After getting Arthropoda
and Unassigned
reads extracted to FastA format (notebook entry) using MEGAN6 Community Edition, the next step was to use the FastA files to extract reads in FastQ format. I used seqtk
to do this. The process is documented in the Jupyter Notebook below.
Jupyter Notebook:
GitHub:
NB Viewer:
RESULTS
Output folder:
FastQ Files
20230730.mmag.CH01-06.trimmed.megan_R1.fq.gz (218M)
- MD5:
e6047623dc885392b3ae816f094552b4
- MD5:
20230730.mmag.CH01-06.trimmed.megan_R2.fq.gz (224M)
- MD5:
40b096dc26066a0d715d05e4bde36806
- MD5:
20230730.mmag.CH01-14.trimmed.megan_R1.fq.gz (405M)
- MD5:
401d6206dcd62c8b682536eef19ee4cc
- MD5:
20230730.mmag.CH01-14.trimmed.megan_R2.fq.gz (412M)
- MD5:
dcfe7a42861fa7406e1cc16522584045
- MD5:
20230730.mmag.CH01-22.trimmed.megan_R1.fq.gz (238M)
- MD5:
e9c1b9a7d3afb9bdd4beaff2c6ddb0fa
- MD5:
20230730.mmag.CH01-22.trimmed.megan_R2.fq.gz (242M)
- MD5:
7491813d90b50e08e3cefca8e1a1d7fc
- MD5:
20230730.mmag.CH01-38.trimmed.megan_R1.fq.gz (405M)
- MD5:
99bf9577b46bf2dfca8b8ac042e179ed
- MD5:
20230730.mmag.CH01-38.trimmed.megan_R2.fq.gz (410M)
- MD5:
4be920ddd78862fe25a46e66235faad4
- MD5:
20230730.mmag.CH03-04.trimmed.megan_R1.fq.gz (214M)
- MD5:
2f85cd2b10061b89011123d3bfa58d4f
- MD5:
20230730.mmag.CH03-04.trimmed.megan_R2.fq.gz (218M)
- MD5:
d220a8d18d8a67bfba19410879464f43
- MD5:
20230730.mmag.CH03-15.trimmed.megan_R1.fq.gz (260M)
- MD5:
a20b5ac49bdf3e17f18d0dbc1b60d6d2
- MD5:
20230730.mmag.CH03-15.trimmed.megan_R2.fq.gz (265M)
- MD5:
7cf21ab8f759a50183d31584aac1d1e3
- MD5:
20230730.mmag.CH03-33.trimmed.megan_R1.fq.gz (235M)
- MD5:
be8e50bf2c6747671ab4c2f2c3cbc5fd
- MD5:
20230730.mmag.CH03-33.trimmed.megan_R2.fq.gz (235M)
- MD5:
a5edfe0babb198adb29d1a19784f678b
- MD5:
20230730.mmag.CH05-01.trimmed.megan_R1.fq.gz (248M)
- MD5:
53ef62108920c3957954ac443418ca92
- MD5:
20230730.mmag.CH05-01.trimmed.megan_R2.fq.gz (254M)
- MD5:
0c22a7ca75b5c5adb646794115f112c7
- MD5:
20230730.mmag.CH05-06.trimmed.megan_R1.fq.gz (219M)
- MD5:
f5abf6a6f57473c7a8aed7b37472a4d2
- MD5:
20230730.mmag.CH05-06.trimmed.megan_R2.fq.gz (223M)
- MD5:
3f17e210323b66673b87682e18c65756
- MD5:
20230730.mmag.CH05-07.trimmed.megan_R1.fq.gz (241M)
- MD5:
3e3823bbf19ec39bca8d5544640a4211
- MD5:
20230730.mmag.CH05-07.trimmed.megan_R2.fq.gz (243M)
- MD5:
58189bc49bee52fa10aca82274657ce3
- MD5:
20230730.mmag.CH05-09.trimmed.megan_R1.fq.gz (335M)
- MD5:
c6900bf83ffbf843216fb67fce1c7df2
- MD5:
20230730.mmag.CH05-09.trimmed.megan_R2.fq.gz (339M)
- MD5:
02f9adfa7438fb42b4dca917aa4763fb
- MD5:
