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09_tximport_consolidateGenes.py
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09_tximport_consolidateGenes.py
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#####################################################################################################################################################################
#
# Script used in:
#
# "Gene expression profiling across ontogenetic stages in wood white (Leptidea sinapis) reveals pathways linked to butterfly diapause regulation."
# Luis Leal, Venkat Talla, Thomas Källman, Magne Friberg, Christer Wiklund, Vlad Dincă, Roger Vila, Niclas Backström
# Mol. Eco. (2018)
#
#
#####################################################################################################################################################################
#
# Luis Leal
# Uppsala University, Uppsala, Sweden, 2017
# Written in Python 3
#
#####################################################################################################################################################################
#####################################################################################################################################################################
#
# Script used to consolidate Trinity entries and counts associated to the same gene
#
# Input files: 1 -> tximport output file (tximport_OUTPUT.csv)
# 2 -> Annotation file (OUT_GO_Associations.csv)
#
# Output: 2 files -> updated tximport output file (consolidated counts)
# -> updated annotation file (consolidated GO terms)
#
#####################################################################################################################################################################
print('\n Gleaning data ...')
######################################################### USAGE
error_message1 = ' \n \
USAGE: $python3 tximport_consolidateGenes.py <tximport_OUTPUT.csv> <annotation_file.csv> \n'
######################################################### LOAD STANDARD MODULES
import sys
import re # 're' module provides regular expression matching operations
import ast # required to convert reference tree from string to list
import os # required to create new folders
import time
import csv #required to open csv file
from pdb import set_trace as bp # when using break points during debugging
######################################################## OPEN INPUT FILES
try:
tximport_list = list() #open tximport output file as csv
with open(sys.argv[1], newline='') as csvfile1:
inputfile_1 = csv.reader(csvfile1, delimiter='\t')
for row in inputfile_1:
tximport_list.append(row)
# print(', '.join(row))
except:
print('\n Error[1]: input file missing.')
print(error_message1)
exit()
try:
annotation_list = list() #open annotation file as csv
with open(sys.argv[2], newline='') as csvfile2:
inputfile_2 = csv.reader(csvfile2, delimiter='\t')
for row in inputfile_2:
annotation_list.append(row)
except:
print('\n Error[2]: input file missing.')
print(error_message1)
exit()
####################################################### FUNCTION: readGENE
def readGene(geneName_long):
if geneName_long != "." :
mark_g = geneName_long.find('|')
if mark_g != -1 :
aux_g = geneName_long[(mark_g+1):]
mark_g2 = aux_g.find('|')
if mark_g2 != -1 :
geneName_long = aux_g[:mark_g2]
return geneName_long
####### END
####################################################### FUNCTION: updateList_v2
def updateList_v2(newS,referenceS) :
if newS == '.' or newS == '' :
aux_output = referenceS
elif referenceS == '.' or referenceS == '' :
aux_output = newS
elif newS in referenceS :
aux_output = referenceS
elif referenceS in newS :
aux_output = newS
else :
aux_output = referenceS + "`" + newS
return aux_output
####### END
####################################################### FUNCTION: cleanGO
def cleanGO(entry_aux) :
aux_list1 = list()
aux_list_terms = list()
if entry_aux != "." and entry_aux != "":
for m in re.finditer('GO:', entry_aux): # find all GO terms in description
aux_list1.append(m.start())
for n in range(len(aux_list1)) : # for all GO terms in description, get GO term (based on index)
GO_aux3 = entry_aux[aux_list1[n]:(aux_list1[(n)]+10)]
