Merge branch 'dev' of github.com:minoda-lab/universc into dev

test/shared/smartseq3-test/Smartseq3_diySpike_R2.fastq.gz filter=lfs diff=lfs merge=lfs -text

test/shared/sciseq-v3-test/SRR7827205_S1_R1.fastq.gz filter=lfs diff=lfs merge=lfs -text

test/shared/sciseq-v3-test/SRR7827205_S1_R2.fastq.gz filter=lfs diff=lfs merge=lfs -text

test/shared/icell8-test/72618_KU812_L002_R2_001.fastq.gz filter=lfs diff=lfs merge=lfs -text

test/shared/cellranger-tiny-fastq/1.2.0/read-RA_si-TTTCATGA_lane-008-chunk-001.fastq.gz filter=lfs diff=lfs merge=lfs -text

test/shared/icell8-test/72618_KU812_L001_R1_001.fastq.gz filter=lfs diff=lfs merge=lfs -text

test/shared/icell8-test/72618_KU812_L001_R2_001.fastq.gz filter=lfs diff=lfs merge=lfs -text

test/shared/icell8-test/72618_KU812_L002_R1_001.fastq.gz filter=lfs diff=lfs merge=lfs -text

1.0.3

1.1.0

### 1.1.0 (in dev)

- add support for 5' technologies (e.g., Smart-Seq3, ICELL8 5')

- compatilibility with counting reads for non-UMI technologies (e.g., Smart-Seq2)

### 1.0.3

- unit tests for inDrops v3, SCI-Seq, Smart-Seq3

**Package**

UniverSC version 1.0.3

UniverSC version 1.1.0

**Maintainers**

        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.},

        eprint = {https://www.biorxiv.org/content/early/2021/01/19/2021.01.19.427209.full.pdf},

        journal = {{bioRxiv}},

        note = {package version 1.0.3},

        note = {package version 1.1.0},

        URL = {https://github.com/minoda-lab/universc},

}

    title = {{UniverSC}:  a flexible cross-platform single-cell data processing pipeline},

    author = {S. Thomas Kelly, Kai Battenberg, Nicola A. Hetherington, Makoto Hayashi, and Aki Minoda},

    year = {2021},

    note = {package version 1.0.3},

    note = {package version 1.1.0},

    url = {https://github.com/minoda-lab/universc},

  }

```

#### Pulling from remote DockerHub repository

We provide a docker image for UniverSC version 1.0.3.

We provide a docker image for UniverSC version 1.1.0.

You can import it if you have docker installed.

  -p,  --per-cell-data          Generates a file with basic run statistics along with per-cell data

       --non-umi or --read-only Force counting reads by adding or replacing UMI with a mock sequence

       --setup                  Set up whitelists for compatibility with new technology and exit

       --as-is                  Skips the FASTQ file conversion if the file already exists

<p><strong>Summary</strong></p>

<p>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. UniverSC is 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. Here we provide a guide to install and use this tool to process single-cell RNA-Seq data from FASTQ format.</p>

<p><strong>Package</strong></p>

<p>UniverSC version 1.0.3</p>

<p>UniverSC version 1.1.0</p>

<p><strong>Maintainers</strong></p>

<p>Tom Kelly<sup>†</sup> (RIKEN IMS) and Kai Battenberg<sup>†</sup> (RIKEN CSRS/IMS)</p>

<p>† These authors contributed equally to this work</p>

        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.},

        eprint = {https://www.biorxiv.org/content/early/2021/01/19/2021.01.19.427209.full.pdf},

        journal = {{bioRxiv}},

        note = {package version 1.0.3},

        note = {package version 1.1.0},

        URL = {https://github.com/minoda-lab/universc},

}

</code></pre>

    title = {{UniverSC}:  a flexible cross-platform single-cell data processing pipeline},

    author = {S. Thomas Kelly, Kai Battenberg, Nicola A. Hetherington, Makoto Hayashi, and Aki Minoda},

    year = {2021},

    note = {package version 1.0.3},

    note = {package version 1.1.0},

    url = {https://github.com/minoda-lab/universc},

  }</code></pre>

<h3 id="bug-reports">Bug Reports <span id="Issues"><span></h3>

<pre><code>docker login -u &quot;myusername&quot;</code></pre>

<p>If you cannot run docker on a remote server, contact your systems administrator.</p>

<h4 id="pulling-from-remote-dockerhub-repository">Pulling from remote DockerHub repository</h4>

<p>We provide a docker image for UniverSC version 1.0.3.</p>

<p>We provide a docker image for UniverSC version 1.1.0.</p>

<p>You can import it if you have docker installed.</p>

<pre><code>docker pull tomkellygenetics/universc:latest</code></pre>

<p>Then you can run convert with:</p>

  -p,  --per-cell-data          Generates a file with basic run statistics along with per-cell data

       --non-umi or --read-only Force counting reads by adding or replacing UMI with a mock sequence

       --setup                  Set up whitelists for compatibility with new technology and exit

       --as-is                  Skips the FASTQ file conversion if the file already exists