Merge pull request #82 from Mayrlab/dev

Milestone v0.4.1

README.md

@@ -4,6 +4,10 @@
 # scUTRquant
 A bioinformatics pipeline for single-cell 3' UTR isoform quantification.
 
+The accompanying manuscript is openly available at:
+
+> Fansler, M.M., Mitschka, S. & Mayr, C. Quantifying 3′UTR length from scRNA-seq data reveals changes independent of gene expression. *Nat Commun* **15**, 4050 (2024). [https://doi.org/10.1038/s41467-024-48254-9](https://doi.org/10.1038/s41467-024-48254-9)
+
 # Overview
 The **scUTRquant** pipeline builds on `kallisto bus` to provide a reusable tool for 
 quantifying 3' UTR isoforms from 3'-end tag-based scRNA-seq datasets. The pipeline
@@ -202,6 +206,11 @@ On GitHub runners with 2-3 cores, these examples have typical execution times of
 On HPC systems with multiple nodes with multiple cores, a large job (e.g., 1-2TB raw data) 
 can process in under an hour when properly configured.
 
+## Full Examples
+The inputs used to process data in [the manuscript][ref:scUTRquant] are also available in the 
+[scUTRquant-inputs repository](https://github.com/Mayrlab/scUTRquant-inputs).
+These also include individual Snakemake pipelines to download atlas-scale datasets. 
+
 # File Specifications
 ## Configuration File
 
@@ -318,12 +327,11 @@ snakemake --profile profile_name --configfile examples/neuron_1k_v3_fastq/config
 
 # Citation
 
-Fansler, M. M., Mitschka, S., & Mayr, C. (2023). Comprehensive annotation of 3′UTRs from primary cells and their quantification from scRNA-seq data.
-*bioRxiv*, 2021.11.22.469635. https://doi.org/10.1101/2021.11.22.469635
+Fansler, M.M., Mitschka, S. & Mayr, C. Quantifying 3′UTR length from scRNA-seq data reveals changes independent of gene expression. *Nat Commun* **15**, 4050 (2024). [https://doi.org/10.1038/s41467-024-48254-9](https://doi.org/10.1038/s41467-024-48254-9)
 
 
 <!-- References -->
 
-[ref:scUTRquant]: https://doi.org/10.1101/2021.11.22.469635
+[ref:scUTRquant]: https://doi.org/10.1038/s41467-024-48254-9
 [ref:snakemake]: https://snakemake.readthedocs.io/en/stable/index.html
 [ref:txcutr]: https://doi.org/doi:10.18129/B9.bioc.txcutr

Snakefile

@@ -1,4 +1,4 @@
-container: "docker://mfansler/scutr-quant:0.1.5"
+container: "docker://mfansler/scutr-quant:0.4.0"
 configfile: "config.yaml"
 
 import os

docker/Dockerfile

@@ -1,26 +1,9 @@
-FROM --platform=linux/amd64 condaforge/mambaforge:4.10.3-3
-
-SHELL ["/bin/bash", "--login", "-c"]
-
-# Install custom kallisto build
-COPY kallisto-build.yaml .
-RUN mamba env create -f kallisto-build.yaml -n kallisto-build \
-  && git clone -b stranded --single-branch https://github.com/mfansler/kallisto.git /tmp/kallisto \
-  && mkdir -p /tmp/kallisto/build && cd /tmp/kallisto/build \
-  && . /opt/conda/etc/profile.d/conda.sh \
-  && conda activate kallisto-build \
-  && cmake /tmp/kallisto && make && make install \
-  && cd $HOME && rm -rf /tmp/kallisto \
-  && conda deactivate \
-  && mamba env remove -n kallisto-build -y \
-  && mamba clean -qafy
-
-# readr needs timezone info
-RUN apt-get update > /dev/null \
-  && DEBIAN_FRONTEND="noninteractive" apt-get install --no-install-recommends -y tzdata > /dev/null \
-  && apt-get clean
+FROM --platform=linux/amd64 mambaorg/micromamba:1.5.8
 
 # Install required packages in base
-COPY scutr-quant.yaml .
-RUN mamba env update -n base -f scutr-quant.yaml \
-  && mamba clean -qafy
+COPY --chown=$MAMBA_USER:$MAMBA_USER scutr-quant.yaml /tmp/scutr-quant.yaml
+RUN micromamba install -yn base -f /tmp/scutr-quant.yaml \
+  && micromamba clean -qafy
+
+# Put base bin on PATH
+ENV PATH "$MAMBA_ROOT_PREFIX/bin:$PATH"

