of scUTRquant, additional annotation, filtering, merging, and summarization was performed in the following pipelines:<code>merged.txs.full_annot.Rds</code> - https://github.com/Mayrlab/atlas-mm (https://doi.org/10.5281/zenodo.10895352)<code>tsapiens.txs.full_annot.Rds</code> - https://github.com/Mayrlab/atlas-hs (https://doi.org/10.5281/zenodo.10895337)<code>(kd6|rd7)_essential_bulk_expressed.Rds</code> - https://github.com/Mayrlab/gwps-sq (https://doi.org/10.5281/zenodo.10895730)<b>Downstream Analyses</b>Additional downstream analyses which use these objects are available in https://github.com/Mayrlab/scUTRquant-figures (https://doi.org/10.5281/zenodo.8118443).