notebook.community

Edit and run



In [1]:

    
%run ~/relmapping/annot/notebooks/__init__.ipynb









    



/mnt/home3/jj374/anaconda36/lib/python3.6/site-packages/statsmodels/compat/pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.
  from pandas.core import datetools






    



os.getcwd(): /mnt/b2/scratch/ahringer/jj374/lab/relmapping

http://genome.cshlp.org/content/27/12/2108.long

aligned to the ce10 version of the C. elegans genome

Additional analysis files, including DNase I signal data, all DHSs and nearest genes, putative TF footprints, novel motifs, motif-associated genes, and GO analysis, are available from WormBase (detailed list of files in Supplemental Table S3).

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE97425

GSE97425_embryo.ce10.allDHS.bed.gz



In [2]:

    
#
#url_ = 'ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE97nnn/GSE97425/suppl/GSE97425_embryo.ce10.allDHS.bed.gz'
#!cd ~/relmapping/wget; wget -m --no-parent {url_}

fp_ = 'wget/ftp.ncbi.nlm.nih.gov/geo/series/GSE97nnn/GSE97425/suppl/GSE97425_embryo.ce10.allDHS.bed.gz'
df_ = pd.read_csv(fp_, names=['chrom', 'start', 'end', 'score'], sep='\t')
df_ho = df_[['chrom', 'start', 'end']]
df_.head()









    Out[2]:







  
    
      
      chrom
      start
      end
      score
    
  
  
    
      0
      chrI
      3900
      4050
      1391.125000
    
    
      1
      chrI
      9740
      9890
      507.437500
    
    
      2
      chrI
      11380
      11530
      1080.578125
    
    
      3
      chrI
      13820
      13970
      149.218750
    
    
      4
      chrI
      16920
      17070
      164.890625



In [3]:

    
fp_ = 'annot/Fig2S3_overlaps/Ho2017/Ho2017_DNase_emb.bed'
df_[['chrom', 'start', 'end']].to_csv(fp_, header=False, index=False, sep='\t')
!wc -l {fp_}









    



41825 annot/Fig2S3_overlaps/Ho2017/Ho2017_DNase_emb.bed



In [4]:

    
gv = yp.GenomicVenn2(
    BedTool.from_dataframe(regl_mode(flank_len=75)),
    BedTool.from_dataframe(df_ho),
    label_a='Accessible sites',
    label_b='(Ho et al., 2017)\nemb DNase-seq peaks',
)

plt.figure(figsize=(8,8))
plt.subplot(1,1,1)
gv.plot()









    Out[4]:





<matplotlib_venn._common.VennDiagram at 0x7f20990bdc18>

	chrom	start	end	score
0	chrI	3900	4050	1391.125000
1	chrI	9740	9890	507.437500
2	chrI	11380	11530	1080.578125
3	chrI	13820	13970	149.218750
4	chrI	16920	17070	164.890625