Processed data for the sRNA landscape chapter
<p><strong>Processed data to be used in analyses related to the sRNA landscape. </strong></p> <p><strong>1) small RNA processed data from stem trichomes</strong>: <a href="https://zenodo.org/api/files/88937ea4-8f58-4970-a931-6f8c8388db87/2020-12-17_11-23_results_stem_trichomes.tar.gz">2020-12-17_11-23_results_stem_trichomes.tar.gz </a></p> <ul> <li>Original small RNA-seq fastq files: available at <a href="https://doi.org/10.5281/zenodo.4105911">https://doi.org/10.5281/zenodo.4105911</a></li> <li>Software: small-rna-seq-pipeline v0.4.4 available at <a href="https://zenodo.org/record/4333786">https://zenodo.org/record/4333786</a></li> </ul> <p> </p> <p><strong>2) small RNA processed data from bald stem, leaf primordium and leaf: </strong></p> <p>xxxx === to be added === xxx</p> <p> </p> <p><strong>3) mRNA-seq processed data (raw and scaled counts) from different tissues (stem trichomes, bald stem, leaf, leaf primordium): </strong> <a href="https://zenodo.org/api/files/1c5ca622-83cf-4ab6-8fc5-7c2f54dc84bb/20201117_snakemake_messenger_rnaseq_trichomes_and_other_tissues.tar.gz">20201117_snakemake_messenger_rnaseq_trichomes_and_other_tissues.tar.gz</a></p> <p>This file was obtained from the following original mRNA-seq fastq files:</p> <ul> <li>Stem trichomes of Moneymaker: <a href="https://doi.org/10.5281/zenodo.3569304">dataset available here</a></li> <li>Stem trichomes of LA0716: <a href="https://doi.org/10.5281/zenodo.3569304">dataset available here</a></li> <li>Stem trichomes of PI127826: <a href="https://doi.org/10.5281/zenodo.3611143">dataset available here</a></li> <li>Bald stems, leaf primordia and leaves of Moneymaker, LA0716 and PI127826: <a href="https://doi.org/10.5281/zenodo.3954272">datasets are available here</a>. Samples S28 to S48 were used. </li> </ul> <p>The pipeline used was <a href="https://github.com/BleekerLab/snakemake_rnaseq/releases/tag/v0.3.4)">Snakemake RNA-seq release 0.3.4</a></p> <p>The file contains:</p> <ul> <li><a href="https://zenodo.org/api/files/10c9d73a-f52b-4923-a793-2fe3326d5587/raw_counts.parsed.tsv?versionId=475a35bb-424d-48f0-bdf8-6ede0455c26e">raw_counts.parsed.tsv</a>: contains the raw counts that can be used for differential expression analysis (e.g. with DESeq2).</li> <li><a href="https://zenodo.org/api/files/10c9d73a-f52b-4923-a793-2fe3326d5587/scaled_counts.tsv?versionId=c1ae1e86-c797-42c8-ac88-f250b97d09b1">scaled_counts.tsv</a>: contains counts that are scaled between samples. This can be used for heatmap creation or PCA analysis for instance. NOT for differential analysis. </li> <li><a href="https://zenodo.org/api/files/10c9d73a-f52b-4923-a793-2fe3326d5587/samples.tsv?versionId=ebefd1b7-50cd-4408-88f6-0770d8540191">samples.tsv</a>.: a file listing the fastq files analysed. </li> <li><a href="https://zenodo.org/api/files/10c9d73a-f52b-4923-a793-2fe3326d5587/config.yaml?versionId=7e47dc9f-7a47-4fbd-9774-7dfa1a46abc1">config.yaml</a>: a file that contains the parameters used when running the pipeline. </li> </ul> <p> </p>
ShareScore
12/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 0
- Reuse readiness
- 0
- Engagement
- 0