#print(GO_aux3)
aux_list_terms.append(GO_aux3)
aux_list_terms = sorted(list(set(aux_list_terms))) # remove duplicates and sort list of GO terms alphabetically
Go_clean = "^NA`".join(aux_list_terms) # convert list to string (Trinotate format)
else :
Go_clean = entry_aux
return Go_clean
####### END
####################################################### FUNCTION: entryCompare
def entryCompare(entry_1, entry_2) :
dif_counter_1 = 0
dif_counter_2 = 0
#
if entry_1 == entry_2 : # the two lists of gene-hits are identical
compare_out = 1
else:
entry_list_1 = entry_1.split('`')
entry_list_2 = entry_2.split('`')
#
for gene in entry_list_1 :
if gene not in entry_list_2 : dif_counter_1 += 1
#
for gene in entry_list_2 :
if gene not in entry_list_1 : dif_counter_2 += 1
#
if (dif_counter_1 == 0) and (len(entry_list_1) >= 2) : #largest list contains shortest list and smallest list is at least 2 elements long
compare_out = 2
elif (dif_counter_2 == 0) and (len(entry_list_2) >= 2) : #largest list contains shortest list and smallest list is at least 2 elements long
compare_out = 2
else :
compare_out = 0 #the two lists are different
return compare_out
####### END
####################################################### FUNCTION: updateCounts
def updateCounts(countsList_1, countsList_2) :
outList = list()
for k in range(len(countsList_1)) :
aux_1 = float(countsList_1[k]) + float(countsList_2[k])
outList.append(aux_1)
return outList
####### END
####################################################### FUNCTION: updateAnnotation
def updateAnnotation(annList_1, annList_2) :
outList = list()
for k in range(len(annList_1)) :
if annList_1[k] == annList_2[k] :
outList.append(annList_1[k])
else :
aux_1 = updateList_v2(annList_1[k],annList_2[k])
outList.append(aux_1)
return outList
####### END
####################################################### FUNCTION: checkCounts
def checkCounts(countsList) :
counter_aux = 0
for entry in countsList :
if float(entry) > 0.5 : counter_aux += 1
if counter_aux > 1 :
outFlag = 1
else :
outFlag = 0
return outFlag
####### END
######################################################## PROCESS DATA
##### read tximport file
tximport_TRINITY_name_list = list()
tximport_counts_list = list()
Flag_header = 1
for line in tximport_list :
if Flag_header == 0 :
tximport_TRINITY_name_list.append(line[0]) # store Trinity gene name
tximport_counts_list.append(line[1:]) # store counts associated to each gene (for all samples)
else :
tximportHeader = line
Flag_header = 0
##### read annoation file
annoation_ALL = list()
Flag_header = 1
for line in annotation_list :
if Flag_header == 0 :
annoation_ALL.append(line)
else :
Flag_header = 0
##### Find Trinity entries associated to the same gene; adjust tximport and annotation file accordingly.
##### This is done by sorting gene names (UniProt entries) alphabetically and then comparing each entry with the previous one
### sort annotation file alphabetically
annoation_SORTED_list = list()
annoation_SORTED_list = sorted(annoation_ALL, key=lambda entry:entry[1]) # sort annotation alphabetically by UniProt's entry name
#for line in annoation_SORTED_list : print('\n', line)
annoation_TRINITY_name_list = list()
annoation_entry_name_list = list()
annotation_geneInfo_list = list()
for entry in annoation_SORTED_list :
annoation_TRINITY_name_list.append(entry[0]) # store Trinity gene name
annoation_entry_name_list.append(entry[1]) # store UniProt entry name associated to each Trinity entry
annotation_geneInfo_list.append(entry[1:]) # store info associated to each gene (protein name, Go terms, etc)
### check for presence of several Trinity entries associated to the same gene
Annotation_DIC = dict() # dictionary: keeps info about unique Trinity genes (gene duplicates are consolidated into just one entry)
Counts_DIC = dict() # dictionary: consolidated counts
Removed_DIC = dict() # dictionary: duplicate entries
geneRepeat_counter = 0
geneReject_counter = 0
counter_MAIN = 0
counter_b = 0
# First dictionary entry
Annotation_DIC[annoation_TRINITY_name_list[0]] = annotation_geneInfo_list[0]
aux_i = tximport_TRINITY_name_list.index(annoation_TRINITY_name_list[0]) #index location of Trinity entry in tximport lists
