MethCompare Part 8
Characterizing CpGs in 5x data
After confirming last week that mapping to a pan-genome wasn’t changing our output, I went ahead with the CpG characterization pipeline. We decided to move ahead with 5x data with the option to return to 10x data later. I decided to create a new Jupyter notebook for running 5x data through the pipeline.
Repo fiasco
Turns out we haven’t mastered how to have five people working on a repo simultaneously without having pull-and-push issues. When Sam reverted to an old repo version, I lost the checksum code I worked on earlier. The first thing I did was add the code back in to my 10x Jupyter notebook and to the new notebook I created for 5x data. This isn’t the first time a repo commit from someone else lost some of my code, so hopefully we figure out!
M. capitata
Using 5x files provided more CpG data to characterize, but the percentages of methylated CpGs total and in various genome features were mostly consistent between 5x and 10x data.
Table 1. Methylated, sparsely methylated, and unmethylated CpGs in M. capitata
| Sample | Method | CpG with Data | Methylated CpG | Sparsely Methylated CpG | Unmethylated CpG |
|---|---|---|---|---|---|
| 10 | WGBS | 4571288 | 450582 (9.9%) | 547868 (12.0%) | 3572838 (78.2%) |
| 11 | WGBS | 4661716 | 528902 (11.3%) | 517805 (11.1%) | 3615009 (77.5%) |
| 12 | WGBS | 8791700 | 1059904 (12.1%) | 1000337 (11.4%) | 6731459 (76.6%) |
| 13 | RRBS | 3173254 | 257741 (8.1%) | 152042 (4.8%) | 2763471 (87.1%) |
| 14 | RRBS | 2648697 | 184742 (7.0%) | 135052 (5.1%) | 2328903 (87.9%) |
| 15 | RRBS | 3176517 | 231347 (7.3%) | 179454 (5.6%) | 2765716 (87.1%) |
| 16 | MBD-BSSeq | 583599 | 106695 (18.3%) | 74839 (12.8%) | 402065 (68.9%) |
| 17 | MBD-BSSeq | 242390 | 45506 (18.8%) | 28850 (11.9%) | 168034 (69.3%) |
| 18 | MBD-BSSeq | 153392 | 29468 (19.2%) | 16793 (10.9%) | 107131 (69.8%) |
Table 2. Number and percent of CpGs that overlap with genes in M. capitata.
| Sample | Method | CpGs with Data | Methylated CpGs | Sparsely Methylated CpGs | Unmethylated CpGs |
|---|---|---|---|---|---|
| 10 | WGBS | 1683069 | 230343 (13.7%) | 196827 (11.7%) | 1255899 (74.6%) |
| 11 | WGBS | 1740149 | 267181 (15.3%) | 188348 (10.8%) | 1284620 (73.8%) |
| 12 | WGBS | 3204885 | 533230 (16.6%) | 348967 (10.9%) | 2322688 (72.5%) |
| 13 | RRBS | 1062577 | 123271 (11.6%) | 53235 (5.0%) | 886071 (83.4%) |
| 14 | RRBS | 895852 | 89865 (10.0%) | 48499 (5.4%) | 757488 (84.6%) |
| 15 | RRBS | 1064769 | 113217 (10.6%) | 64106 (6.0%) | 887446 (83.3%) |
| 16 | MBD-BSSeq | 208503 | 48436 (23.2%) | 25316 (12.1%) | 134751 (64.6%) |
| 17 | MBD-BSSeq | 83519 | 20458 (24.5%) | 9441 (11.3%) | 53620 (64.2%) |
| 18 | MBD-BSSeq | 50302 | 12960 (25.8%) | 4843 (9.6%) | 32499 (64.6%) |
Table 3. Number and percent of CpGs that overlap with CDS in M. capitata.
| Sample | Method | CpGs with Data | Methylated CpGs | Sparsely Methylated CpGs | Unmethylated CpGs |
|---|---|---|---|---|---|
| 10 | WGBS | 476579 | 54412 (11.4%) | 60266 (12.6%) | 361901 (75.9%) |
| 11 | WGBS | 496887 | 64070 (12.9%) | 58258 (11.7%) | 374559 (75.4%) |
| 12 | WGBS | 791965 | 113396 (14.3%) | 89455 (11.3%) | 589114 (74.4%) |
| 13 | RRBS | 200808 | 18158 (9.0%) | 11383 (5.7%) | 171267 (85.3%) |
| 14 | RRBS | 172313 | 12833 (7.4%) | 10486 (6.1%) | 148994 (86.5%) |
| 15 | RRBS | 203147 | 15130 (7.4%) | 14015 (6.9%) | 174002 (85.7%) |
| 16 | MBD-BSSeq | 72490 | 13535 (18.7%) | 9666 (13.3%) | 49289 (68.0%) |
| 17 | MBD-BSSeq | 29305 | 5649 (19.3%) | 3690 (12.6%) | 19966 (68.1%) |
| 18 | MBD-BSSeq | 17619 | 3992 (22.7%) | 1907 (10.8%) | 11720 (66.5%) |
Table 4. Number and percent of CpGs that overlap with introns in M. capitata.
