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Bioinformatics data analysis and visualization toolkit

Project description

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The bioinfokit toolkit aimed to provide various easy-to-use functionalities to analyze,
visualize, and interpret the biological data generated from genome-scale omics experiments.

How to install:

bioinfokit requires

  • Python 3
  • NumPy
  • scikit-learn
  • seaborn
  • pandas
  • matplotlib
  • SciPy
  • matplotlib_venn
git clone https://github.com/reneshbedre/bioinfokit.git
cd bioinfokit
python setup.py install

Volcano plot

latest update v0.8.8

bioinfokit.visuz.gene_exp.volcano(table, lfc, pv, lfc_thr, pv_thr, color, valpha, geneid, genenames, gfont, gstyle, sign_line, dotsize, markerdot, r, dim, show, figtype, axxlabel, axylabel, axlabelfontsize, axlabelfontname, axtickfontsize, axtickfontname, xlm, ylm, plotlegend, legendpos, legendanchor, figname, legendlabels)

Parameters Description
table Pandas dataframe table having atleast gene IDs, log fold change, P-values or adjusted P-values columns
lfc Name of a column having log or absolute fold change values [string][default:logFC]
pv Name of a column having P-values or adjusted P-values [string][default:p_values]
lfc_thr Log or absolute fold change cutoff for up and downregulated genes [float][default:1.0]
pv_thr P-values or adjusted P-values cutoff for up and downregulated genes [float][default:0.05]
color Tuple of three colors [tuple or list][default: color=("green", "grey", "red")]
valpha Transparency of points on volcano plot [float (between 0 and 1)][default: 1.0]
geneid Name of a column having gene Ids. This is necessary for plotting gene label on the points [string][default: None]
genenames Tuple of gene Ids to label the points. The gene Ids must be present in the geneid column. If this option set to "deg" it will label all genes defined by lfc_thr and pv_thr [string, tuple, dict][default: None]
gfont Font size for genenames [float][default: 10.0]. gfont not compatible with gstyle=2.
gstyle Style of the text for genenames. 1 for default text and 2 for box text [int][default: 1]
sign_line Show grid lines on plot with defined log fold change (lfc_thr) and P-value (pv_thr) threshold value [True or False][default:False]
dotsize The size of the dots in the plot [float][default: 8]
markerdot Shape of the dot marker. See more options at https://matplotlib.org/3.1.1/api/markers_api.html [string][default: "o"]
dim Figure size [tuple of two floats (width, height) in inches][default: (5, 5)]
r Figure resolution in dpi [int][default: 300]. Not compatible with show= True
figtype Format of figure to save. Supported format are eps, pdf, pgf, png, ps, raw, rgba, svg, svgz [string][default:'png']
show Show the figure on console instead of saving in current folder [True or False][default:False]
axxlabel Label for X-axis. If you provide this option, default label will be replaced [string][default: None]
axylabel Label for Y-axis. If you provide this option, default label will be replaced [string][default: None]
axlabelfontsize Font size for axis labels [float][default: 9]
axlabelfontname Font name for axis labels [string][default: 'Arial']
axtickfontsize Font size for axis ticks [float][default: 9]
axtickfontname Font name for axis ticks [string][default: 'Arial']
xlm Range of ticks to plot on X-axis [float (left, right, interval)][default: None]
ylm Range of ticks to plot on Y-axis [float (bottom, top, interval)][default: None]
plotlegend plot legend on volcano plot [True or False][default:False]
legendpos position of the legend on plot. For more options see loc parameter at https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.legend.html [string ][default:"best"]
legendanchor position of the legend outside of the plot. For more options see bbox_to_anchor parameter at https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.legend.html [list][default:None]
figname name of figure [string ][default:"ma"]
legendlabels legend label names. If you provide custom label names keep the same order of label names as default [list][default:['significant up', 'not significant', 'significant down']]

Returns:

Volcano plot image in same directory (volcano.png) Working example

MA plot

latest update v0.8.8

bioinfokit.visuz.gene_exp.ma(table, lfc, ct_count, st_count, lfc_thr, color, dim, dotsize, show, r, valpha, figtype, axxlabel, axylabel, axlabelfontsize, axtickfontsize, axtickfontname, xlm, ylm, fclines, fclinescolor, legendpos, legendanchor, figname, legendlabels, plotlegend)