20230730.mmag.CH05-14.trimmed.megan_R1.fq.gz (336M)
- MD5:
fa31a570dc375a9fd2764b4723fad235
- MD5:
20230730.mmag.CH05-14.trimmed.megan_R2.fq.gz (341M)
- MD5:
99e636f1a2ebdd870d6f822901ceed61
- MD5:
20230730.mmag.CH05-21.trimmed.megan_R1.fq.gz (319M)
- MD5:
753d18733a2d9c041660d3b8c14c8f6e
- MD5:
20230730.mmag.CH05-21.trimmed.megan_R2.fq.gz (324M)
- MD5:
f5d38ef3d32b2e11a23ca6a46098b8e6
- MD5:
20230730.mmag.CH05-29.trimmed.megan_R1.fq.gz (350M)
- MD5:
383b33f41b1412d9dbf0dcc9457a305c
- MD5:
20230730.mmag.CH05-29.trimmed.megan_R2.fq.gz (360M)
- MD5:
9a910e7748d1aa92c8035df26c1cc42b
- MD5:
20230730.mmag.CH07-04.trimmed.megan_R1.fq.gz (193M)
- MD5:
370c7b651ff1cc7c1406123d831e7d64
- MD5:
20230730.mmag.CH07-04.trimmed.megan_R2.fq.gz (196M)
- MD5:
1574c16f21475c91aa21ae9f81426768
- MD5:
20230730.mmag.CH07-06.trimmed.megan_R1.fq.gz (262M)
- MD5:
9d44fc4c9f7a7c7df0125b6174613627
- MD5:
20230730.mmag.CH07-06.trimmed.megan_R2.fq.gz (265M)
- MD5:
ac41ebdd06208c728e1146839153b29e
- MD5:
20230730.mmag.CH07-08.trimmed.megan_R1.fq.gz (503M)
- MD5:
d8f891faeead968fa5b4fdb6a9c26d21
- MD5:
20230730.mmag.CH07-08.trimmed.megan_R2.fq.gz (513M)
- MD5:
98340e3ca008cf97fe240469b5c0f6f5
- MD5:
20230730.mmag.CH07-11.trimmed.megan_R1.fq.gz (349M)
- MD5:
8ffcad6e64dd7d1b12c1739767425ec1
- MD5:
20230730.mmag.CH07-11.trimmed.megan_R2.fq.gz (350M)
- MD5:
4b2673c0f02e48db0acbb847a4fb6dab
- MD5:
20230730.mmag.CH07-24.trimmed.megan_R1.fq.gz (378M)
- MD5:
cdd6d93b54fd40b135f4545474d9f837
- MD5:
20230730.mmag.CH07-24.trimmed.megan_R2.fq.gz (384M)
- MD5:
3229af42be57da29f13cad72f1f99523
- MD5:
20230730.mmag.CH09-02.trimmed.megan_R1.fq.gz (215M)
- MD5:
4328a6e6194fb6417dcc9cb61d3f0a72
- MD5:
20230730.mmag.CH09-02.trimmed.megan_R2.fq.gz (219M)
- MD5:
74c58ba1072a61ea3e75b83342589830
- MD5:
20230730.mmag.CH09-13.trimmed.megan_R1.fq.gz (263M)
- MD5:
a748a887a31a327d90bb80550c4e2e40
- MD5:
20230730.mmag.CH09-13.trimmed.megan_R2.fq.gz (265M)
- MD5:
7d81df73ba6dc5bbe3457bf973ede371
- MD5:
20230730.mmag.CH09-28.trimmed.megan_R1.fq.gz (191M)
- MD5:
67d2237f163289bc2b962e52c21562cc
- MD5:
20230730.mmag.CH09-28.trimmed.megan_R2.fq.gz (190M)
- MD5:
088a69aaf3371a0a6e16ab63e67146e2
- MD5:
20230730.mmag.CH10-08.trimmed.megan_R1.fq.gz (305M)
- MD5:
e61fb563e027256c0d45144bb3c89b78
- MD5:
20230730.mmag.CH10-08.trimmed.megan_R2.fq.gz (312M)
- MD5:
426403c8c8cb8275c84bdca3635b3186
- MD5:
20230730.mmag.CH10-11.trimmed.megan_R1.fq.gz (259M)
- MD5:
8e5dc9bc9d058b23cefec0e4d03f2cde
- MD5:
20230730.mmag.CH10-11.trimmed.megan_R2.fq.gz (260M)
- MD5:
e894988fd6467f8263f40e5946e3fe88
- MD5: