2.2.2: Docs

docs/output.md

@@ -28,7 +28,7 @@ as the distribution of total number of reads per cell, duplication rate, or excl
 
 Afterwards, every pages show the overview of binning count result of each of the single-cells as presented below. The depth of Crick reads are depicted in the green color in the right side, and the depth of Watson reads are depicted in the orange color in the left side of each chromosome lines. HMM automatically defines the WW/WC/CC status according the reads distribution (yellow background: WC, green background: CC, orange background: WW).
 
-|   ![summary](images/plots/414.png)   |
+| ![summary](images/plots/correct.png) |
 | :----------------------------------: |
 | _Strand-seq karyotype visualisation_ |
 
@@ -128,6 +128,32 @@ By using these heatmaps, the user can easily identify subclones based on the SV
 | :----------------------------------------: |
 |        _2. SV clustering (SV type)_        |
 
+### Genome browsing
+
+File path: `<OUTPUT_FOLDER>/<SAMPLE>/plots/UCSC|IGV`
+
+You can now also generates UCSC and IGV genome-browsing ready-to-be-used files when `genome_browsing_files_generation=True`. Here is an example below:
+
+|                 ![summary](images/plots/genome_browsing.png)                 |
+| :--------------------------------------------------------------------------: |
+| _(A) UCSC and (B) IGV Genome browsing using files generated by MosaiCatcher_ |
+
+#### UCSC genome browser
+
+To visualise your data on the UCSC genome browser, go to the [website](https://genome.ucsc.edu/cgi-bin/hgTracks), section `My Data/Custom Tracks`, and upload the .gz file generated by MosaiCatcher located in `<OUTPUT_FOLDER>/<SAMPLE>/plots/UCSC/<SAMPLE>.bedUCSC.gz`. Then click on the `submit` button, wait until the loading complete. You should see the list of tracks loaded.
+
+#### IGV
+
+MosaiCatcher generates an XML session ready to use by IGV. Thus, files in this XML session are referenced using relative path. It's thus important to either mount the disk where is present the data on your computer, or to copy the complete `<OUTPUT_FOLDER>/<SAMPLE>/plots/IGV/` on your computer. Once this is done, open the software, click on `File/Open Session` and load the XML file present in the IGV folder. Please note that the SV calls coloring appears only once you are displaying the data at the chromosome level, not at the genome level.
+
+### scTRIP multiplot (Marco Cosenza)
+
+From 2.2.2, it's now possible to use [scTRIP multiplot](/docs/usage.md/#sctrip-multiplot) inside MosaiCatcher. By enabling the option available in the configuration (`scTRIP_multiplot=True`), you will obtain for each chromosome of each cell able to be processed, a plot similar to below:
+
+|              ![summary](images/plots/scTRIP_multiplot.png)              |
+| :---------------------------------------------------------------------: |
+| _scTRIP multiplot (Watson/Crick, depth, haplotype phased and SV calls)_ |
+
 ## Statistics
 
 ---

docs/usage.md

@@ -14,6 +14,15 @@ From 2.2.0, you don't need to clone both [ashleys-qc-pipeline preprocessing modu
 
 1. A. Create a dedicated conda environment
 
+---
+
+**ℹ️ Note**
+
+- Please be careful of your conda/mamba setup, if you applied specific constraints/modifications to your system, this could lead to some versions discrepancies.
+- mamba is usually preferred but might not be installed by default on a shared cluster environment
+
+---
+
 ```bash
 conda create -n snakemake -c bioconda -c conda-forge -c defaults -c anaconda snakemake
 ```
@@ -24,7 +33,7 @@ conda create -n snakemake -c bioconda -c conda-forge -c defaults -c anaconda sna
 conda activate snakemake
 ```
 
-**Reminder:** You will need to verify that this conda environment is activated and provide the right snakemake before each execution (`which snakemake` command should output like <FOLDER>/<USER>/[ana|mini]conda3/envs/snakemake/bin/snakemake)
+**Reminder:** You will need to verify that this conda environment is activated and provide the right snakemake before each execution (`which snakemake` command should output like \<FOLDER>/\<USER>/[ana|mini]conda3/envs/snakemake/bin/snakemake)
 
 2. Clone the repository
 
@@ -81,8 +90,7 @@ snakemake \
 
 **ℹ️ Note for 🇪🇺 EMBL users**
 
-- You can load already installed snakemake modules on the HPC (by connecting to login01 & login02) using the following `module load snakemake/7.14.0-foss-2022a`
-- Use the following command for singularity-args parameter: `--singularity-args "-B /g:/g -B /scratch:/scratch"`
+- Use the following profile to run on EMBL cluster: `--profile workflow/snakemake_profiles/HPC/slurm_EMBL`
 
 ---
 
@@ -132,7 +140,7 @@ If possible, it is also highly recommended to install and use `mamba` package ma
 
