<jupyter_start><jupyter_text>Spelling out results Running each of the dedup_basic, dedup_pos, dedup_gene and dedup_sc modules leads to three output files;1. {method}_ave_ed_pos_bin.txt2. {method}_dedup_sum.txt3. {name}_dedup.bam{method} is automatically named by uniq, cc, adj, direc, mcl, mcl_val, or mcl_ed.{name} can be designated by users.  {method}_ave_ed_pos_bin.txt -1.0	529781.0	22.0	73.0	364.0	3025.0	9976.0	28047.0	83728.0	310789.0	537410.0	892... the first column: average edit distance between UMIs at genomic positionsthe second column: the number of genomic positionsNote: 1. -1.0 stands for only one unique umi seen at a single genomic position; in total there are 3653 genomic positions seen with one unique umi.2. interpret the fifth row: the number of genomic positions observed with an average edit distance 4 between UMIs is 302.  {method}_dedup_sum.txt for single-cell data<jupyter_code>type	direc_umi_len	ave_eds	uniq_umi_len	dedup_uniq_diff_pos	dedup_read_diff_pos
('AAAGATGAGAAACGAG', 'exon-NM_000099.4-3')	6	8.0	6	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000100.4-3')	14	8.0	14	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000101.4-6')	3	8.0	3	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000146.4-3')	2	8.0	2	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000146.4-4')	44	8.0	44	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000156.6-6')	8	8.0	8	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000194.3-9')	3	8.0	3	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000232.5-6')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000270.4-6')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000291.4-11')	3	8.0	3	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000317.3-6')	2	8.0	2	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000363.5-7')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000386.4-12')	2	6.0	2	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000454.5-4')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000454.5-5')	19	8.0	19	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000455.5-10')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000485.3-5')	2	9.0	2	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000538.4-3')	2	8.0	2	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000599.4-1')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000613.3-3')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000613.3-4')	2	8.0	3	1	1
('AAAGATGAGAAACGAG', 'exon-NM_000713.3-4')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000713.3-5')	2	7.0	2	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000728.4-5')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000852.4-6')	2	7.0	2	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000852.4-7')	15	8.0	15	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000876.4-48')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000937.5-30')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000945.4-6')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000968.4-10')	43	8.0	43	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000976.4-1')	5	8.0	5	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000976.4-3')	1	-1.0	1	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000976.4-6')	8	8.0	8	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000978.4-3')	8	7.0	8	0	0
('AAAGATGAGAAACGAG', 'exon-NM_000978.4-4')	8	7.0	8	0	0<jupyter_output><empty_output>
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