| Sample | Method | CpGs with Data | Methylated CpGs | Sparsely Methylated CpGs | Unmethylated CpGs |
|---|---|---|---|---|---|
| 10 | WGBS | 1207609 | 176102 (14.6%) | 136671 (11.3%) | 894836 (74.1%) |
| 11 | WGBS | 1244403 | 203311 (16.3%) | 130195 (10.5%) | 910897 (73.2%) |
| 12 | WGBS | 2415036 | 420249 (17.4%) | 259702 (10.8%) | 1735085 (71.8%) |
| 13 | RRBS | 862191 | 105145 (12.2%) | 41866 (4.9%) | 715180 (82.9%) |
| 14 | RRBS | 723933 | 77053 (10.6%) | 38032 (5.3%) | 608848 (84.1%) |
| 15 | RRBS | 862091 | 98111 (11.4%) | 50116 (5.8%) | 713864 (82.8%) |
| 16 | MBD-BSSeq | 136153 | 34929 (25.7%) | 15666 (11.5%) | 85558 (62.8%) |
| 17 | MBD-BSSeq | 54275 | 14821 (27.3%) | 5755 (10.6%) | 33699 (62.1%) |
| 18 | MBD-BSSeq | 32717 | 8973 (27.4%) | 2942 (9.0%) | 20802 (63.6%) |
Table 5. Number and percent of CpGs that overlap with intergenic regions in M. capitata.
| Sample | Method | CpGs with Data | Methylated CpGs | Sparsely Methylated CpGs | Unmethylated CpGs |
|---|---|---|---|---|---|
| 10 | WGBS | 2888219 | 220239 (7.6%) | 351041 (12.2%) | 2316939 (80.2%) |
| 11 | WGBS | 2921567 | 261721 (9.0%) | 329457 (11.3%) | 2330389 (79.8%) |
| 12 | WGBS | 5586815 | 526674 (9.4%) | 651370 (11.7%) | 4408771 (78.9%) |
| 13 | RRBS | 2110677 | 134470 (6.4%) | 98807 (4.7%) | 1877400 (88.9%) |
| 14 | RRBS | 1752845 | 94877 (5.4%) | 86553 (4.9%) | 1571415 (89.6%) |
| 15 | RRBS | 2111748 | 118130 (5.6%) | 115348 (5.5%) | 1878270 (88.9%) |
| 16 | MBD-BSSeq | 375096 | 58259 (15.5%) | 49523 (13.2%) | 267314 (71.3%) |
| 17 | MBD-BSSeq | 158871 | 25048 (15.8%) | 19409 (12.2%) | 114414 (72.0%) |
| 18 | MBD-BSSeq | 103090 | 16508 (16.0%) | 11950 (11.6%) | 74632 (72.4%) |
P. acuta
Table 6. Methylated, sparsely methylated, and unmethylated CpGs in P. acuta
| Sample | Method | CpG with Data | Methylated CpG | Sparsely Methylated CpG | Unmethylated CpG |
|---|---|---|---|---|---|
| 1 | WGBS | 5546051 | 110364 (2.0%) | 367019 (6.6%) | 5068668 (91.4%) |
| 2 | WGBS | 6358722 | 126440 (2.0%) | 345887 (5.4%) | 5886395 (92.6%) |
| 3 | WGBS | 5866786 | 124819 (2.1%) | 385346 (6.6%) | 5356621 (91.3%) |
| 4 | RRBS | 1835561 | 31047 (1.7%) | 137700 (7.5%) | 1666814 (90.8%) |
| 5 | RRBS | 1451229 | 30345 (2.1%) | 64837 (4.5%) | 1356047 (93.4%) |
| 6 | RRBS | 1517358 | 26617 (1.8%) | 89246 (5.9%) | 1401495 (92.4%) |
| 7 | MBD-BSSeq | 2640625 | 258222 (9.8%) | 296059 (11.2%) | 2086344 (79.0%) |
| 8 | MBD-BSSeq | 539008 | 213342 (39.6%) | 80086 (14.9%) | 245580 (45.6%) |
| 9 | MBD-BSSeq | 2732607 | 255370 (9.3%) | 337855 (12.4%) | 2139382 (78.3%) |
Table 7. Number and percent of CpGs that overlap with genes in P. acuta.
| Sample | Method | CpG with Data | Methylated CpG | Sparsely Methylated CpG | Unmethylated CpG |
|---|---|---|---|---|---|
| 1 | WGBS | 2466992 | 73959 (3.0%) | 157337 (6.4%) | 2235696 (90.6%) |
| 2 | WGBS | 2761956 | 85861 (3.1%) | 144292 (5.2%) | 2531803 (91.7%) |
| 3 | WGBS | 2588278 | 82377 (3.2%) | 161791 (6.3%) | 2344110 (90.6%) |
| 4 | RRBS | 776123 | 13588 (1.8%) | 56290 (7.3%) | 706245 (91.0%) |
| 5 | RRBS | 607225 | 12789 (2.1%) | 25954 (4.3%) | 568482 (93.6%) |
| 6 | RRBS | 639570 | 11396 (1.8%) | 35633 (5.6%) | 592541 (92.6%) |
| 7 | MBD-BSSeq | 1253805 | 118291 (9.4%) | 120485 (9.6%) | 1015029 (81.0%) |
| 8 | MBD-BSSeq | 220096 | 86074 (39.1%) | 27902 (12.7%) | 106120 (48.2%) |
| 9 | MBD-BSSeq | 1281644 | 125536 (9.8%) | 139034 (10.8%) | 1017074 (79.4%) |
Table 8. Number and percent of CpGs that overlap with CDS in P. acuta.
| Sample | Method | CpG with Data | Methylated CpG | Sparsely Methylated CpG | Unmethylated CpG |
|---|---|---|---|---|---|
| 1 | WGBS | 1494340 | 59188 (4.0%) | 89863 (6.0%) | 1345289 (90.0%) |
| 2 | WGBS | 1620632 | 66365 (4.1%) | 76868 (4.7%) | 1477399 (91.2%) |
| 3 | WGBS | 1552715 | 65245 (4.2%) | 89654 (5.8%) | 1397816 (90.0%) |
| 4 | RRBS | 500779 | 9644 (1.9%) | 36616 (7.3%) | 454519 (90.8%) |
| 5 | RRBS | 395869 | 8808 (2.2%) | 17345 (4.4%) | 369716 (93.4%) |
| 6 | RRBS | 415529 | 7954 (1.9%) | 23679 (5.7%) | 383896 (92.4%) |
| 7 | MBD-BSSeq | 931250 | 92559 (9.9%) | 87369 (9.4%) | 751322 (80.7%) |
| 8 | MBD-BSSeq | 184606 | 70696 (38.3%) | 21973 (11.9%) | 91937 (49.8%) |
| 9 | MBD-BSSeq | 924825 | 95614 (10.3%) | 98699 (10.7%) | 730512 (79.0%) |
Table 9. Number and percent of CpGs that overlap with introns in P. acuta.
| Sample | Method | CpG with Data | Methylated CpG | Sparsely Methylated CpG | Unmethylated CpG |
|---|---|---|---|---|---|
| 1 | WGBS | 1840138 | 41787 (2.3%) | 122271 (6.6%) | 1676080 (91.1%) |
| 2 | WGBS | 2113295 | 51567 (2.4%) | 117738 (5.6%) | 1943990 (92.0%) |
| 3 | WGBS | 1946150 | 47352 (2.4%) | 128122 (6.6%) | 1770676 (91.0%) |
| 4 | RRBS | 539524 | 8446 (1.6%) | 38589 (7.2%) | 492489 (91.3%) |
| 5 | RRBS | 414147 | 8375 (2.0%) | 17239 (4.2%) | 388533 (93.8%) |
| 6 | RRBS | 439844 | 7162 (1.6%) | 23825 (5.4%) | 408857 (93.0%) |
| 7 | MBD-BSSeq | 746710 | 64572 (8.6%) | 71046 (9.5%) | 611092 (81.8%) |
| 8 | MBD-BSSeq | 101087 | 42068 (41.6%) | 13365 (13.2%) | 45654 (45.2%) |
| 9 | MBD-BSSeq | 794295 | 72530 (9.1%) | 85117 (10.7%) | 636648 (80.2%) |
Table 10. Number and percent of CpGs that overlap with intergenic regions in P. acuta.
| Sample | Method | CpG with Data | Methylated CpG | Sparsely Methylated CpG | Unmethylated CpG |
|---|---|---|---|---|---|
| 1 | WGBS | 3080835 | 3080835 (1.2%) | 209781 (6.8%) | 2834593 (92.0%) |
| 2 | WGBS | 3598848 | 40642 (1.1%) | 201712 (5.6%) | 3356494 (93.3%) |
| 3 | WGBS | 3280357 | 42507 (1.3%) | 223666 (6.8%) | 3014184 (91.9%) |
| 4 | RRBS | 1060062 | 17473 (1.6%) | 81473 (7.7%) | 961116 (90.7%) |
| 5 | RRBS | 844509 | 17581 (2.1%) | 38900 (4.6%) | 788028 (93.3%) |
| 6 | RRBS | 878266 | 15232 (1.7%) | 53637 (6.1%) | 809397 (92.2%) |
| 7 | MBD-BSSeq | 1387623 | 140057 (10.1%) | 175668 (12.7%) | 1071898 (77.2%) |
| 8 | MBD-BSSeq | 319125 | 127376 (39.9%) | 52215 (16.4%) | 139534 (43.7%) |
| 9 | MBD-BSSeq | 1451853 | 129949 (9.0%) | 198940 (13.7%) | 1122964 (77.3%) |
Going forward
- Create figures for CpG characterization in various genome features
- Update code for methylation frequency distribution figure
- Generate repeat tracks for each species
- Find a way to generate tables programmatically
- Figure out how to meaningfully concatenate data for each method
- Figure out methylation island analysis