bioplotz 0.1.0.dev19

A python package for drawing some bioinformatic pictures.

bioplotz: A package for plotting images for bioinformatics

Dependencies

Python modules:

• numpy
• matplotlib
• pandas

Installation

Install via pip

pip install bioplotz

Install from source code

pip install git+https://github.com/sc-zhang/bioplotz.git --user

Usage

Manhattan Plot

import bioplotz as bp

fig, ax = bp.manhattan(data, threshold=0, color=['orange', 'green'], threshold_line_color='blue', log_base=0,
                       reverse=False, xtick_labels=True, ytick_labels=True, ax=None, marker='.', s=1, **kwargs)

parameter	value type	explain
data	dict list	dict key: block name     value: [[x1,x2,...,xn], [y1,y2,...,yn]] list is a list like: [[x1,y1], [x2, y2], ..., [xn, yn]]
threshold	value list	value if only one threshold line to plot, list if more than one threshold line need to plot, a list can be used for different lines, like: [threshold_value1, threshol_value2]
color	list	color is a list used for blocks, if the count of block greater than color count, it will be used circularly
threshold_line_color	value list	value if threshold is a single value list if threshold is a list
threshold_line_width	value	value the line width of threshold lines
block_line_width	value	value if there are only one color, the block line will display as border, the width is set by this parameter
log_base	value	log_base = 0 means not calucate value with log log_base != 0 means log base for log values with it
reverse	Boolean	if all data lower than 0, you may use it to show opposite values
other parameters	value	same with parameters used in pyplot.scatter

Chromosome Plot

import matplotlib.pyplot as plt
import bioplotz as bp

fig, ax, mapper = bp.chromosome(chr_len_db, chr_order, inner_data=bed_data, centro_db=centro_pos,
                                inner_value_type="numeric", orientation="vertical", **kwargs)
plt.colorbar(mapper, ax=ax, shrink=0.5)

# for drawing telomeres, we need a dict of telomeres
# the telomere dict is like below:
# chr_telo_db = {"Chr1": "start", "Chr2": "end", "Chr3": "both"}
# then add codes below
left_telo_list = []
right_telo_list = []
for _ in range(len(chr_order)):
    chrn = chr_order[_]
    if not chrn in chr_telo_db:
        continue
    if chr_telo_db[chrn] == "start":
        left_telo_list.append(_)
    elif chr_telo_db[chrn] == "end":
        right_telo_list.append(_)
    elif chr_telo_db[chrn] == "both":
        left_telo_list.append(_)
        right_telo_list.append(_)

# the value of color and s should be adjusted by user manually
plt.scatter([_ for _ in left_telo_list], [0 for _ in left_telo_list], color="blue", s=50)
plt.scatter([_ for _ in right_telo_list], [chr_len_db[chr_order[_]] for _ in right_telo_list], color="blue", s=50)

parameter	value type	Optional	Default	explain
chr_len_db	dict	No	-	key: chromosome name value: chromosome length
chr_order	list	Yes	None	list: the custom chromosome order, like: ["Chr1", "Chr3", "Chr2"] must same with keys in chr_len
inner_data	list	Yes	None	list: two dimension list, like: [[chrome name, start pos, end pos, value/color]]
outer_data	list	Yes	None	same with inner_data
centro_pos	dict	Yes	None	key: chromosome name value: middle position of centromere
inner_value_type	str	Yes	numeric	numeric: the 4th column of bed_data should be value color: the 4th column of bed_data is color marker: different with other two types, it need 5 columns, the 4th column of bed_data is marker, the 5th column is color (marker is same with the parameter which be used in pyplot.scatter)
outer_value_type	str	Yes	numeric	similar with inner_value_type, but only support numeric and marker
orientation	str	Yes	vertical	"vertical" or "horizontal"
inner_vmin	float	Yes	nan	only affect when inner_value_type is numeric, if not set, the minimum value of inner_data would be use, otherwise, the value lower than vmin would be increased to vmin
inner_vmax	float	Yes	nan	only affect when inner_value_type is numeric, if not set, the maximum value of inner_data would be use, otherwise, the value greater than vmax would be decreased to vmax
outer_vmin	float	Yes	nan	only affect when outer_value_type is numeric, if not set, the minimum value of outer_data would be use, otherwise, the value lower than vmin would be increased to vmin
outer_vmax	float	Yes	nan	only affect when outer_value_type is numeric, if not set, the maximum value of outer_data would be use, otherwise, the value greater than vmax would be decreased to vmax
cmap	str	Yes	gist_rainbow	cmap for colorbar
cmap_parts	int	Yes	100	how many parts for splitting cmap
inner_size	float or array-like, shape(n,)	Yes	None	size of marker size if inner_value_type is marker
outer_size	float or array-like, shape(n, )	Yes	None	same with inner_size
outer_line_color		Yes	None	color of line if outer_value_type is numeric
outer_line_style		Yes	None	style of line if outer_value_type is numeric
fig_ratio	float	Yes	None	if plot with subplots, use this parameter to keep the arcs of chromosomes correct, for "vertical", this parameter should be fig_width/fig_height, otherwise, fig_height/fig_width
other parameters	value	Yes	None	same with parameters used in pyplot.plot

