It appears that it is possible though somewhat difficult to apply batch estimations generated by sva to the model given to DESeq/EdgeR/limma. In the case of limma it is fairly simple, but in the other two it is a bit more difficult. There is a nice discussion of this at: https://www.biostars.org/p/156186/ I am attempting to apply that logic to this data with limited success.
pa_de <- all_pairwise(input=pa_expt, model_batch=FALSE, limma_method="robust")## Assuming no batch in model for testing pca.## Finished running DE analyses, collecting outputs.## Comparing analyses 1/15: mt_st_vs_mt_ex## Comparing analyses 2/15: mt_undef_vs_mt_ex## Comparing analyses 3/15: wt_ex_vs_mt_ex## Comparing analyses 4/15: wt_st_vs_mt_ex## Comparing analyses 5/15: wt_undef_vs_mt_ex## Comparing analyses 6/15: mt_undef_vs_mt_st## Comparing analyses 7/15: wt_ex_vs_mt_st## Comparing analyses 8/15: wt_st_vs_mt_st## Comparing analyses 9/15: wt_undef_vs_mt_st## Comparing analyses 10/15: wt_ex_vs_mt_undef## Comparing analyses 11/15: wt_st_vs_mt_undef## Comparing analyses 12/15: wt_undef_vs_mt_undef## Comparing analyses 13/15: wt_st_vs_wt_ex## Comparing analyses 14/15: wt_undef_vs_wt_ex## Comparing analyses 15/15: wt_undef_vs_wt_stpa_tables <- combine_de_tables(pa_de,
excel=paste0("excel/pa_nobatch-v", ver, ".xlsx"))## Deleting the file excel/pa_nobatch-v20171019.xlsx before writing the tables.## Writing a legend of columns.## Printing a pca plot before/after surrogates/batch estimation.## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse## Working on table 1/15: mt_st_vs_mt_ex## Working on table 2/15: mt_undef_vs_mt_ex## Working on table 3/15: wt_ex_vs_mt_ex## Working on table 4/15: wt_st_vs_mt_ex## Working on table 5/15: wt_undef_vs_mt_ex## Working on table 6/15: mt_undef_vs_mt_st## Working on table 7/15: wt_ex_vs_mt_st## Working on table 8/15: wt_st_vs_mt_st## Working on table 9/15: wt_undef_vs_mt_st## Working on table 10/15: wt_ex_vs_mt_undef## Working on table 11/15: wt_st_vs_mt_undef## Working on table 12/15: wt_undef_vs_mt_undef## Working on table 13/15: wt_st_vs_wt_ex## Working on table 14/15: wt_undef_vs_wt_ex## Working on table 15/15: wt_undef_vs_wt_st## Adding venn plots for mt_st_vs_mt_ex.## Limma expression coefficients for mt_st_vs_mt_ex; R^2: 0.914; equation: y = 0.96x + 0.289## Edger expression coefficients for mt_st_vs_mt_ex; R^2: 0.911; equation: y = 1.07x - 0.561## DESeq2 expression coefficients for mt_st_vs_mt_ex; R^2: 0.909; equation: y = 1.08x - 0.615## Adding venn plots for mt_undef_vs_mt_ex.## Limma expression coefficients for mt_undef_vs_mt_ex; R^2: 0.914; equation: y = 0.951x + 0.248## Edger expression coefficients for mt_undef_vs_mt_ex; R^2: 0.92; equation: y = 1.08x - 0.667## DESeq2 expression coefficients for mt_undef_vs_mt_ex; R^2: 0.919; equation: y = 1.08x - 0.709## Adding venn plots for wt_ex_vs_mt_ex.## Limma expression coefficients for wt_ex_vs_mt_ex; R^2: 0.943; equation: y = 0.975x + 0.133## Edger expression coefficients for wt_ex_vs_mt_ex; R^2: 0.946; equation: y = 1.06x - 0.518## DESeq2 expression coefficients for wt_ex_vs_mt_ex; R^2: 0.944; equation: y = 1.07x - 0.565## Adding venn plots for wt_st_vs_mt_ex.## Limma expression coefficients for wt_st_vs_mt_ex; R^2: 0.649; equation: y = 0.817x + 1.02## Edger expression coefficients for wt_st_vs_mt_ex; R^2: 0.649; equation: y = 0.982x + 0.0713## DESeq2 expression coefficients for wt_st_vs_mt_ex; R^2: 0.638; equation: y = 0.981x + 0.0143## Adding venn plots for wt_undef_vs_mt_ex.