Parameters Description
table Pandas dataframe table having atleast gene IDs, log fold change, and normalized counts (control and treatment) columns
lfc Name of a column having log fold change values [default:logFC]
ct_count Name of a column having count values for control sample [default:value1]
st_count Name of a column having count values for treatment sample [default:value2]
lfc_thr Log fold change cutoff for up and downregulated genes [default:1]
color Tuple of three colors [tuple or list][default: ("green", "grey", "red")]
dotsize The size of the dots in the plot [float][default: 8]
markerdot Shape of the dot marker. See more options at https://matplotlib.org/3.1.1/api/markers_api.html [string][default: "o"]
valpha Transparency of points on plot [float (between 0 and 1)][default: 1.0]
dim Figure size [tuple of two floats (width, height) in inches][default: (5, 5)]
r Figure resolution in dpi [int][default: 300]. Not compatible with show= True
figtype Format of figure to save. Supported format are eps, pdf, pgf, png, ps, raw, rgba, svg, svgz [string][default:'png']
show Show the figure on console instead of saving in current folder [True or False][default:False]
axxlabel Label for X-axis. If you provide this option, default label will be replaced [string][default: None]
axylabel Label for Y-axis. If you provide this option, default label will be replaced [string][default: None]
axlabelfontsize Font size for axis labels [float][default: 9]
axtickfontsize Font size for axis ticks [float][default: 9]
axtickfontname Font name for axis ticks [string][default: 'Arial']
xlm Range of ticks to plot on X-axis [float (left, right, interval)][default: None]
ylm Range of ticks to plot on Y-axis [float (bottom, top, interval)][default: None]
fclines draw log fold change threshold lines as defines by lfc [True or False][default:False]
fclinescolor color of fclines [string][default: '#2660a4']
plotlegend plot legend on MA plot [True or False][default:False]
legendpos position of the legend on plot. For more options see loc parameter at https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.legend.html [string ][default:"best"]
legendanchor position of the legend outside of the plot. For more options see bbox_to_anchor parameter at https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.legend.html [list][default:None]
figname name of figure [string ][default:"ma"]
legendlabels legend label names. If you provide custom label names keep the same order of label names as default [list][default:['significant up', 'not significant', 'significant down']]

Returns:

MA plot image in same directory (ma.png) Working example

Inverted Volcano plot

latest update v0.8.8

bioinfokit.visuz.gene_exp.involcano(table, lfc, pv, lfc_thr, pv_thr, color, valpha, geneid, genenames, gfont, gstyle, dotsize, markerdot, r, dim, show, r, dim, show, figtype, axxlabel, axylabel, axlabelfontsize, axtickfontsize, axtickfontname, plotlegend, legendpos, legendanchor, figname, legendlabels)

Parameters Description
table Pandas dataframe table having atleast gene IDs, log fold change, P-values or adjusted P-values
lfc Name of a column having log fold change values [default:logFC]
pv Name of a column having P-values or adjusted P-values [default:p_values]
lfc_thr Log fold change cutoff for up and downregulated genes [default:1]
pv_thr P-values or adjusted P-values cutoff for up and downregulated genes [default:0.05]
color Tuple of three colors [tuple or list][default: color=("green", "grey", "red")]
valpha Transparency of points on volcano plot [float (between 0 and 1)][default: 1.0]
geneid Name of a column having gene Ids. This is necessary for plotting gene label on the points [string][default: None]
genenames Tuple of gene Ids to label the points. The gene Ids must be present in the geneid column. If this option set to "deg" it will label all genes defined by lfc_thr and pv_thr [string, tuple, dict][default: None]
gfont Font size for genenames [float][default: 10.0]
gstyle Style of the text for genenames. 1 for default text and 2 for box text [int][default: 1]
dotsize The size of the dots in the plot [float][default: 8]
markerdot Shape of the dot marker. See more options at https://matplotlib.org/3.1.1/api/markers_api.html [string][default: "o"]
dim Figure size [tuple of two floats (width, height) in inches][default: (5, 5)]
r Figure resolution in dpi [int][default: 300]. Not compatible with show= True
figtype Format of figure to save. Supported format are eps, pdf, pgf, png, ps, raw, rgba, svg, svgz [string][default:'png']
show Show the figure on console instead of saving in current folder [True or False][default:False]
axxlabel Label for X-axis. If you provide this option, default label will be replaced [string][default: None]
axylabel Label for Y-axis. If you provide this option, default label will be replaced [string][default: None]
axlabelfontsize Font size for axis labels [float][default: 9]
axtickfontsize Font size for axis ticks [float][default: 9]
axtickfontname Font name for axis ticks [string][default: 'Arial']
plotlegend plot legend on inverted volcano plot [True or False][default:False]
legendpos position of the legend on plot. For more options see loc parameter at https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.legend.html [string ][default:"best"]
legendanchor position of the legend outside of the plot. For more options see bbox_to_anchor parameter at https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.legend.html [list][default:None]
figname name of figure [string ][default:"involcano"]
legendlabels legend label names. If you provide custom label names keep the same order of label names as default [list][default:['significant up', 'not significant', 'significant down']]

