sav

README.md

@@ -1,7 +1,10 @@
 bam-lorenz-coverage
 ===================
 
-Generate Lorenz plots and Coverage plots directly from BAM files
+This is a free software package that very easily allows you to generate
+Lorenz plots and Coverage plots, directly from a BAM file. It can also
+output the tables as text documents so you can generate custom plots.
+There is also support to only analyse specific regions.
 
 Implemented in:
  * Python3 + Matplotlib + Pysam
@@ -19,6 +22,12 @@ $ python setup.py install
 $ bam-lorenz-coverage --help
 ```
 
+Possible issues:
+ - pysam is currently incompatible with python 3.7 - manual installation of pysam is still possible (git clone + python setup.py install)
+ - matplotlib depends on Tk but does not throw an error if it is missing during installation, only at runtime
+   * debian/ubuntu: sudo apt-get install python3-tk
+   * arch: pacman -Sy tk
+
 Usage:
 
 ```
@@ -27,13 +36,15 @@ Usage: bam-lorenz-coverage [OPTIONS] INPUT_ALIGNMENT_FILE
 Options:
   --version                  Show the version and exit.
   -l, --lorenz-table TEXT    Output table Lorenz-curve (for stdout use: -)
-  -x, --roc                  Output Lorenz-curve ROC to $lorenz_table.roc.txt
-                             [ requires --lorenz-table to be set to file ]
   -c, --coverage-table TEXT  Output table Coverage-graph (for stdout use: -)
   -L, --lorenz-svg TEXT      Output figure Lorenz-curve (SVG).
   -C, --coverage-svg TEXT    Output figure Coverage-graph (SVG).
+  -s, --stats TEXT           Output additional stats to text-file
+  -r, --region TEXT          Scan depth only in selected region <chr:from-to>
+                             (all positions: 1-based)
+  -b, --bed-regions TEXT     Scan depth only in selected positions or regions
+                             (BED file: start: 0-based & end: 1-based)
   --help                     Show this message and exit.
-
 ```
 
 The lowercase arguments (-l, -c) allow extraction of the raw data tables for custom plotting. The uppercase arguments (-L, -C) directly generate a plot. The implemented plot only contains one sample per plot. For multi-sample plots, use the column tables and your imagination.