Closed baozg closed 1 year ago
This is possible from coverage histogram data, i.e, the output of panacus hist ...
, but requires you to manually merge the chromosome data together. This is simple, because they're just tables, and here is one way to do that with python/pandas:
import pandas as pd
FILES=['/your/list/of/chromosomes/chr1.hist.txt', '/your/list/of/chromosomes/chr2.hist.txt', ]
df = None
for f in FILES:
_df = pd.read_csv(f, sep='\t', header=[1], index_col=[0])
if df is None:
df = _df
else:
df += _df
with open('/your/output/file.hist.txt', 'w') as out:
df.reset_index().to_csv(out, sep='\t', index=False)
Then pass the output file to panacus, i.e., panacus growth /your/output/file.hist.txt
and you're good to go.
After panacus hist
and panacus growth
, the final visualization will show #nodes
instead of bps
. I use -c bp
for hist
Right, this is a known bug that I need to fix at some point. For the record, it’s just the label that is wrong (good that put this in the ticket here)On 8. Aug 2023, at 22:03, Zhigui Bao @.***> wrote: After panacus hist and panacus growth, the final visualization will show #nodes instead of bps. I use -c bp for hist
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Hi,
How do we merge stats from all chromosomes into a single plot?
Best regards Zhigui