@@ -80,3 +80,7 @@ RUN wget https://github.com/alexdobin/STAR/archive/2.5.1b.tar.gz \
# && tar -xvzf BBMap_38.87.tar.gz
# ENV PATH bbmap:$PATH
# ENV PATH bbmap:$PATH
RUN cp /cellranger-3.0.2.9001/cellranger-cs/3.0.2.9001/lib/python/cellranger/chemistry.py /cellranger-3.0.2.9001/cellranger-cs/3.0.2.9001/lib/python/cellranger/check.py
@@ -93,7 +93,7 @@ and use this tool to process single-cell RNA-Seq data from FASTQ format.
**Package**
UniverSC version 1.1.4
UniverSC version 1.2.1
**Maintainers**
@@ -120,7 +120,7 @@ If you wish to install `cellranger` and configure this script to run on a Linux
Note that `cellranger` installations that are pre-compiled on Linux will not run on Mac or Windows. Note that Mac OS and some Linux distributions also have different version of sed and rename. It is possible to compile an open-source version of Cell Ranger but it is tricky to install the dependencies so we recommend using our docker [image](#Docker) if you wish to do this.
### Beginners
### Command-line Beginners
If you are a beginner bioinformatician or wish to run this on a local computer (Mac or Windows), no problem! We provide a "docker" image containing everything needed to run it without installing the software needed. All you need to do is install [docker](https://docs.docker.com/desktop/) and follow our guide to use the [image](#Docker). This comes bundled with all the compatible versions needed to run it.
@@ -128,6 +128,13 @@ Note that you need to run the shell commands given in a unix-like command-line i
If you run into problems installing or running `launch_universc.sh` please don't hesistate to contact us via email or GitHub.
### Graphical application Users
We also provide a graphical user interface (GUI) based application to run the Docker [image](#Docker). Please install Docker as described above and pull our `tomkellygenetics/universc:latest` image using either the docker command-line interface (CLI) or the docker graphical application.
Once you have a docker image installed on your system, you can run the applicable binary available here:
package version 1.2.1. [https://github.com/minoda-lab/universc](https://github.com/minoda-lab/universc)
```
@article {Kelly2021.01.19.427209,
@@ -355,12 +362,12 @@ package version 1.1.4. [https://github.com/minoda-lab/universc](https://github.c
title = {{UniverSC}: a flexible cross-platform single-cell data processing pipeline},
elocation-id = {2021.01.19.427209},
year = {2021},
doi = {10.11.1.4021.01.19.427209},
doi = {10.11.2.1021.01.19.427209},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Single-cell RNA-sequencing analysis to quantify RNA molecules in individual cells has become popular owing to the large amount of information one can obtain from each experiment. We have developed UniverSC (https://github.com/minoda-lab/universc), a universal single-cell processing tool that supports any UMI-based platform. Our command-line tool enables consistent and comprehensive integration, comparison, and evaluation across data generated from a wide range of platforms.Competing Interest StatementThe authors have declared no competing interest.},