## Limma expression coefficients for wt_undef_vs_mt_ex; R^2: 0.915; equation: y = 0.956x + 0.232## Edger expression coefficients for wt_undef_vs_mt_ex; R^2: 0.913; equation: y = 0.985x + 0.0641## DESeq2 expression coefficients for wt_undef_vs_mt_ex; R^2: 0.91; equation: y = 0.985x + 0.0338## Adding venn plots for mt_undef_vs_mt_st.## Limma expression coefficients for mt_undef_vs_mt_st; R^2: 0.842; equation: y = 0.912x + 0.363## Edger expression coefficients for mt_undef_vs_mt_st; R^2: 0.853; equation: y = 0.924x + 0.516## DESeq2 expression coefficients for mt_undef_vs_mt_st; R^2: 0.848; equation: y = 0.92x + 0.588## Adding venn plots for wt_ex_vs_mt_st.## Limma expression coefficients for wt_ex_vs_mt_st; R^2: 0.881; equation: y = 0.941x + 0.237## Edger expression coefficients for wt_ex_vs_mt_st; R^2: 0.887; equation: y = 0.923x + 0.569## DESeq2 expression coefficients for wt_ex_vs_mt_st; R^2: 0.882; equation: y = 0.919x + 0.633## Adding venn plots for wt_st_vs_mt_st.## Limma expression coefficients for wt_st_vs_mt_st; R^2: 0.796; equation: y = 0.903x + 0.55## Edger expression coefficients for wt_st_vs_mt_st; R^2: 0.795; equation: y = 0.968x + 0.23## DESeq2 expression coefficients for wt_st_vs_mt_st; R^2: 0.786; equation: y = 0.965x + 0.21## Adding venn plots for wt_undef_vs_mt_st.## Limma expression coefficients for wt_undef_vs_mt_st; R^2: 0.862; equation: y = 0.925x + 0.323## Edger expression coefficients for wt_undef_vs_mt_st; R^2: 0.863; equation: y = 0.851x + 1.12## DESeq2 expression coefficients for wt_undef_vs_mt_st; R^2: 0.859; equation: y = 0.846x + 1.19## Adding venn plots for wt_ex_vs_mt_undef.## Limma expression coefficients for wt_ex_vs_mt_undef; R^2: 0.882; equation: y = 0.946x + 0.26## Edger expression coefficients for wt_ex_vs_mt_undef; R^2: 0.899; equation: y = 0.93x + 0.56## DESeq2 expression coefficients for wt_ex_vs_mt_undef; R^2: 0.896; equation: y = 0.927x + 0.584## Adding venn plots for wt_st_vs_mt_undef.## Limma expression coefficients for wt_st_vs_mt_undef; R^2: 0.606; equation: y = 0.786x + 1.13## Edger expression coefficients for wt_st_vs_mt_undef; R^2: 0.619; equation: y = 0.85x + 1.14## DESeq2 expression coefficients for wt_st_vs_mt_undef; R^2: 0.604; equation: y = 0.842x + 1.17## Adding venn plots for wt_undef_vs_mt_undef.## Limma expression coefficients for wt_undef_vs_mt_undef; R^2: 0.947; equation: y = 0.97x + 0.152## Edger expression coefficients for wt_undef_vs_mt_undef; R^2: 0.952; equation: y = 0.889x + 0.875## DESeq2 expression coefficients for wt_undef_vs_mt_undef; R^2: 0.951; equation: y = 0.887x + 0.879## Adding venn plots for wt_st_vs_wt_ex.## Limma expression coefficients for wt_st_vs_wt_ex; R^2: 0.662; equation: y = 0.821x + 0.975## Edger expression coefficients for wt_st_vs_wt_ex; R^2: 0.679; equation: y = 0.909x + 0.664## DESeq2 expression coefficients for wt_st_vs_wt_ex; R^2: 0.666; equation: y = 0.903x + 0.667## Adding venn plots for wt_undef_vs_wt_ex.## Limma expression coefficients for wt_undef_vs_wt_ex; R^2: 0.925; equation: y = 0.955x + 0.263## Edger expression coefficients for wt_undef_vs_wt_ex; R^2: 0.929; equation: y = 0.906x + 0.723## DESeq2 expression coefficients for wt_undef_vs_wt_ex; R^2: 0.926; equation: y = 0.902x + 0.762## Adding venn plots for wt_undef_vs_wt_st.## Limma expression coefficients for wt_undef_vs_wt_st; R^2: 0.655; equation: y = 0.798x + 0.88## Edger expression coefficients for wt_undef_vs_wt_st; R^2: 0.644; equation: y = 0.672x + 2.47## DESeq2 expression coefficients for wt_undef_vs_wt_st; R^2: 0.638; equation: y = 0.666x + 2.65## Writing summary information.## Attempting to add the comparison plot to pairwise_summary at row: 33 and column: 1##
