[](https://travis-ci.org/conchoecia/pauvre) [](https://zenodo.org/badge/latestdoi/112774670)
## pauvre: a plotting package designed for nanopore and PacBio long reads
This package currently hosts four scripts for plotting and/or printing stats.
- `pauvre marginplot`
- takes a fastq file as input and outputs a marginal histogram with a heatmap.
- `pauvre stats`
- Takes a fastq file as input and prints out a table of stats, including how many basepairs/reads there are for a length/mean quality cutoff.
- This is also automagically called when using `pauvre marginplot`
- `pauvre redwood`
- I am happy to introduce the redwood plot to the world as a method
of representing circular genomes. A redwood plot contains long
reads as "rings" on the inside, a gene annotation
"cambrium/phloem", and a RNAseq "bark". The input is `.bam` files
for the long reads and RNAseq data, and a `.gff` file for the
annotation. More details to follow as we document this program
better...
- `pauvre synteny`
- Makes a synteny plot of circular genomes. Finds the most
parsimonius rotation to display the synteny of all the input
genomes with the fewest crossings-over. Input is one `.gff` file
per circular genome and one directory of gene alignments.
## Updates:
- 20200215 - v0.1.924 - Made some minor updates to work with python 3.7 and the latest version of pandas,
- 20171130 - v0.1.86 - some changes by @wdecoster to integrate `pauvre` into [nanoplot](https://github.com/wdecoster/NanoPlot),
as well as some formatting changes that *may* make `pauvre` work better with python2.7. Adding Travis-CI functionality.
- 20171025 - v0.1.83 - added some changes to make marginplot interface
with @wdecoster's [nanoPlot](https://github.com/wdecoster/NanoPlot)
package, and made `pauvre stats` only output data tables for
filtered reads. `pauvre stats` also now has the `--filt_maxlen`,
`--filt_maxqual`, `--filt_minlen`, and `--filt_minqual` options.
- 20171018 - v0.1.8 - you can now filter reads and adjust the plotting viewing window.
[See below for a demonstration.](#filter-reads-and-adjust-viewing-window) I added the following options:
```
--filt_maxlen FILT_MAXLEN
This sets the max read length filter reads.
--filt_maxqual FILT_MAXQUAL
This sets the max mean read quality to filter reads.
--filt_minlen FILT_MINLEN
This sets the min read length to filter reads.
--filt_minqual FILT_MINQUAL
This sets the min mean read quality to filter reads.
--plot_maxlen PLOT_MAXLEN
Sets the maximum viewing area in the length dimension.
--plot_maxqual PLOT_MAXQUAL
Sets the maximum viewing area in the quality
dimension.
--plot_minlen PLOT_MINLEN
Sets the minimum viewing area in the length dimension.
--plot_minqual PLOT_MINQUAL
Sets the minimum viewing area in the quality
dimension.
```
- 20171014 - uploading information on `pauvre redwood` and `pauvre synteny` usage.
- 20171012 - made `pauvre stats` more consistently produce useful histograms.
`pauvre stats` now also calculates some statistics for different size ranges.
- 20170529 - added automatic scaling to the input fastq file. It
scales to show the highest read quality and the top 99th percentile
of reads by length.
# Requirements
- You must have the following installed on your system to install this software:
- python 3.x
- matplotlib
- biopython
- pandas
- pillow
# Installation
- Instructions to install on your mac or linux system. Not sure on
Windows! Make sure *python 3* is the active environment before
installing.
- `git clone https://github.com/conchoecia/pauvre.git`
- `cd ./pauvre`
- `pip3 install .`
- Or, install with pip
- `pip3 install pauvre`
# Usage
## `stats`
- generate basic statistics about the fastq file. For example, if I
want to know the number of bases and reads with AT LEAST a PHRED
score of 5 and AT LEAST a read length of 500, run the program as below
and look at the cells highlighted with `<braces>`.
- `pauvre stats --fastq miniDSMN15.fastq`
```
numReads: 1000
numBasepairs: 1029114
meanLen: 1029.114
medianLen: 875.5
minLen: 11
maxLen: 5337
N50: 1278
L50: 296
Basepairs >= bin by mean PHRED and length
minLen Q0 Q5 Q10 Q15 Q17.5 Q20 Q21.5 Q25 Q25.5 Q30
0 1029114 1010681 935366 429279 143948 25139 3668 2938 2000 0
500 984212 <968653> 904787 421307 142003 24417 3668 2938 2000 0
1000 659842 649319 616788 300948 103122 17251 2000 2000 2000 0
et cetera...
Number of reads >= bin by mean Phred+Len
minLen Q0 Q5 Q10 Q15 Q17.5 Q20 Q21.5 Q25 Q25.5 Q30
0 1000 969 865 366 118 22 3 2 1 0
500 873 <859> 789 347 113 20 3 2 1 0
1000 424 418 396 187 62 11 1 1 1 0
et cetera...
```
## `marginplot`
### Basic usage
- automatically calls `pauvre stats` for each fastq file
- Make the default plot showing the 99th percentile of longest reads
- `pauvre marginplot --fastq miniDSMN15.fastq`
- 
- Make a marginal histogram for ONT 2D or 1D^2 cDNA data with a
lower maxlen and higher maxqual.
- `pauvre marginplot --maxlen 4000 --maxqual 25 --lengthbin 50 --fileform pdf png --qualbin 0.5 --fastq miniDSMN15.fastq`
- 
### Filter reads and adjust viewing window
- Filter out reads with a mean quality less than 5, and a length
less than 800. Zoom in to plot only mean quality of at least 4 and
read length at least 500bp.
- `pauvre marginplot -f miniDSMN15.fastq --filt_minqual 5 --filt_minlen 800 -y --plot_minlen 500 --plot_minqual 4`
- 
### Specialized Options
- Plot ONT 1D data with a large tail
- `pauvre marginplot --maxlen 100000 --maxqual 15 --lengthbin 500 <myfile>.fastq`
- Get more resolution on lengths
- `pauvre marginplot --maxlen 100000 --lengthbin 5 <myfile>.fastq`
### Transparency
- Turn off transparency if you just want a white background
- `pauvre marginplot --transparent False <myfile>.fastq`
- Note: transparency is the default behavior
- 
# Contributors
@conchoecia (Darrin Schultz)
@mebbert (Mark Ebbert)
@wdecoster (Wouter De Coster)