Returns:

Inverted volcano plot image in same directory (involcano.png)

Working example

Correlation matrix plot

bioinfokit.visuz.stat.corr_mat(table, corm, cmap, r, dim, show, figtype, axtickfontsize, axtickfontname)

Parameters Description
table Dataframe object with numerical variables (columns) to find correlation. Ideally, you should have three or more variables. Dataframe should not have identifier column.
corm Correlation method [pearson,kendall,spearman] [default:pearson]
cmap Color Palette for heatmap [string][default: 'seismic']. More colormaps are available at
     https://matplotlib.org/3.1.0/tutorials/colors/colormaps.html

r | Figure resolution in dpi [int][default: 300]. Not compatible with show= True dim | Figure size [tuple of two floats (width, height) in inches][default: (6, 5)]
show | Show the figure on console instead of saving in current folder [True or False][default:False] figtype | Format of figure to save. Supported format are eps, pdf, pgf, png, ps, raw, rgba, svg, svgz [string][default:'png'] axtickfontsize | Font size for axis ticks [float][default: 7] axtickfontname | Font name for axis ticks [string][default: 'Arial']

Returns:

Correlation matrix plot image in same directory (corr_mat.png)

Working example

Merge VCF files

bioinfokit.analys.marker.mergevcf(file)

Parameters Description
file Multiple vcf files separated by comma

Returns:

Merged VCF file (merge_vcf.vcf)

Working example

Split VCF file

bioinfokit.analys.marker.splitvcf(file)

Split single VCF file containing variants for all chromosomes into individual file containing variants for each chromosome

Parameters Description
file VCF file to split
id chromosome id column in VCF file [string][default='#CHROM']

Returns:

VCF files for each chromosome

Working example

Reverse complement of DNA sequence

bioinfokit.analys.rev_com(sequence)

Parameters Description
seq DNA sequence to perform reverse complement
file DNA sequence in a fasta file

Returns:

Reverse complement of original DNA sequence

Working example

Sequencing coverage

bioinfokit.analys.seqcov(file, gs)

Parameters Description
file FASTQ file
gs Genome size in Mbp

Returns:

Sequencing coverage of the given FASTQ file

Working example

Convert TAB to CSV file

bioinfokit.analys.tcsv(file)

Parameters Description
file TAB delimited text file

Returns:

CSV delimited file (out.csv)

Heatmap

latest update v0.8.4

bioinfokit.visuz.gene_exp.hmap(table, cmap='seismic', scale=True, dim=(6, 8), rowclus=True, colclus=True, zscore=None, xlabel=True, ylabel=True, tickfont=(12, 12), show, r, figtype, figname)