|
| | 0%
|
|==== | 7%
|
|========= | 13%
|
|============= | 20%
|
|================= | 27%
|
|====================== | 33%
|
|========================== | 40%
|
|============================== | 47%
|
|=================================== | 53%
|
|======================================= | 60%
|
|=========================================== | 67%
|
|================================================ | 73%
|
|==================================================== | 80%
|
|======================================================== | 87%
|
|============================================================= | 93%
|
|=================================================================| 100%## Performing save of the workbook.pa_sig <- extract_significant_genes(pa_tables,
excel=paste0("excel/pa_nobatch_significant-v", ver, ".xlsx"),
according_to="all")## Writing a legend of columns.## Writing excel data for mt_st_vs_mt_ex: 1/60.## After (adj)p filter, the up genes table has 1242 genes.## After (adj)p filter, the down genes table has 1720 genes.## After fold change filter, the up genes table has 571 genes.## After fold change filter, the down genes table has 507 genes.## Writing excel data for mt_undef_vs_mt_ex: 2/60.## After (adj)p filter, the up genes table has 1493 genes.## After (adj)p filter, the down genes table has 1494 genes.## After fold change filter, the up genes table has 438 genes.## After fold change filter, the down genes table has 597 genes.## Writing excel data for wt_ex_vs_mt_ex: 3/60.## After (adj)p filter, the up genes table has 1071 genes.## After (adj)p filter, the down genes table has 1085 genes.## After fold change filter, the up genes table has 329 genes.## After fold change filter, the down genes table has 409 genes.## Writing excel data for wt_st_vs_mt_ex: 4/60.## After (adj)p filter, the up genes table has 1860 genes.## After (adj)p filter, the down genes table has 2503 genes.## After fold change filter, the up genes table has 1279 genes.## After fold change filter, the down genes table has 1564 genes.## Writing excel data for wt_undef_vs_mt_ex: 5/60.## After (adj)p filter, the up genes table has 1404 genes.## After (adj)p filter, the down genes table has 1493 genes.## After fold change filter, the up genes table has 466 genes.## After fold change filter, the down genes table has 540 genes.## Writing excel data for mt_undef_vs_mt_st: 6/60.## After (adj)p filter, the up genes table has 1999 genes.## After (adj)p filter, the down genes table has 1699 genes.## After fold change filter, the up genes table has 938 genes.## After fold change filter, the down genes table has 914 genes.## Writing excel data for wt_ex_vs_mt_st: 7/60.## After (adj)p filter, the up genes table has 1794 genes.## After (adj)p filter, the down genes table has 1472 genes.## After fold change filter, the up genes table has 683 genes.## After fold change filter, the down genes table has 762 genes.## Writing excel data for wt_st_vs_mt_st: 8/60.## After (adj)p filter, the up genes table has 1696 genes.## After (adj)p filter, the down genes table has 2092 genes.## After fold change filter, the up genes table has 1002 genes.## After fold change filter, the down genes table has 1056 genes.## Writing excel data for wt_undef_vs_mt_st: 9/60.## After (adj)p filter, the up genes table has 1837 genes.## After (adj)p filter, the down genes table has 1633 genes.## After fold change filter, the up genes table has 826 genes.