Error executing process > 'get_abundances (1)'

[claudiodonati]

The program runs fine on test data, but on my it dies at the get_abundances stage

Command:
nextflow run main.nf -profile docker --reads sample1.fastq --outdir out_dir --db "db/16S_ribosomal_RNA" --tax "db/taxdb/" -resume

output:
nf-core/nanoclust] Pipeline completed with errors
Error executing process > 'get_abundances (1)'

Caused by:
Process get_abundances (1) terminated with an error exit status (1)

Command executed [/home/donatic/Downloads/NanoCLUST-master/templates/get_abundance.py]:

#!/usr/bin/env python

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
import pandas as pd
from functools import reduce
import requests
import json
#https://unipept.ugent.be/apidocs/taxonomy

def get_taxname(tax_id,tax_level):
tags = {"S": "species_name","G": "genus_name","F": "family_name","O":'order_name', "C": "class_name"}
tax_level_tag = tags[tax_level]
#Avoids pipeline crash due to "nan" classification output. Thanks to Qi-Maria from Github
if str(tax_id) == "nan":
tax_id = 1

  path = 'http://api.unipept.ugent.be/api/v1/taxonomy.json?input[]=' + str(int(tax_id)) + '&extra=true&names=true'
  complete_tax = requests.get(path).text

  #Checks for API correct response (field containing the tax name). Thanks to devinbrown from Github
  try:
      name = json.loads(complete_tax)[0][tax_level_tag]
  except:
      name = str(int(tax_id))

  return json.loads(complete_tax)[0][tax_level_tag]

def get_abundance_values(names,paths):
dfs = []
for name,path in zip(names,paths):
data = pd.read_csv(path, index_col=False, sep=';').iloc[:,1:]

      total = sum(data['reads_in_cluster'])
      rel_abundance=[]

      for index,row in data.iterrows():
          rel_abundance.append(row['reads_in_cluster'] / total)
          
      data['rel_abundance'] = rel_abundance
      dfs.append(pd.DataFrame({'taxid': data['taxid'], 'rel_abundance': rel_abundance}))
      data.to_csv("" + name + "_nanoclust_out.txt")

  return dfs

def merge_abundance(dfs,tax_level):
df_final = reduce(lambda left,right: pd.merge(left,right,on='taxid',how='outer').fillna(0), dfs)
df_final["taxid"] = [get_taxname(row["taxid"], tax_level) for index, row in df_final.iterrows()]
df_final_grp = df_final.groupby(["taxid"], as_index=False).sum()
return df_final_grp

def get_abundance(names,paths,tax_level):
if(not isinstance(paths, list)):
paths = [paths]
names = [names]

  dfs = get_abundance_values(names,paths)
  df_final_grp = merge_abundance(dfs, tax_level)
  df_final_grp.to_csv("rel_abundance_"+ names[0] + "_" + tax_level + ".csv", index = False)

paths = "sample1.nanoclust_out.txt"
names = "sample1"

get_abundance(names,paths, "G")
get_abundance(names,paths, "S")
get_abundance(names,paths, "O")
get_abundance(names,paths, "F")

Command exit status:
1

Command output:
(empty)

Command error:
Traceback (most recent call last):
File ".command.sh", line 65, in
get_abundance(names,paths, "G")
File ".command.sh", line 59, in get_abundance
df_final_grp = merge_abundance(dfs, tax_level)
File ".command.sh", line 49, in merge_abundance
df_final["taxid"] = [get_taxname(row["taxid"], tax_level) for index, row in df_final.iterrows()]
File ".command.sh", line 49, in
df_final["taxid"] = [get_taxname(row["taxid"], tax_level) for index, row in df_final.iterrows()]
File ".command.sh", line 28, in get_taxname
return json.loads(complete_tax)[0][tax_level_tag]
IndexError: list index out of range

Any hint?

[BirgitRijvers]

@claudiodonati Have you been able to fix this error? I'm struggling with exactly the same one.

[claudiodonati]

Nope, I gave up after some time

…

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