• If value_type is numeric, the return value mapper will be a mappable which could be used with plt.colorbar, else None

Gene Cluster Plot

import bioplotz as bp

fig, ax = bp.genecluster(gene_list)

parameter	value type	Optional	Default	explain
gene_list	list	No	-	list: 2-dimension list, like [[gene name, start pos, end pos, direct(+/-), color], ..., [gene name, start pos, end pos, direct(+/-), color]]
edgecolor	list str	Yes	None	list: same length with gene_list, like: ["green", "blue", ..., "red"] str: common edge color for all genes
edgewidth	int	Yes	1	edge width for all genes
lw	int	Yes	3	line width to show the genome backbone

Notice, the best figsize should be (gene count, 1), for example: plt.figure(figsize=(16, 1)), and the bbox_inches parameter which in savefig should be 'tight'.

Multi Alignment Plot

import bioplotz as bp

fig, ax = bp.multialign(data)

parameter	value type	Optional	Default	explain
data	dict	No	-	key: gene name value: alignment sequence
base_per_line	int	Yes	80	base count to display for each line
color_mode	string	Yes	match	should be one of "match" and "base"
color_kws	dict	Yes	-	based on color_mode, details could be found below
**kwargs	any	Yes	-	same with which use in ax.text

Details of color_kws
if color_mod is "match", the struct and default values of color_kws is like below:

# the default color of background colors is "white", 
# if there are not be set or set to None, 
# the default color of text colors is "black",
# if there are not be set or set to None
# user can overwrite any of them by set color_kws like:
# color_kws = {"match_color": "black", "match_background_color": "grey"} 
color_kws = {
    "match_color": 'blue',
    "match_background_color": None,
    "mismatch_color": 'red',
    "mismatch_background_color": None,
    "highlight_positions": None,
    "highlight_color": 'green',
    "highlight_background_color": None
}

if color_mod is "base", the struct and default values of color_kws is like below:

# the default color of text is "black" and default color of background is set below
# user can overwrite color of any charactor or add color for new charactor like *, -, ?
# by set color_kws like:
# color_kws = {"base_color": {"-": "white}, "base_background_color": {"-", "yellow"}}

color_kws = {
    "base_color": {},
    "base_background_color": {
        "A": "salmon", "a": "salmon",
        "T": "lightgreen", "t": "lightgreen",
        "G": "orange", "g": "orange",
        "C": "steelblue", "c": "steelblue",
        "U": "tomato", "u": "tomato",
        "F": "khaki", "f": "khaki",
        "D": "cadetblue", "d": "cadetblue",
        "N": "coral", "n": "coral",
        "E": "yellowgreen", "e": "yellowgreen",
        "Q": "plum", "q": "plum",
        "H": "orchid", "h": "orchid",
        "L": "darkseagreen", "l": "darkseagreen",
        "I": "yellow", "i": "yellow",
        "K": "lightseagreen", "k": "lightseagreen",
        "O": "darkkhaki", "o": "darkkhaki",
        "M": "palevioletred", "m": "palevioletred",
        "P": "sandybrown", "p": "sandybrown",
        "R": "palegreen", "r": "palegreen",
        "S": "peru", "s": "peru",
        "V": "violet", "v": "violet",
        "W": "mediumturquoise", "w": "mediumturquoise",
        "Y": "deepskyblue", "y": "deepskyblue"
    }
}

colors for base:

Notice, the figsize should be (base_per_line/10, x) where x=align_length/base_per_line*gene_count/5, and the font must be monospaced, like "Courier New", that sometimes user need add codes as following.

import matplotlib as mpl
import bioplotz as bp

basefont = mpl.font_manager.FontProperties(fname="/path/to/font.ttf")
fig, ax = bp.multialign(data, fontproperties=basefont)

or

plt.rcParams['font.sans-serif'] = 'Courier New'