## After fold change filter, the down genes table has 798 genes.## Writing excel data for wt_ex_vs_mt_undef: 10/60.## After (adj)p filter, the up genes table has 1714 genes.## After (adj)p filter, the down genes table has 1710 genes.## After fold change filter, the up genes table has 720 genes.## After fold change filter, the down genes table has 726 genes.## Writing excel data for wt_st_vs_mt_undef: 11/60.## After (adj)p filter, the up genes table has 2032 genes.## After (adj)p filter, the down genes table has 2488 genes.## After fold change filter, the up genes table has 1381 genes.## After fold change filter, the down genes table has 1637 genes.## Writing excel data for wt_undef_vs_mt_undef: 12/60.## After (adj)p filter, the up genes table has 1204 genes.## After (adj)p filter, the down genes table has 1266 genes.## After fold change filter, the up genes table has 346 genes.## After fold change filter, the down genes table has 300 genes.## Writing excel data for wt_st_vs_wt_ex: 13/60.## After (adj)p filter, the up genes table has 1906 genes.## After (adj)p filter, the down genes table has 2509 genes.## After fold change filter, the up genes table has 1320 genes.## After fold change filter, the down genes table has 1562 genes.## Writing excel data for wt_undef_vs_wt_ex: 14/60.## After (adj)p filter, the up genes table has 1323 genes.## After (adj)p filter, the down genes table has 1497 genes.## After fold change filter, the up genes table has 514 genes.## After fold change filter, the down genes table has 484 genes.## Writing excel data for wt_undef_vs_wt_st: 15/60.## After (adj)p filter, the up genes table has 2502 genes.## After (adj)p filter, the down genes table has 1962 genes.## After fold change filter, the up genes table has 1534 genes.## After fold change filter, the down genes table has 1309 genes.## Printing significant genes to the file: excel/pa_nobatch_significant-v20171019.xlsx## 1/15: Creating significant table up_1limma_mt_st_vs_mt_ex## 2/15: Creating significant table up_2limma_mt_undef_vs_mt_ex## 3/15: Creating significant table up_3limma_wt_ex_vs_mt_ex## 4/15: Creating significant table up_4limma_wt_st_vs_mt_ex## 5/15: Creating significant table up_5limma_wt_undef_vs_mt_ex## 6/15: Creating significant table up_6limma_mt_undef_vs_mt_st## 7/15: Creating significant table up_7limma_wt_ex_vs_mt_st## 8/15: Creating significant table up_8limma_wt_st_vs_mt_st## 9/15: Creating significant table up_9limma_wt_undef_vs_mt_st## 10/15: Creating significant table up_10limma_wt_ex_vs_mt_undef## 11/15: Creating significant table up_11limma_wt_st_vs_mt_undef## 12/15: Creating significant table up_12limma_wt_undef_vs_mt_undef## The sheet name was too long for Excel, truncating it by removing vowels.## 13/15: Creating significant table up_13limma_wt_st_vs_wt_ex## 14/15: Creating significant table up_14limma_wt_undef_vs_wt_ex## 15/15: Creating significant table up_15limma_wt_undef_vs_wt_st## Writing excel data for mt_st_vs_mt_ex: 16/60.## After (adj)p filter, the up genes table has 931 genes.## After (adj)p filter, the down genes table has 969 genes.## After fold change filter, the up genes table has 728 genes.## After fold change filter, the down genes table has 512 genes.## Writing excel data for mt_undef_vs_mt_ex: 17/60.## After (adj)p filter, the up genes table has 1001 genes.## After (adj)p filter, the down genes table has 834 genes.## After fold change filter, the up genes table has 670 genes.## After fold change filter, the down genes table has 498 genes.