bioepic: OverflowError: cannot convert float infinity to integer

[anishdattani]

No description provided.

[anishdattani]

I have installed bioepic and have run the epic program from the bin folder. However, each time I run my H3K27me3 ChIP against Input I get the following error:

Merging the bins on both strands per chromosome. (File: count_reads_in_windows, Log level: INFO, Time: Thu, 03 Nov 2016 21:53:12 )
Merging ChIP and Input data. (File: helper_functions, Log level: INFO, Time: Thu, 03 Nov 2016 21:57:15 )
600000000.0 effective_genome_size (File: compute_background_probabilites, Log level: DEBUG, Time: Thu, 03 Nov 2016 21:58:51 )
200 window size (File: compute_background_probabilites, Log level: DEBUG, Time: Thu, 03 Nov 2016 21:58:51 )
0 total chip count (File: compute_background_probabilites, Log level: DEBUG, Time: Thu, 03 Nov 2016 21:58:51 )
0.0 average_window_readcount (File: compute_background_probabilites, Log level: DEBUG, Time: Thu, 03 Nov 2016 21:58:51 )
1 island_enriched_threshold (File: compute_background_probabilites, Log level: DEBUG, Time: Thu, 03 Nov 2016 21:58:51 )
4.0 gap_contribution (File: compute_background_probabilites, Log level: DEBUG, Time: Thu, 03 Nov 2016 21:58:51 )
1.0 boundary_contribution (File: compute_background_probabilites, Log level: DEBUG, Time: Thu, 03 Nov 2016 21:58:51 )
/home/anish/.local/lib/python2.7/site-packages/epic/statistics/compute_score_threshold.py:22: RuntimeWarning: divide by zero encountered in log
score = -log(required_p_value)
Traceback (most recent call last):
File "./epic", line 218, in
run_epic(args)
File "/home/anish/.local/lib/python2.7/site-packages/epic/run/run_epic.py", line 47, in run_epic
compute_background_probabilities(nb_chip_reads, args)
File "/home/anish/.local/lib/python2.7/site-packages/epic/statistics/compute_background_probabilites.py", line 49, in compute_background_probabilities
boundary_contribution, genome_length_in_bins)
File "/home/anish/.local/lib/python2.7/site-packages/epic/statistics/compute_score_threshold.py", line 24, in compute_score_threshold
current_scaled_score = int(round(score / BIN_SIZE))
OverflowError: cannot convert float infinity to integer

What does this mean? I know that there should be broad peaks as I find them running MACS2 broad-peak (no-model) option. Forgive me - I am new to these sorts of analyses.

Best,
Anish

[endrebak]

Thanks for reporting. It seems like epic cannot interpret your files. What do they look like?

Please post the output of

head <yourfiles> | cat -et

to this thread.

[anishdattani]

Hi,

Sorry for the late reply. The following was what I inputted into epic:

./epic --control /pathtofolder/lib.filtered.input.sorted_2_MARKDUP.bed --treatment /pathtofolder/lib.filtered.H3K27me3_2_new.sorted.MARKDUP.bed --number-cores 30 --fragment-size 300 --chromsizes /pathtofolder/Asxl.size.file --effective_genome_size 6e8 > /pathtohomefolder/h3k27.broad.csv

My input folder looks like this:

scaffold4^I1^I160^INB501801:1:HN3WLBGXY:4:11601:9830:10032^I159$
scaffold4^I1^I164^INB501801:1:HN3WLBGXY:3:13412:18598:13811^I163$
scaffold4^I1^I167^INB501801:1:HN3WLBGXY:3:22404:14294:20264^I166$
scaffold4^I15^I189^INB501801:1:HN3WLBGXY:2:23204:7996:11409^I174$
scaffold4^I1^I201^INB501801:1:HN3WLBGXY:3:21609:2881:5564^I200$
scaffold4^I46^I230^INB501801:1:HN3WLBGXY:4:23510:23247:4818^I184$
scaffold4^I67^I239^INB501801:1:HN3WLBGXY:4:11406:17309:7190^I172$
scaffold4^I80^I273^INB501801:1:HN3WLBGXY:4:21606:9304:15988^I193$
scaffold4^I76^I287^INB501801:1:HN3WLBGXY:1:22103:20705:12481^I211$
scaffold4^I95^I288^INB501801:1:HN3WLBGXY:3:23411:2064:14725^I193$