Counts_DIC[tximport_TRINITY_name_list[aux_i]] = tximport_counts_list[aux_i]
store_Annot = annoation_entry_name_list[0]
store_Trinity = annoation_TRINITY_name_list[0]
for k in range(len(annoation_TRINITY_name_list)) :
#
aux_i = tximport_TRINITY_name_list.index(annoation_TRINITY_name_list[k]) #index location of Trinity entry in tximport lists
#
if (k > 0) :
#
counter_MAIN += 1
counter_b += 1
if counter_b == 1000 :
print(counter_MAIN) #counter used to keep track of things during long runs
counter_b = 0
#
flagCounts = checkCounts(tximport_counts_list[aux_i]) # checks whether there are counts observed for more than one sample
if (flagCounts == 0) and (annoation_entry_name_list[k] == '.') : # filter out non-annotated genes with counts for only one sample
geneReject_counter += 1
print(annoation_TRINITY_name_list[k])
#
store_Annot = store_Annot
store_Trinity = store_Trinity
#
Removed_DIC[annoation_TRINITY_name_list[k]] = annotation_geneInfo_list[k]
#
elif (annoation_entry_name_list[k] == '.') or (store_Annot == '.') : #no annotation info (or comparing with gene with no annotation info)
Annotation_DIC[annoation_TRINITY_name_list[k]] = annotation_geneInfo_list[k]
Counts_DIC[tximport_TRINITY_name_list[aux_i]] = tximport_counts_list[aux_i]
#
store_Annot = annoation_entry_name_list[k]
store_Trinity = annoation_TRINITY_name_list[k]
else :
Flag_sameness = entryCompare(annoation_entry_name_list[k], store_Annot) #compares list of gene-hits associated to two Trinity entries
#print(annoation_TRINITY_name_list[k],Flag_sameness)
if Flag_sameness == 0 : #gene-hit lists are different >> different gene
#
Annotation_DIC[annoation_TRINITY_name_list[k]] = annotation_geneInfo_list[k]
Counts_DIC[tximport_TRINITY_name_list[aux_i]] = tximport_counts_list[aux_i]
#
store_Annot = annoation_entry_name_list[k]
store_Trinity = annoation_TRINITY_name_list[k]
#
elif Flag_sameness == 1 : #gene-hit lists are exactly the same >> same gene >> must update counts
geneRepeat_counter += 1
#
ind_ref = tximport_TRINITY_name_list.index(store_Trinity)
counts_ref_list = Counts_DIC[tximport_TRINITY_name_list[ind_ref]]
newCounts = updateCounts(tximport_counts_list[aux_i], counts_ref_list)
Counts_DIC[tximport_TRINITY_name_list[ind_ref]] = newCounts
#print('\n', '\n', tximport_counts_list[aux_i])
#print('\n', counts_ref_list)
#print('\n', newCounts)
#
store_Annot = store_Annot
store_Trinity = store_Trinity
#
Removed_DIC[annoation_TRINITY_name_list[k]] = annotation_geneInfo_list[k]
else : # gene-hit lists almost the same >> same gene >> must update counts and annotation info
geneRepeat_counter += 1
#print(annoation_TRINITY_name_list[k])
#
ind_ref = tximport_TRINITY_name_list.index(store_Trinity)
counts_ref_list = Counts_DIC[tximport_TRINITY_name_list[ind_ref]]
newCounts = updateCounts(tximport_counts_list[aux_i], counts_ref_list) #computes new counts
Counts_DIC[tximport_TRINITY_name_list[ind_ref]] = newCounts #updates counts in dictionary
#
annot_Ref_list = Annotation_DIC[store_Trinity]
newAnnot_list = updateAnnotation(annotation_geneInfo_list[k], annot_Ref_list)
Annotation_DIC[store_Trinity] = newAnnot_list #updates annotation info in dictionary
#
store_Annot = newAnnot_list[0]
store_Trinity = store_Trinity
#
Removed_DIC[annoation_TRINITY_name_list[k]] = annotation_geneInfo_list[k]
### Number or sequences removed
print('\n', 'Number of sequences removed:', geneRepeat_counter)
print('\n', 'Number of sequences rejected:', geneReject_counter)
##### List of genes in final dictionary
trinity_list_final = list()
for entry in Annotation_DIC :
trinity_list_final.append(entry)
#print(entry)
trinity_list_final = sorted(trinity_list_final) ## sort alphabetically
##### remove duplicate GO entries from Trinity_DIC dictionary
for gene in trinity_list_final :
entry_aux_list = Annotation_DIC.get(gene ,0)
if type(entry_aux_list) == tuple : entry_aux_list = list(entry_aux_list) #converts tuple to list
if entry_aux_list != "0" and entry_aux_list != 0:
#
entry_goBP = entry_aux_list[7] ##GO-BP
new_goBP = cleanGO(entry_goBP)
#
entry_goMF = entry_aux_list[8] ##GO-MF
new_goMF = cleanGO(entry_goMF)
#
entry_goCC = entry_aux_list[9] ##GO-CC
new_goCC = cleanGO(entry_goCC)
#
entry_gopfam = entry_aux_list[10] ##GO-Pfam