## Writing excel data for wt_ex_vs_mt_ex: 18/60.## After (adj)p filter, the up genes table has 489 genes.## After (adj)p filter, the down genes table has 386 genes.## After fold change filter, the up genes table has 400 genes.## After fold change filter, the down genes table has 251 genes.## Writing excel data for wt_st_vs_mt_ex: 19/60.## After (adj)p filter, the up genes table has 1856 genes.## After (adj)p filter, the down genes table has 1816 genes.## After fold change filter, the up genes table has 1589 genes.## After fold change filter, the down genes table has 1392 genes.## Writing excel data for wt_undef_vs_mt_ex: 20/60.## After (adj)p filter, the up genes table has 922 genes.## After (adj)p filter, the down genes table has 867 genes.## After fold change filter, the up genes table has 611 genes.## After fold change filter, the down genes table has 530 genes.## Writing excel data for mt_undef_vs_mt_st: 21/60.## After (adj)p filter, the up genes table has 1275 genes.## After (adj)p filter, the down genes table has 1130 genes.## After fold change filter, the up genes table has 831 genes.## After fold change filter, the down genes table has 813 genes.## Writing excel data for wt_ex_vs_mt_st: 22/60.## After (adj)p filter, the up genes table has 835 genes.## After (adj)p filter, the down genes table has 945 genes.## After fold change filter, the up genes table has 537 genes.## After fold change filter, the down genes table has 691 genes.## Writing excel data for wt_st_vs_mt_st: 23/60.## After (adj)p filter, the up genes table has 1265 genes.## After (adj)p filter, the down genes table has 1310 genes.## After fold change filter, the up genes table has 1013 genes.## After fold change filter, the down genes table has 887 genes.## Writing excel data for wt_undef_vs_mt_st: 24/60.## After (adj)p filter, the up genes table has 1229 genes.## After (adj)p filter, the down genes table has 1241 genes.## After fold change filter, the up genes table has 812 genes.## After fold change filter, the down genes table has 864 genes.## Writing excel data for wt_ex_vs_mt_undef: 25/60.## After (adj)p filter, the up genes table has 842 genes.## After (adj)p filter, the down genes table has 988 genes.## After fold change filter, the up genes table has 508 genes.## After fold change filter, the down genes table has 646 genes.## Writing excel data for wt_st_vs_mt_undef: 26/60.## After (adj)p filter, the up genes table has 1747 genes.## After (adj)p filter, the down genes table has 1929 genes.## After fold change filter, the up genes table has 1354 genes.## After fold change filter, the down genes table has 1433 genes.## Writing excel data for wt_undef_vs_mt_undef: 27/60.## After (adj)p filter, the up genes table has 527 genes.## After (adj)p filter, the down genes table has 589 genes.## After fold change filter, the up genes table has 264 genes.## After fold change filter, the down genes table has 336 genes.## Writing excel data for wt_st_vs_wt_ex: 28/60.## After (adj)p filter, the up genes table has 1637 genes.## After (adj)p filter, the down genes table has 1728 genes.## After fold change filter, the up genes table has 1347 genes.## After fold change filter, the down genes table has 1230 genes.## Writing excel data for wt_undef_vs_wt_ex: 29/60.## After (adj)p filter, the up genes table has 650 genes.## After (adj)p filter, the down genes table has 658 genes.## After fold change filter, the up genes table has 414 genes.## After fold change filter, the down genes table has 435 genes.## Writing excel data for wt_undef_vs_wt_st: 30/60.