My treatment folder looks like this:

scaffold4^I1^I164^INB501801:1:HN3WLBGXY:3:13412:18598:13811^I163$
scaffold4^I1^I165^INB501801:1:HN3WLBGXY:4:12512:24813:1400^I164$
scaffold4^I9^I188^INB501801:1:HN3WLBGXY:3:23511:22654:9868^I179$
scaffold4^I15^I189^INB501801:1:HN3WLBGXY:2:23204:7996:11409^I174$
scaffold4^I1^I204^INB501801:1:HN3WLBGXY:4:21412:4710:15556^I203$
scaffold4^I55^I239^INB501801:1:HN3WLBGXY:4:11508:23962:14301^I184$
scaffold4^I42^I250^INB501801:1:HN3WLBGXY:3:21401:2738:10832^I208$
scaffold4^I76^I287^INB501801:1:HN3WLBGXY:1:22103:20705:12481^I211$
scaffold4^I91^I298^INB501801:1:HN3WLBGXY:3:12411:9664:14867^I207$
scaffold4^I87^I304^INB501801:1:HN3WLBGXY:2:21106:6046:15213^I217$

My chromsize folder:

scaffold4^I49623$
scaffold1^I75538$
scaffold2^I35872$
scaffold6^I61357$
scaffold3^I23435$
scaffold7^I107993$
scaffold10^I43946$
scaffold11^I23991$
scaffold8^I118074$
scaffold13^I28105$

I hope this helps. Thank you in advance.

Best,
Anish

[endrebak]

Effective genome size should be a number between 0 and 1.

You have no strand info in your files.

On Sat, Nov 5, 2016 at 12:20 PM, anishdattani [email protected]
wrote:

Hi,

Sorry for the late reply. The following was what I inputted into epic:

./epic --control /pathtofolder/lib.filtered.input.sorted_2_MARKDUP.bed
--treatment /pathtofolder/lib.filtered.H3K27me3_2_new.sorted.MARKDUP.bed
--number-cores 30 --fragment-size 300 --chromsizes
/pathtofolder/Asxl.size.file --effective_genome_size 6e8 >
/pathtohomefolder/h3k27.broad.csv

My input folder looks like this:

scaffold4^I1^I160^INB501801:1:HN3WLBGXY:4:11601:9830:10032^I159$
scaffold4^I1^I164^INB501801:1:HN3WLBGXY:3:13412:18598:13811^I163$
scaffold4^I1^I167^INB501801:1:HN3WLBGXY:3:22404:14294:20264^I166$
scaffold4^I15^I189^INB501801:1:HN3WLBGXY:2:23204:7996:11409^I174$
scaffold4^I1^I201^INB501801:1:HN3WLBGXY:3:21609:2881:5564^I200$
scaffold4^I46^I230^INB501801:1:HN3WLBGXY:4:23510:23247:4818^I184$
scaffold4^I67^I239^INB501801:1:HN3WLBGXY:4:11406:17309:7190^I172$
scaffold4^I80^I273^INB501801:1:HN3WLBGXY:4:21606:9304:15988^I193$
scaffold4^I76^I287^INB501801:1:HN3WLBGXY:1:22103:20705:12481^I211$
scaffold4^I95^I288^INB501801:1:HN3WLBGXY:3:23411:2064:14725^I193$

My treatment folder looks like this:

scaffold4^I1^I164^INB501801:1:HN3WLBGXY:3:13412:18598:13811^I163$
scaffold4^I1^I165^INB501801:1:HN3WLBGXY:4:12512:24813:1400^I164$
scaffold4^I9^I188^INB501801:1:HN3WLBGXY:3:23511:22654:9868^I179$
scaffold4^I15^I189^INB501801:1:HN3WLBGXY:2:23204:7996:11409^I174$
scaffold4^I1^I204^INB501801:1:HN3WLBGXY:4:21412:4710:15556^I203$
scaffold4^I55^I239^INB501801:1:HN3WLBGXY:4:11508:23962:14301^I184$
scaffold4^I42^I250^INB501801:1:HN3WLBGXY:3:21401:2738:10832^I208$
scaffold4^I76^I287^INB501801:1:HN3WLBGXY:1:22103:20705:12481^I211$
scaffold4^I91^I298^INB501801:1:HN3WLBGXY:3:12411:9664:14867^I207$
scaffold4^I87^I304^INB501801:1:HN3WLBGXY:2:21106:6046:15213^I217$

My chromsize folder:

scaffold4^I49623$
scaffold1^I75538$
scaffold2^I35872$
scaffold6^I61357$
scaffold3^I23435$
scaffold7^I107993$
scaffold10^I43946$
scaffold11^I23991$
scaffold8^I118074$
scaffold13^I28105$

I hope this helps. Thank you in advance.

Best,

Anish

—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
#45 (comment), or mute
the thread
https://github.com/notifications/unsubscribe-auth/AQ9I0nN8mE_fLgCVzVNXL6zX6hMGASOtks5q7GZ1gaJpZM4KpblD
.