Parameters Description
file CSV delimited data file. It should not have NA or missing values
cmap Color Palette for heatmap [string][default: 'seismic']
scale Draw a color key with heatmap [boolean (True or False)][default: True]
dim heatmap figure size [tuple of two floats (width, height) in inches][default: (6, 8)]
rowclus Draw hierarchical clustering for rows [boolean (True or False)][default: True]
colclus Draw hierarchical clustering for columns [boolean (True or False)][default: True]
zscore Z-score standardization of row (0) or column (1). It works when clus is True. [None, 0, 1][default: None]
xlabel Plot X-label [boolean (True or False)][default: True]
ylabel Plot Y-label [boolean (True or False)][default: True]
tickfont Fontsize for X and Y-axis tick labels [tuple of two floats][default: (14, 14)]
show Show the figure on console instead of saving in current folder [True or False][default:False]
r Figure resolution in dpi [int][default: 300]. Not compatible with show= True
figtype Format of figure to save. Supported format are eps, pdf, pgf, png, ps, raw, rgba, svg, svgz [string][default:'png']
figname name of figure [string ][default:"heatmap"]

Returns:

heatmap plot (heatmap.png, heatmap_clus.png)

Working example

Venn Diagram

bioinfokit.visuz.venn(vennset, venncolor, vennalpha, vennlabel)

Parameters Description
vennset Venn dataset for 3 and 2-way venn. Data should be in the format of (100,010,110,001,101,011,111) for 3-way venn and 2-way venn (10, 01, 11) [default: (1,1,1,1,1,1,1)]
venncolor Color Palette for Venn [color code][default: ('#00909e', '#f67280', '#ff971d')]
vennalpha Transparency of Venn [float (0 to 1)][default: 0.5]
vennlabel Labels to Venn [string][default: ('A', 'B', 'C')]

Returns:

Venn plot (venn3.png, venn2.png)

Working example

Two sample and Welch's t-test

bioinfokit.analys.stat.ttsam(table, xfac, res, evar, alpha)

Parameters Description
table Pandas dataframe. It should be stacked table with independent (xfac) and dependent (res) variable columns.
xfac Independent group column name with two levels [string][default: None]
res Response variable column name [string][default: None]
evar t-test with equal variance [bool (True or False)][default: True]
alpha Confidence level [float][default: 0.05]

Returns:

summary output and group boxplot (ttsam_boxplot.png)

Working example

Chi-square test for independence

bioinfokit.analys.stat.chisq(table)

Parameters Description
table Pandas dataframe. It should be contingency table.

Returns:

summary output and variable mosaic plot (mosaic.png)

Working example

File format conversions

bioinfokit.analys.format

Function Parameters Description
bioinfokit.analys.format.fqtofa(file) FASTQ file Convert FASTQ file into FASTA format
bioinfokit.analys.format.hmmtocsv(file) HMM file Convert HMM text output (from HMMER tool) to CSV format
bioinfokit.analys.format.tabtocsv(file) TAB file Convert TAB file to CSV format
bioinfokit.analys.format.csvtotab(file) CSV file Convert CSV file to TAB format

Returns:

Output will be saved in same directory

Working example

One-way ANOVA

bioinfokit.stat.oanova(table, res, xfac, ph, phalpha)

Parameters Description
table Pandas dataframe in stacked table format
res Response variable (dependent variable) [string][default: None]
xfac Treatments or groups or factors (independent variable) [string][default: None]
ph perform pairwise comparisons with Tukey HSD test [bool (True or False)] [default: False]
phalpha significance level Tukey HSD test [float (0 to 1)][default: 0.05]

Returns:

ANOVA summary, multiple pairwise comparisons, and assumption tests statistics

Working example

Manhatten plot

bioinfokit.visuz.marker.mhat(df, chr, pv, color, dim, r, ar, gwas_sign_line, gwasp, dotsize, markeridcol, markernames, gfont, valpha, show, figtype, axxlabel, axylabel, axlabelfontsize, ylm, gstyle)

