error using meme format motifs

Dear Mette Bentson,

When running BINdetect I get the belowissue with my motifs. I’m including an example of my MEME file. Any idea what may be causing this?

Many thanks for any help!

Steven

# TOBIAS 0.12.10 BINDetect (run started 2021-06-16 17:04:57.407317)
# Working directory: /work/rpapa/share/TOBIAS
# Command line call: TOBIAS BINDetect --motifs /work/rpapa/share/TOBIAS/motifs_meme/motif_1.txt --signals /work/rpapa/share/TOBIAS/erato.TExATAcxunique100_footprints.bw --genome /work/rpapa/share/REF/H_erato_dem/Herato_final.fasta --peaks /work/rpapa/share/TOBIAS/erato.TExATAcxunique100_peaks_start_end_original.rowsort.scafpos.bed --outdir BINDetect --cond_names erato_TE --cores 8

# ----- Input parameters -----
# signals:      ['/work/rpapa/share/TOBIAS/erato.TExATAcxunique100_footprints.bw']
# peaks:        /work/rpapa/share/TOBIAS/erato.TExATAcxunique100_peaks_start_end_original.rowsort.scafpos.bed
# motifs:       ['/work/rpapa/share/TOBIAS/motifs_meme/motif_1.txt']
# genome:       /work/rpapa/share/REF/H_erato_dem/Herato_final.fasta
# cond_names:   ['erato_TE']
# peak_header:  None
# naming:       name_id
# motif_pvalue: 0.0001
# bound_pvalue: 0.001
# pseudo:       None
# time_series:  False
# skip_excel:   False
# output_peaks: None
# prefix:       bindetect
# outdir:       /work/rpapa/share/TOBIAS/BINDetect
# cores:        8
# split:        100
# verbosity:    3


# ----- Output files -----
# /work/rpapa/share/TOBIAS/BINDetect/*/beds/*_erato_TE_bound.bed
# /work/rpapa/share/TOBIAS/BINDetect/*/beds/*_erato_TE_unbound.bed
# /work/rpapa/share/TOBIAS/BINDetect/*/beds/*_all.bed
# /work/rpapa/share/TOBIAS/BINDetect/*/plots/*_log2fcs.pdf
# /work/rpapa/share/TOBIAS/BINDetect/*/*_overview.txt
# /work/rpapa/share/TOBIAS/BINDetect/*/*_overview.xlsx
# /work/rpapa/share/TOBIAS/BINDetect/bindetect_distances.txt
# /work/rpapa/share/TOBIAS/BINDetect/bindetect_results.txt
# /work/rpapa/share/TOBIAS/BINDetect/bindetect_results.xlsx
# /work/rpapa/share/TOBIAS/BINDetect/bindetect_figures.pdf


2021-06-16 17:04:57 (18617) [INFO]      ----- Processing input data -----
2021-06-16 17:04:57 (18617) [INFO]      Checking reading/writing of files
2021-06-16 17:04:57 (18617) [INFO]      Reading peaks
2021-06-16 17:04:57 (18617) [INFO]      - Found 678 regions in input peaks
2021-06-16 17:04:57 (18617) [INFO]      - Merged to 677 regions
2021-06-16 17:04:57 (18617) [INFO]      Checking for match between --peaks and --fasta/--signals boundaries
2021-06-16 17:04:57 (18617) [INFO]      - Comparing peaks to /work/rpapa/share/REF/H_erato_dem/Herato_final.fasta
2021-06-16 17:04:57 (18617) [INFO]      - Comparing peaks to /work/rpapa/share/TOBIAS/erato.TExATAcxunique100_footprints.bw
2021-06-16 17:04:57 (18617) [INFO]      Estimating GC content from peak sequences
2021-06-16 17:04:57 (18617) [INFO]      - GC content estimated at 40.76%
2021-06-16 17:04:57 (18617) [INFO]      Reading motifs from file
Traceback (most recent call last):
  File "/cm/shared/apps/python3/3.6.10/bin/TOBIAS", line 11, in <module>
    load_entry_point('tobias==0.12.10', 'console_scripts', 'TOBIAS')()
  File "/cm/shared/apps/python3/3.6.10/lib/python3.6/site-packages/tobias/TOBIAS.py", line 154, in main
    args.func(args)
  File "/cm/shared/apps/python3/3.6.10/lib/python3.6/site-packages/tobias/tools/bindetect.py", line 223, in run_bindetect
    motif_list += MotifList().from_file(f)  #List of OneMotif objects
  File "/cm/shared/apps/python3/3.6.10/lib/python3.6/site-packages/tobias/utils/motifs.py", line 253, in from_file
    for c in range(motif.length):
TypeError: 'NoneType' object cannot be interpreted as an integer

MEME file:

MEME version 4

ALPHABET= ACGT

strands: + -

Background letter frequencies (from file `TExATAcaround_meme/dem_hydara_peaks_Genrich_all_merged.m1.mod'):
A 0.31000 C 0.19000 G 0.19000 T 0.31000 

MOTIF 1 CAGMGNGA-DREME-1

letter-probability matrix: alength= 4 w= 8 nsites= 10974 E= 1.4e-1262
  0.000000	  1.000000	  0.000000	  0.000000	
  1.000000	  0.000000	  0.000000	  0.000000	
  0.000000	  0.000000	  1.000000	  0.000000	
  0.652542	  0.347458	  0.000000	  0.000000	
  0.000000	  0.000000	  1.000000	  0.000000	
  0.098779	  0.266721	  0.303900	  0.330600	
  0.000000	  0.000000	  1.000000	  0.000000	
  1.000000	  0.000000	  0.000000	  0.000000	

MOTIF 2 CTYAACRC-DREME-2

letter-probability matrix: alength= 4 w= 8 nsites= 10470 E= 1.0e-1159
  0.000000	  1.000000	  0.000000	  0.000000	
  0.000000	  0.000000	  0.000000	  1.000000	
  0.000000	  0.584241	  0.000000	  0.415759	
  1.000000	  0.000000	  0.000000	  0.000000	
  1.000000	  0.000000	  0.000000	  0.000000	
  0.000000	  1.000000	  0.000000	  0.000000	
  0.661891	  0.000000	  0.338109	  0.000000	
  0.000000	  1.000000	  0.000000	  0.000000	

[StevenVB12]

Works!

Huge thanks,

Steven

From: Mette @.> Sent: Monday, June 21, 2021 8:58 AM To: @.> Cc: Steven M. Van @.>; @.> Subject: Re: [loosolab/TOBIAS] error using meme format motifs (#77)

Hi again Steven,

Good news - I found the bug, and have fixed this in tobias 0.12.11. Please fetch this version from PyPI (or from bioconda as soon as the repository updates). I hope this fixues the issue, and otherwise, feel free to let me know. Thanks!

Best Mette

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[msbentsen]

Hi Steven,

Uh I am not familiar with the results from butterfly ATAC - I am not sure if CTCF is conserved in function?

I can only encourage you to check the general ATAC-seq quality measures like insertion-size distribution plots, reads-in-peaks enrichment (=signal-to-noise ratio) and mapping rate etc. If these look good, you can make better assumptions about why some TFs might not be creating strong footprints. Otherwise, as I mentioned, you can still use the footprinting values, although these will be mostly driven by accessibility.

Best Mette