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key error #255
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can you print first 5 row of your ranking ? make sure the first column is gene_symbol, the second column is ranking values |
This is how I calculate the rank: and ranking.head(5) yields: |
can you print out the full error message ? I don't know where the errors come from |
here is the entire error message:KeyError Traceback (most recent call last) File ~/miniconda3/lib/python3.9/site-packages/gseapy/init.py:396, in prerank(rnk, gene_sets, outdir, pheno_pos, pheno_neg, min_size, max_size, permutation_num, weight, ascending, threads, figsize, format, graph_num, no_plot, seed, verbose, *arg, **kwargs) File ~/miniconda3/lib/python3.9/site-packages/gseapy/gsea.py:444, in Prerank.run(self) File ~/miniconda3/lib/python3.9/site-packages/gseapy/gsea.py:418, in Prerank.load_ranking(self) File ~/miniconda3/lib/python3.9/site-packages/gseapy/gsea.py:385, in Prerank._load_ranking(self, rank_metric) File ~/miniconda3/lib/python3.9/site-packages/gseapy/base.py:246, in GSEAbase.make_unique(self, rank_metric, col_idx) File ~/miniconda3/lib/python3.9/site-packages/pandas/core/series.py:2238, in Series.groupby(self, by, axis, level, as_index, sort, group_keys, observed, dropna) File ~/miniconda3/lib/python3.9/site-packages/pandas/core/groupby/groupby.py:1329, in GroupBy.init(self, obj, keys, axis, level, grouper, exclusions, selection, as_index, sort, group_keys, observed, dropna) File ~/miniconda3/lib/python3.9/site-packages/pandas/core/groupby/grouper.py:1043, in get_grouper(obj, key, axis, level, sort, observed, validate, dropna) KeyError: 'gene_name' |
I think the issue is same to #251, can you install v1.1.2 and try again ? the error should be gone in the fixed version( v1.1.2) |
Setup
I am reporting a problem with GSEApy version, Python version, and operating
system as follows:
(Please copy and run the above in your Python, and copy-and-paste the output)
Expected behaviour
prerank
Actual behaviour
key error: "gene_name"
Steps to reproduce
pre_res = gp.prerank(rnk = ranking, gene_sets = 'GO_Biological_Process_2021', seed = 6, permutation_num = 100, min_size = 5 )
ranking is df with 2 columns.
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