Parameters Description
df Pandas dataframe object with atleast SNP, chromosome, and P-values columns
chr Name of a column having chromosome numbers [string][default:None]
pv Name of a column having P-values. Must be numeric column [string][default:None]
color List the name of the colors to be plotted. It can accept two alternate colors or the number colors equal to chromosome number. If nothing (None) provided, it will randomly assign the color to each chromosome [list][default:None]
gwas_sign_line Plot statistical significant threshold line defined by option gwasp [bool (True or False)][default: False]
gwasp Statistical significant threshold to identify significant SNPs [float][default: 5E-08]
dotsize The size of the dots in the plot [float][default: 8]
markeridcol Name of a column having SNPs. This is necessary for plotting SNP names on the plot [string][default: None]
markernames The list of the SNPs to display on the plot. These SNP should be present in SNP column. Additionally, it also accepts the dict of SNPs and its associated gene name. If this option set to True, it will label all SNPs with P-value significant score defined by gwasp [string, list, tuple, dict][default: True]
gfont Font size for SNP names to display on the plot [float][default: 8]. gfont not compatible with gstyle=2.
valpha Transparency of points on plot [float (between 0 and 1)][default: 1.0]
dim Figure size [tuple of two floats (width, height) in inches][default: (6, 4)]
r Figure resolution in dpi [int][default: 300]
ar Rotation of X-axis labels [float][default: 90]
figtype Format of figure to save. Supported format are eps, pdf, pgf, png, ps, raw, rgba, svg, svgz [string][default:'png']
show Show the figure on console instead of saving in current folder [True or False][default:False]
axxlabel Label for X-axis. If you provide this option, default label will be replaced [string][default: None]
axylabel Label for Y-axis. If you provide this option, default label will be replaced [string][default: None]
axlabelfontsize Font size for axis labels [float][default: 9]
ylm Range of ticks to plot on Y-axis [float tuple (bottom, top, interval)][default: None]
gstyle Style of the text for markernames. 1 for default text and 2 for box text [int][default: 1]

Returns:

Manhatten plot image in same directory (manhatten.png)

Working example

Extract the sequences from the FASTA file

bioinfokit.analys.extract_seq(file, id)

Parameters Description
file input FASTA file from which sequneces to be extracted
id sequence ID file

Returns: Extracted sequences in FASTA format file in same directory (out.fasta)

Bar-dot plot

latest update v0.8.5

bioinfokit.visuz.stat.bardot(df, colorbar, colordot, bw, dim, r, ar, hbsize, errorbar, dotsize, markerdot, valphabar, valphadot, show, figtype, axxlabel, axylabel, axlabelfontsize, axlabelfontname, ylm, axtickfontsize, axtickfontname, yerrlw, yerrcw)

Parameters Description
df Pandas dataframe object
colorbar Color of bar graph [string or list][default:"#bbcfff"]
colordot Color of dots on bar [string or list][default:"#ee8972"]
bw Width of bar [float][default: 0.4]
dim Figure size [tuple of two floats (width, height) in inches][default: (6, 4)]
r Figure resolution in dpi [int][default: 300]
ar Rotation of X-axis labels [float][default: 0]
hbsize Horizontal bar size for standard error bars [float][default: 4]
errorbar Draw standard error bars [bool (True or False)][default: True]
dotsize The size of the dots in the plot [float][default: 6]
markerdot Shape of the dot marker. See more options at https://matplotlib.org/3.1.1/api/markers_api.html [string][default: "o"]
valphabar Transparency of bars on plot [float (between 0 and 1)][default: 1]
valphadot Transparency of dots on plot [float (between 0 and 1)][default: 1]
figtype Format of figure to save. Supported format are eps, pdf, pgf, png, ps, raw, rgba, svg, svgz [string][default:'png']
show Show the figure on console instead of saving in current folder [True or False][default:False]
axxlabel Label for X-axis. If you provide this option, default label will be replaced [string][default: None]
axylabel Label for Y-axis. If you provide this option, default label will be replaced [string][default: None]
axlabelfontsize Font size for axis labels [float][default: 9]
axlabelfontname Font name for axis labels [string][default: 'Arial']
ylm Range of ticks to plot on Y-axis [float tuple (bottom, top, interval)][default: None]
axtickfontsize Font size for axis ticks [float][default: 9]
axtickfontname Font name for axis ticks [string][default: 'Arial']
yerrlw Error bar line width [float][default: None]
yerrcw Error bar cap width [float][default: None]

Returns:

Bar-dot plot image in same directory (bardot.png)

Working Example

FASTQ quality format detection

bioinfokit.analys.format.fq_qual_var(file)

Parameters Description
file FASTQ file to detect quality format [deafult: None]

Returns:

Quality format encoding name for FASTQ file (Supports only Sanger, Illumina 1.8+ and Illumina 1.3/1.4)

Working Example

Linear regression analysis

bioinfokit.visuz.stat.lin_reg(df, x, y)

Parameters Description
df Pandas dataframe object
x Name of column having independent X variables [list][default:None]
y Name of column having dependent Y variables [list][default:None]

Returns:

Regression analysis summary

Working Example

Regression plot

bioinfokit.visuz.stat.regplot(df, x, y, yhat, dim, colordot, colorline, r, ar, dotsize, markerdot, linewidth, valphaline, valphadot, show, figtype, axxlabel, axylabel, axlabelfontsize, axlabelfontname, xlm, ylm, axtickfontsize, axtickfontname)

Parameters Description
df Pandas dataframe object
x Name of column having independent X variables [string][default:None]
y Name of column having dependent Y variables [string][default:None]
yhat Name of column having predicted response of Y variable (y_hat) from regression [string][default:None]
dim Figure size [tuple of two floats (width, height) in inches][default: (6, 4)]
r Figure resolution in dpi [int][default: 300]
ar Rotation of X-axis labels [float][default: 0]
dotsize The size of the dots in the plot [float][default: 6]
markerdot Shape of the dot marker. See more options at https://matplotlib.org/3.1.1/api/markers_api.html [string][default: "o"]
valphaline Transparency of regression line on plot [float (between 0 and 1)][default: 1]
valphadot Transparency of dots on plot [float (between 0 and 1)][default: 1]
linewidth Width of regression line [float][default: 1]
figtype Format of figure to save. Supported format are eps, pdf, pgf, png, ps, raw, rgba, svg, svgz [string][default:'png']
show Show the figure on console instead of saving in current folder [True or False][default:False]
axxlabel Label for X-axis. If you provide this option, default label will be replaced [string][default: None]
axylabel Label for Y-axis. If you provide this option, default label will be replaced [string][default: None]
axlabelfontsize Font size for axis labels [float][default: 9]
axlabelfontname Font name for axis labels [string][default: 'Arial']
xlm Range of ticks to plot on X-axis [float tuple (bottom, top, interval)][default: None]
ylm Range of ticks to plot on Y-axis [float tuple (bottom, top, interval)][default: None]
axtickfontsize Font size for axis ticks [float][default: 9]
axtickfontname Font name for axis ticks [string][default: 'Arial']
colordot Color of dots on plot [string ][default:"#4a4e4d"]

Returns:

Regression plot image in same directory (reg_plot.png)

Working Example

GFF3 to GTF file format conversion

bioinfokit.analys.gff.gff_to_gtf(file)

Parameters Description
file GFF3 genome annotation file

Returns:

GTF format genome annotation file (file.gtf will be saved in same directory)

Working Example

Scree plot

bioinfokit.visuz.cluster.screeplot(obj, axlabelfontsize, axlabelfontname, axxlabel, axylabel, figtype, r, show)

Parameters Description
obj list of component name and component variance
axlabelfontsize Font size for axis labels [float][default: 9]
axlabelfontname Font name for axis labels [string][default: 'Arial']
axxlabel Label for X-axis. If you provide this option, default label will be replaced [string][default: None]
axylabel Label for Y-axis. If you provide this option, default label will be replaced [string][default: None]
figtype Format of figure to save. Supported format are eps, pdf, pgf, png, ps, raw, rgba, svg, svgz [string][default:'png']
r Figure resolution in dpi [int][default: 300]
show Show the figure on console instead of saving in current folder [True or False][default:False]

Returns:

Scree plot image (screeplot.png will be saved in same directory)

Working Example

Principal component analysis (PCA) loadings plots

bioinfokit.visuz.cluster.pcaplot(x, y, z, labels, var1, var2, var3, axlabelfontsize, axlabelfontname, figtype, r, show)