 ```bash
 conda install -c conda-forge mamba
-mamba create -n snakemake -c bioconda -c conda-forge -c defaults -c anaconda snakemake=7.14.0
+mamba create -n snakemake -c bioconda -c conda-forge -c defaults -c anaconda snakemake
 conda activate mosaicatcher_env
 ```
 
@@ -227,19 +235,15 @@ Parent_folder
     `-- selected
         |-- Cell_03.sort.mdup.bam
         `-- Cell_04.sort.mdup.bam
-
-
-
-
 ```
 
-> Using the `old behavior`, cells flagged as low-quality will be determined both based on their presence in the `selected` folder presented above and on coverage [see Note here](#note:-filtering-of-low-quality-cells-impossible-to-process).
+> Using the `input_bam_legacy` parameter, cells flagged as low-quality will be determined both based on their presence in the `selected` folder presented above and on coverage [see Note here](#note:-filtering-of-low-quality-cells-impossible-to-process).
 
 ---
 
 **⚠️ Warning**
 
-Using the `old behavior`, only **intersection** between cells present in the selected folder and with enough coverage will be kept. Example: if a library is present in the selected folder but present a low coverage [see Note here](#note:-filtering-of-low-quality-cells-impossible-to-process), this will not be processed.
+Using the `input_bam_legacy` parameter, only **intersection** between cells present in the selected folder and with enough coverage will be kept. Example: if a library is present in the selected folder but present a low coverage [see Note here](#note:-filtering-of-low-quality-cells-impossible-to-process), this will not be processed.
 
 ---
 
@@ -316,7 +320,7 @@ snakemake \
 **ℹ️ Note**
 
 It is possible to provide multiple mouting points between system and cointainer using as many `-B` as needed in the `singularity-args` command like the following: "-B /<mouting_point1>:/<mounting_point1> -B /<mouting_point2>:/<mounting_point2>"
-For EMBL users, this can be for example "-B /g:/g -B /scratch:/scratch"
+For EMBL users, you don't need to specify this as this is already part of the execution profile (workflow/snakemake_profiles/HPC/slurm_EMBL)
 
 ---
 

workflow/rules/debug.smk

@@ -6,12 +6,12 @@ rule fastqc_debug:
         labels_strandscape="{folder}/{sample}/cell_selection/labels_strandscape.tsv",
     output:
         html=report(
-            "{folder}/{sample}/debug/mosaicatcher_fastqc/{cell}_{pair}_fastqc.html",
+            "{folder}/{sample}/debug/mosaicatcher_fastqc/{cell}.{pair}_fastqc.html",
             category="FastQC",
             subcategory="{sample}",
             labels={"Sample": "{sample}", "Cell": "{cell}", "Pair": "{pair}"},
         ),
-        zip="{folder}/{sample}/debug/mosaicatcher_fastqc/{cell}_{pair}_fastqc.zip",
+        zip="{folder}/{sample}/debug/mosaicatcher_fastqc/{cell}.{pair}_fastqc.zip",
     log:
         "{folder}/log/fastqc_debug/{sample}/{cell}_{pair}.log",
     threads: 1
@@ -22,4 +22,4 @@ rule fastqc_debug:
     params:
         outdir = lambda wc, output: "/".join(output.zip.split("/")[:-1])
     shell:
-        "fastqc --outdir {params.outdir} --quiet {input.fastq}"
+        "fastqc --outdir {params.outdir} --quiet {input.fastq} "