new_gopfam = cleanGO(entry_gopfam)
#
allGo = new_goBP + "^NA`" + new_goMF + "^NA`" + new_goCC + "^NA`" + new_gopfam ## All GO terms
new_allGo = cleanGO(allGo)
#
entry_aux_list = entry_aux_list[:12] #remove previous GO_clean entries; add the new ones
entry_aux_list.append(new_goBP)
entry_aux_list.append(new_goMF)
entry_aux_list.append(new_goCC)
entry_aux_list.append(new_gopfam)
entry_aux_list.append(new_allGo)
#
Annotation_DIC[gene] = entry_aux_list # new columns containing clean GO terms add to each entry
#print dictionaries
#for gene in trinity_list_final:
# aux_dic_list2 = Annotation_DIC.get(gene ,0)
# print()
# print(gene, aux_dic_list2)
#for gene in trinity_list_final:
# aux_dic_list2 = Counts_DIC.get(gene ,0)
# print()
# print(gene, aux_dic_list2)
#for gene in Removed_DIC:
# aux_dic_list2 = Removed_DIC.get(gene ,0)
# print()
# print(gene, aux_dic_list2)
#bp()
######################################################## SAVE RESULTS TO FILE
## Consolidated annotation file
outFileName1 = 'trinotate-invertebrates-CONSOLIDATED.txt'
outfile1 = open(outFileName1, 'w')
aux_save = '"Trinity_gene_ID"' + '\t' + '"Entry_name"' + '\t' + '"Accession_code"' + '\t' + '"Protein_name"' + '\t' + '"Gene_name"' + '\t' + '"Organism_name"' + '\t' + '"KEGG"' + '\t' + '"FlyBase"' + '\t' + '"GO_BioProcess"' + '\t' + '"GO_MolFunction"' + '\t' + '"GO_CelComponent"' + '\t' + '"GO_Pfam"' + '\t' + '"KB_or_trembl"' + '\t' + '"GO_BioProcess_clean"' + '\t' + '"GO_MolFunction_clean"' + '\t' + '"GO_CelComponent_clean"' + '\t' + '"GO_Pfam_clean"' + '\t' + '"All_GO_terms_clean"' + '\n' #write header
outfile1.write(aux_save)
for gene in trinity_list_final :
entry_aux_list = Annotation_DIC.get(gene ,0)
#print('\n', entry_aux_list)
if entry_aux_list != "" and entry_aux_list != "." and entry_aux_list != 0 :
aux_save = '"' + gene + '"'
for k in range(len(entry_aux_list)) :
#print(entry_aux_list[k])
if entry_aux_list[k] == '' : entry_aux_list[k] = '.'
aux_save = aux_save + '\t' + '"' + entry_aux_list[k] + '"'
else :
aux_save = '"' + gene + '"'
for k in range(0,17) :
aux_save = aux_save + '\t' + '"."'
aux_save = aux_save + '\n'
outfile1.write(aux_save)
## Genes excluded from consolidated annotation file
trinity_list_rejected = list()
for entry in Removed_DIC :
trinity_list_rejected.append(entry)
#print(entry)
trinity_list_rejected = sorted(trinity_list_rejected) ## sort alphabetically
outFileName2 = 'OUT_rejectedTrinityGenes.txt'
outfile2 = open(outFileName2, 'w')
aux_save = '"Trinity_gene_ID"' + '\t' + '"Entry_name"' + '\t' + '"Accession_code"' + '\t' + '"Protein_name"' + '\t' + '"Gene_name"' + '\t' + '"Organism_name"' + '\t' + '"KEGG"' + '\t' + '"FlyBase"' + '\t' + '"GO_BioProcess"' + '\t' + '"GO_MolFunction"' + '\t' + '"GO_CelComponent"' + '\t' + '"GO_Pfam"' + '\t' + '"KB_or_trembl"' + '\t' + '"GO_BioProcess_clean"' + '\t' + '"GO_MolFunction_clean"' + '\t' + '"GO_CelComponent_clean"' + '\t' + '"GO_Pfam_clean"' + '\t' + '"All_GO_terms_clean"' + '\n' #write header
outfile2.write(aux_save)
for gene in trinity_list_rejected :
entry_aux_list = Removed_DIC.get(gene ,0)
#print('\n', entry_aux_list)
if entry_aux_list != "" and entry_aux_list != "." and entry_aux_list != 0 :
aux_save = '"' + gene + '"'
for k in range(len(entry_aux_list)) :
#print(entry_aux_list[k])
if entry_aux_list[k] == '' : entry_aux_list[k] = '.'
aux_save = aux_save + '\t' + '"' + entry_aux_list[k] + '"'
else :
aux_save = '"' + gene + '"'
for k in range(0,17) :
aux_save = aux_save + '\t' + '"."'
aux_save = aux_save + '\n'
outfile2.write(aux_save)
## Consolidated counts
tximportHeader
outFileName3 = 'tximport-CONSOLIDATED.txt'
outfile3 = open(outFileName3, 'w')
aux_save = ''
for k in range(len(tximportHeader)) :
if k == 0 :
aux_save = '"' + str(tximportHeader[k]) + '"'
else :
aux_save = aux_save + '\t' + '"' + str(tximportHeader[k]) + '"'
aux_save = aux_save + '\n'
outfile3.write(aux_save) #write header
for gene in trinity_list_final :
entry_aux_list = Counts_DIC.get(gene ,0)
aux_save = '"' + gene + '"'
for k in range(len(entry_aux_list)) :
aux_save = aux_save + '\t' + str(entry_aux_list[k])
aux_save = aux_save + '\n'
outfile3.write(aux_save)
outfile1.close()
outfile2.close()
outfile3.close()
print()
print('\n Done!')