Parameters Description
x loadings (correlation coefficient) for principal component 1 (PC1)
y loadings (correlation coefficient) for principal component 2 (PC2)
z loadings (correlation coefficient) for principal component 3 (PC2)
labels original variables labels from dataframe used for PCA
var1 Proportion of PC1 variance [float (0 to 1)]
var2 Proportion of PC2 variance [float (0 to 1)]
var3 Proportion of PC3 variance [float (0 to 1)]
axlabelfontsize Font size for axis labels [float][default: 9]
axlabelfontname Font name for axis labels [string][default: 'Arial']
figtype Format of figure to save. Supported format are eps, pdf, pgf, png, ps, raw, rgba, svg, svgz [string][default:'png']
r Figure resolution in dpi [int][default: 300]
show Show the figure on console instead of saving in current folder [True or False][default:False]
plotlabels Plot labels as defined by labels parameter [True or False][default:True]

Returns:

PCA loadings plot 2D and 3D image (pcaplot_2d.png and pcaplot_3d.png will be saved in same directory)

Working Example

Principal component analysis (PCA) biplots

latest update v0.8.4

bioinfokit.visuz.cluster.biplot(cscore, loadings, labels, var1, var2, var3, axlabelfontsize, axlabelfontname, figtype, r, show, markerdot, dotsize, valphadot, colordot, arrowcolor, valphaarrow, arrowlinestyle, arrowlinewidth, centerlines, datapoints, legendpos, colorlist)

Parameters Description
cscore principal component scores (obtained from PCA().fit_transfrom() function in sklearn.decomposition)
loadings loadings (correlation coefficient) for principal components
labels original variables labels from dataframe used for PCA
var1 Proportion of PC1 variance [float (0 to 1)]
var2 Proportion of PC2 variance [float (0 to 1)]
var3 Proportion of PC3 variance [float (0 to 1)]
axlabelfontsize Font size for axis labels [float][default: 9]
axlabelfontname Font name for axis labels [string][default: 'Arial']
figtype Format of figure to save. Supported format are eps, pdf, pgf, png, ps, raw, rgba, svg, svgz [string][default:'png']
r Figure resolution in dpi [int][default: 300]
show Show the figure on console instead of saving in current folder [True or False][default:False]
markerdot Shape of the dot on plot. See more options at https://matplotlib.org/3.1.1/api/markers_api.html [string][default: "o"]
dotsize The size of the dots in the plot [float][default: 6]
valphadot Transparency of dots on plot [float (between 0 and 1)][default: 1]
colordot Color of dots on plot [string or list ][default:"#4a4e4d"]
arrowcolor Color of the arrow [string ][default:"#fe8a71"]
valphaarrow Transparency of the arrow [float (between 0 and 1)][default: 1]
arrowlinestyle line style of the arrow. check more styles at https://matplotlib.org/3.1.0/gallery/lines_bars_and_markers/linestyles.html [string][default: '-']
arrowlinewidth line width of the arrow [float][default: 1.0]
centerlines draw center lines at x=0 and y=0 for 2D plot [bool (True or False)][default: True]
datapoints plot data points on graph [bool (True or False)][default: True]
legendpos position of the legend on plot. For more options see loc parameter at https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.legend.html [string ][default:"best"]
colorlist list of the categories to assign the color [list][default:None]

Returns:

PCA biplot 2D and 3D image (biplot_2d.png and biplot_3d.png will be saved in same directory)

Working Example

t-SNE plot

latest update v0.8.5

bioinfokit.visuz.cluster.tsneplot(score, colorlist, axlabelfontsize, axlabelfontname, figtype, r, show, markerdot, dotsize, valphadot, colordot, dim, figname, legendpos, legendanchor)

Parameters Description
score t-SNE component embeddings (obtained from TSNE().fit_transfrom() function in sklearn.manifold)
colorlist list of the categories to assign the color [list][default:None]
axlabelfontsize Font size for axis labels [float][default: 9]
axlabelfontname Font name for axis labels [string][default: 'Arial']
figtype Format of figure to save. Supported format are eps, pdf, pgf, png, ps, raw, rgba, svg, svgz [string][default:'png']
r Figure resolution in dpi [int][default: 300]
show Show the figure on console instead of saving in current folder [True or False][default:False]
markerdot Shape of the dot on plot. See more options at https://matplotlib.org/3.1.1/api/markers_api.html [string][default: "o"]
dotsize The size of the dots in the plot [float][default: 6]
valphadot Transparency of dots on plot [float (between 0 and 1)][default: 1]
colordot Color of dots on plot [string or list ][default:"#4a4e4d"]
legendpos position of the legend on plot. For more options see loc parameter at https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.legend.html [string ][default:"best"]
legendanchor position of the legend outside of the plot. For more options see bbox_to_anchor parameter at https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.legend.html [list][default:None]
dim Figure size [tuple of two floats (width, height) in inches][default: (6, 4)]
figname name of figure [string ][default:"tsne_2d"]

