Magnifier is a snakemake pipeline that help magnifies what's in your sample, check GC bias, coverage, etc. More ways of investigating your samples will be included as we go.
Update config files for different with you samples names and other parameters.
You will get a plot of percentages of primary and secondary alignments. In addition to percentage of unmapped reads and quality of mapped reads for each sample.
A density plot of the mapping quality of your reads.
Investigates GCbias in your samples. It output several metrics (txt files) and wraps them up in a figure, as follows:
Outputs overall coverage plot:
Outputs a histogram of coverage of your sample, a sample output example is:
Outputs several metrics for insert size, and a wrapped up figure as follows:
Outputs a nice plot as below to check contamination:
The pipeline will also generate more text files with more detailed stats:
sample1.s_1.alignment_metrics.txt
sample1.s_1.gc_bias_metrics.txt
sample1.s_1.insert_size_metrics.txt
Use:
snakemake -jn
to run the pipeline where n is the number of cores for example for 10 cores use. Snakemake has to be installed.
For less froodiness, use conda:
snakemake -jn --use-conda
For example, for 10 cores use:
snakemake -j10 --use-conda
This will pull automatically the same versiosn of tools we used. Conda has to be installed in the system, in addition to snakemake. Conda as well has to be installed.
For a dry run use:
snakemake -j1 -n
and to print command in dry run use:
snakemake -j1 -n -p