SSCRNA-v1.0

single cell sequencing simulation program

Working Directory

Set up a working directory (WorkPath/), Create several new folders (fragment_data, pcr_control_data, umi_data, Simulation_Path).
Put the files (Test_Data.txt, Error_Profile.txt, Quality_Profile.txt) and codes (SSCRNA.py, MyProcess10.py, S_S2.py, simulation_in_preDatabase.py) in the working directory.

Running the main file (Main.py)--for construction simulation sequencing library

As recorded in Main.py file:

Import packages:

import sys
sys.path.append('WorkPath/')
import SSCRNA as sc
import time
import os
import pickle

read the cell specific profile

filename = 'WorkPath/'+'/Test_Data.txt'

read the gene names and mRNA number

cell_pro,gene_na=sc.Read_Gene_Table(filename)

get the seq of genes (f_seq variable)

sequences data can be found in ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_32/gencode.v32.pc_transcripts.fa.gz

f=r"gencode.v32.pc_transcripts.fa"

extract the gene names of transcripts fasta file

f_na=sc.read_names_from_file(f)

split the name elements

genes_in=sc.split_GENENAMES(f_na)

extract the Ensemble gene ids

gene_name_list=sc.get_iterm_list(genes_in,2)

delete the ensemble version

gene_name_list=sc.del_version(gene_name_list)
sel_genes=sc.del_version(gene_na)

select genes corresponding ground truth (Test_Data.txt)

sel_index=sc.get_gene_index(gene_name_list,sel_genes)

extract the corresponding sequences

f_seq=sc.read_seqs_from_file(f,sel_index)

get cell profile

f_na=sc.get_sel_gene_name(gene_name_list,sel_index)
cell_pro_n=sc.get_map_gene_profile(cell_pro,sel_index)

seperate cell name and profile to two list

cells_profile=[]
cell_names=[]
for each in cell_pro_n:
cell_names.append(each)
cells_profile.append(cell_pro_n[each])

construct simulation sequencing library

make real cell fragment database

frag_list_path='WorkPath/'+'fragment_data/'
sc.multi_cell2(frag_list_path,cells_profile,f_na,f_seq)

make pcr database

pcr_list_path='WorkPath/'+'pcr_control_data/'
sc.PCR_database(pcr_list_path,frag_list_path,3)

make UMI database

umi_path='WorkPath/'+'umi_data/'
sc.get_UMI_bank(frag_list_path,umi_path,8)

make barcode library:get_barcord_bank(length,least_distance,number)

cell_barcord=sc.get_barcord_bank(27,2,22)

save some data in pickle data

xc=[cell_barcord, f_na, f_seq]
with open('WorkPath/'+'cell_barcord_gene_name_seq.pickle', 'wb') as handle:
pickle.dump(xc, handle)

run the simulation program (python simulation_in_preDatabase.py [number of reads] working_path process)

make sure using linux system, and run the command as follow (number of reads = 200, process = 5):
python simulation_in_preDatabase.py 200 'WorkPath/' 5

running process showing as follow

The simulation data will be located in the ‘Simulation_Path’ folder