Returns:

t-SNE 2D image (tsne_2d.png will be saved in same directory)

Working Example

RPM or CPM normalization

Normalize raw gene expression counts into Reads per million mapped reads (RPM) or Counts per million mapped reads (CPM)

bioinfokit.analys.norm.cpm(df)

Parameters Description
df Pandas dataframe containing raw gene expression values. Genes with missing expression values (NA) will be dropped.

Returns:

RPM or CPM normalized Pandas dataframe as class attributes (cpm_norm)

Working Example

RPKM or FPKM normalization

Normalize raw gene expression counts into Reads per kilo base per million mapped reads (RPKM) or Fragments per kilo base per million mapped reads (FPKM)

bioinfokit.analys.norm.rpkm(df, gl)

Parameters Description
df Pandas dataframe containing raw gene expression values. Genes with missing expression or gene length values (NA) will be dropped.
gl Name of a column having gene length in bp [string][default: None]

Returns:

RPKM or FPKM normalized Pandas dataframe as class attributes (rpkm_norm)

Working Example

TPM normalization

Normalize raw gene expression counts into Transcript per million (TPM)

bioinfokit.analys.norm.tpm(df, gl)

Parameters Description
df Pandas dataframe containing raw gene expression values. Genes with missing expression or gene length values (NA) will be dropped.
gl Name of a column having gene length in bp [string][default: None]

Returns:

TPM normalized Pandas dataframe as class attributes (tpm_norm)

Working Example

How to cite bioinfokit?

  • Renesh Bedre. (2020, July 29). reneshbedre/bioinfokit: Bioinformatics data analysis and visualization toolkit (Version v0.9). Zenodo. http://doi.org/10.5281/zenodo.3965241
  • Additionally check Zenodo to cite specific version of bioinfokit

References:

  • Travis E. Oliphant. A guide to NumPy, USA: Trelgol Publishing, (2006).
  • John D. Hunter. Matplotlib: A 2D Graphics Environment, Computing in Science & Engineering, 9, 90-95 (2007), DOI:10.1109/MCSE.2007.55 (publisher link)
  • Fernando Pérez and Brian E. Granger. IPython: A System for Interactive Scientific Computing, Computing in Science & Engineering, 9, 21-29 (2007), DOI:10.1109/MCSE.2007.53 (publisher link)
  • Michael Waskom, Olga Botvinnik, Joel Ostblom, Saulius Lukauskas, Paul Hobson, MaozGelbart, … Constantine Evans. (2020, January 24). mwaskom/seaborn: v0.10.0 (January 2020) (Version v0.10.0). Zenodo. http://doi.org/10.5281/zenodo.3629446
  • Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, Édouard Duchesnay. Scikit-learn: Machine Learning in Python, Journal of Machine Learning Research, 12, 2825-2830 (2011)
  • Wes McKinney. Data Structures for Statistical Computing in Python, Proceedings of the 9th Python in Science Conference, 51-56 (2010)

bioinfokit cited by:

  • Jennifer Gribble, Andrea J. Pruijssers, Maria L. Agostini, Jordan Anderson-Daniels, James D. Chappell, Xiaotao Lu, Laura J. Stevens, Andrew L. Routh, Mark R. Denison bioRxiv 2020.04.23.057786; doi: https://doi.org/10.1101/2020.04.23.057786
  • Greaney AM, Adams TS, Raredon MS, Gubbins E, Schupp JC, Engler AJ, Ghaedi M, Yuan Y, Kaminski N, Niklason LE. Platform Effects on Regeneration by Pulmonary Basal Cells as Evaluated by Single-Cell RNA Sequencing. Cell Reports. 2020 Mar 24;30(12):4250-65.

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