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@@ -17,7 +17,7 @@ This is is the **RNA-seq** pipeline from the `Sequana <https://sequana.readthedo
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:Overview: RNASeq analysis from raw data to feature counts
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:Input: A set of Fastq Files and genome reference and annotation.
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:Output: MultiQC and HTML reports, BAM and bigwig files, feature Counts, script to launch differential analysis
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:Status: Production.
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:Status: Production.
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:Citation(sequana): Cokelaer et al, (2017), ‘Sequana’: a Set of Snakemake NGS pipelines, Journal of Open Source Software, 2(16), 352, JOSS DOI doi:10.21105/joss.00352
@@ -80,7 +80,7 @@ Or use the conda.yaml file available in this repository. If you start a new
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environment from scratch, those commands will create the environment and install
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all dependencies for you::
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conda create --name sequana_env python 3.7.3
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conda create --name sequana_env python 3.7.3
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conda activate sequana_env
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conda install -c anaconda qt pyqt>5
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pip install sequana
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Details
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~~~~~~~~~
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This pipeline runs a **RNA-seq** analysis of sequencing data. It runs in
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parallel on a set of input FastQ files (paired or not).
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This pipeline runs a **RNA-seq** analysis of sequencing data. It runs in
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parallel on a set of input FastQ files (paired or not).
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A brief HTML report is produced together with a MultiQC report.
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This pipeline is complex and requires some expertise for the interpretation.
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Many online-resources are available and should help you deciphering the output.
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Many online-resources are available and should help you deciphering the output.
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Yet, it should be quite straigtforward to execute it as shown above. The
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pipeline uses bowtie1 to look for ribosomal contamination (rRNA). Then,
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pipeline uses bowtie1 to look for ribosomal contamination (rRNA). Then,
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it cleans the data with cutapdat if you say so (your data may already be
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pre-processed). If no adapters are provided (default), reads are
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trimmed for low quality bases only. Then, mapping is performed with standard mappers such as
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pre-processed). If no adapters are provided (default), reads are
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trimmed for low quality bases only. Then, mapping is performed with standard mappers such as
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star or bowtie2 (--aligner option). Finally,
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feature counts are extracted from the previously generated BAM files. We guess
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the strand and save the feature counts into the directoy
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./rnadiff/feature_counts.
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./rnadiff/feature_counts.
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The pipelines stops there. However, RNA-seq analysis are followed by a different
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analysis (DGE hereafter). Although the DGE is not part of the pipeline, you can
@@ -138,7 +138,7 @@ Rules and configuration details
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Here is the `latest documented configuration file <https://raw.githubusercontent.com/sequana/sequana_rnaseq/main/sequana_pipelines/rnaseq/config.yaml>`_
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to be used with the pipeline. Each rule used in the pipeline may have a section in the configuration file.
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to be used with the pipeline. Each rule used in the pipeline may have a section in the configuration file.
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.. warning:: the RNAseQC rule is switch off and is not currently functional in
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