docker/scutr-quant.yaml

@@ -3,12 +3,26 @@ channels:
   - conda-forge
   - bioconda
   - defaults
+  - merv
 dependencies:
+  ## downloading
+  - gzip
+  - tar
+  - wget
+
+  ## kallisto-bustools
+  - merv::kallisto=0.46.2sq
   - bustools=0.40.0
-  - r-base=4.0
-  - r-tidyverse=1.3
-  - r-cowplot=1.1
-  - bioconductor-singlecellexperiment=1.10
-  - bioconductor-plyranges=1.8
-  - xorg-libxt
-  - fonts-conda-ecosystem
+
+  ## sce + reporting
+  - r-base=4.1
+  - r-dplyr=1.0
+  - r-ggplot2=3.3
+  - r-matrix=1.4
+  - r-readr=2.1
+  - r-rmarkdown=2.14
+  - r-stringr=1.4
+  - bioconductor-hdf5array=1.22
+  - bioconductor-singlecellexperiment=1.16
+  - bioconductor-plyranges=1.14
+  - openssl=1

extdata/targets/targets.yaml

@@ -14,8 +14,8 @@ utrome_mm10_v2:
   gtf: "utrome.e30.t5.gc25.pas3.f0.9999.w500.gtf"
   kdx: "utrome.e30.t5.gc25.pas3.f0.9999.w500.kdx"
   merge_tsv: "utrome.e30.t5.gc25.pas3.f0.9999.w500.m200.tsv"
-  tx_annots: "utrome_txs_annotation.Rds"
-  gene_annots: "utrome_genes_annotation.Rds"
+  tx_annots: "utrome_mm10_v2_tx_annots.2024.05.13.Rds"
+  gene_annots: "utrome_mm10_v2_gene_annots.2024.05.13.Rds"
   download_script: "download_utrome.sh"
 
 utrome_hg38_v1:
@@ -24,8 +24,8 @@ utrome_hg38_v1:
   gtf: "utrome.e30.t5.gc39.pas3.f0.9999.w500.gtf"
   kdx: "utrome.e30.t5.gc39.pas3.f0.9999.w500.kdx"
   merge_tsv: "utrome.e30.t5.gc39.pas3.f0.9999.w500.m200.tsv"
-  tx_annots: "utrome_txs_annotation.Rds"
-  gene_annots: "utrome_genes_annotation.Rds"
+  tx_annots: "utrome_hg38_v1_tx_annots.2024.05.13.Rds"
+  gene_annots: "utrome_hg38_v1_gene_annots.2024.05.13.Rds"
   download_script: "download_utrome.sh"
 
 ## example custom target using GENCODE

extdata/targets/utrome_hg38_v1/download_utrome.sh

@@ -7,7 +7,9 @@ wget -O tmp.tar.gz "https://figshare.com/ndownloader/files/35874803?private_link
 
 # hg38 Annotations
 ## txs
-wget -O utrome_txs_annotation.Rds "https://figshare.com/ndownloader/files/36741828?private_link=9f97fd9772574bee6a61"
+wget -O utrome_hg38_v1_tx_annots.2024.05.13.csv.gz "https://figshare.com/ndownloader/files/46407826?private_link=9f97fd9772574bee6a61"
+wget -O utrome_hg38_v1_tx_annots.2024.05.13.Rds "https://figshare.com/ndownloader/files/46407829?private_link=9f97fd9772574bee6a61"
 
 ## genes
-wget -O utrome_genes_annotation.Rds "https://figshare.com/ndownloader/files/36741825?private_link=9f97fd9772574bee6a61"
+wget -O utrome_hg38_v1_gene_annots.2024.05.13.csv.gz "https://figshare.com/ndownloader/files/46407820?private_link=9f97fd9772574bee6a61"
+wget -O utrome_hg38_v1_gene_annots.2024.05.13.Rds "https://figshare.com/ndownloader/files/46407823?private_link=9f97fd9772574bee6a61"

extdata/targets/utrome_mm10_v2/download_utrome.sh

@@ -7,7 +7,9 @@ wget -O tmp.tar.gz "https://figshare.com/ndownloader/files/36677958?private_link
 
 # mm10 Annotations
 ## txs
-wget -O utrome_txs_annotation.Rds "https://figshare.com/ndownloader/files/36741822?private_link=78bbfa3c5e58a8cc5275"
+wget -O utrome_mm10_v2_tx_annots.2024.05.13.csv.gz "https://figshare.com/ndownloader/files/46407730?private_link=78bbfa3c5e58a8cc5275"
+wget -O utrome_mm10_v2_tx_annots.2024.05.13.Rds "https://figshare.com/ndownloader/files/46407733?private_link=78bbfa3c5e58a8cc5275"
 
 ## genes
-wget -O utrome_genes_annotation.Rds "https://figshare.com/ndownloader/files/36741819?private_link=78bbfa3c5e58a8cc5275"
+wget -O utrome_mm10_v2_gene_annots.2024.05.13.csv.gz "https://figshare.com/ndownloader/files/46407724?private_link=78bbfa3c5e58a8cc5275"
+wget -O utrome_mm10_v2_gene_annots.2024.05.13.Rds "https://figshare.com/ndownloader/files/46407727?private_link=78bbfa3c5e58a8cc5275"