notes: gdb, mmseqs2, metat cov (issue #121)

notes/gdb_mmseqs2_uniq_metat.md

+Notes for genes identified as "unique" using `mmseqs2` clustering results.
+
+```python
+# Per assembly, compute the total number of unique genes,
+# and number and percentage of unique genes with ave. metaT coverage
+# of at least 10x.
+
+import pandas
+df = pandas.read_csv("/scratch/users/vgalata/gdb/results/report/mmseqs2_uniq.tsv", sep="\t", header=0)
+for gr_value, gr_df in df.groupby(axis=0, by=["tool"]): # group by assembly/tool
+    total = gr_df.shape[0]
+    count = sum(gr_df["ave_cov"] >= 10) # ave. metaT coverage >= 10x
+    pct   = 100 * count / total
+    print("%s: %d, %d, %.2f" % (gr_value, total, count, pct))
+
+# flye: 51750, 6520, 12.60
+# megahit: 16693, 1657, 9.93
+# metaspades: 13878, 1141, 8.22
+# metaspadeshybrid: 27181, 1946, 7.16
+# operamsmegahit: 15624, 1452, 9.29
+# operamsmetaspades: 14840, 1193, 8.04
+# raven: 35144, 5519, 15.70
+```
\ No newline at end of file