## After (adj)p filter, the up genes table has 1904 genes.## After (adj)p filter, the down genes table has 1855 genes.## After fold change filter, the up genes table has 1417 genes.## After fold change filter, the down genes table has 1520 genes.## Printing significant genes to the file: excel/pa_nobatch_significant-v20171019.xlsx## 1/15: Creating significant table up_1edger_mt_st_vs_mt_ex## 2/15: Creating significant table up_2edger_mt_undef_vs_mt_ex## 3/15: Creating significant table up_3edger_wt_ex_vs_mt_ex## 4/15: Creating significant table up_4edger_wt_st_vs_mt_ex## 5/15: Creating significant table up_5edger_wt_undef_vs_mt_ex## 6/15: Creating significant table up_6edger_mt_undef_vs_mt_st## 7/15: Creating significant table up_7edger_wt_ex_vs_mt_st## 8/15: Creating significant table up_8edger_wt_st_vs_mt_st## 9/15: Creating significant table up_9edger_wt_undef_vs_mt_st## 10/15: Creating significant table up_10edger_wt_ex_vs_mt_undef## 11/15: Creating significant table up_11edger_wt_st_vs_mt_undef## 12/15: Creating significant table up_12edger_wt_undef_vs_mt_undef## The sheet name was too long for Excel, truncating it by removing vowels.## 13/15: Creating significant table up_13edger_wt_st_vs_wt_ex## 14/15: Creating significant table up_14edger_wt_undef_vs_wt_ex## 15/15: Creating significant table up_15edger_wt_undef_vs_wt_st## Writing excel data for mt_st_vs_mt_ex: 31/60.## After (adj)p filter, the up genes table has 963 genes.## After (adj)p filter, the down genes table has 1161 genes.## After fold change filter, the up genes table has 689 genes.## After fold change filter, the down genes table has 521 genes.## Writing excel data for mt_undef_vs_mt_ex: 32/60.## After (adj)p filter, the up genes table has 988 genes.## After (adj)p filter, the down genes table has 1018 genes.## After fold change filter, the up genes table has 588 genes.## After fold change filter, the down genes table has 525 genes.## Writing excel data for wt_ex_vs_mt_ex: 33/60.## After (adj)p filter, the up genes table has 533 genes.## After (adj)p filter, the down genes table has 522 genes.## After fold change filter, the up genes table has 376 genes.## After fold change filter, the down genes table has 262 genes.## Writing excel data for wt_st_vs_mt_ex: 34/60.## After (adj)p filter, the up genes table has 1934 genes.## After (adj)p filter, the down genes table has 1825 genes.## After fold change filter, the up genes table has 1619 genes.## After fold change filter, the down genes table has 1333 genes.## Writing excel data for wt_undef_vs_mt_ex: 35/60.## After (adj)p filter, the up genes table has 1049 genes.## After (adj)p filter, the down genes table has 945 genes.## After fold change filter, the up genes table has 605 genes.## After fold change filter, the down genes table has 507 genes.## Writing excel data for mt_undef_vs_mt_st: 36/60.## After (adj)p filter, the up genes table has 1314 genes.## After (adj)p filter, the down genes table has 1230 genes.## After fold change filter, the up genes table has 774 genes.## After fold change filter, the down genes table has 824 genes.## Writing excel data for wt_ex_vs_mt_st: 37/60.## After (adj)p filter, the up genes table has 959 genes.## After (adj)p filter, the down genes table has 1013 genes.## After fold change filter, the up genes table has 523 genes.## After fold change filter, the down genes table has 668 genes.## Writing excel data for wt_st_vs_mt_st: 38/60.## After (adj)p filter, the up genes table has 1391 genes.## After (adj)p filter, the down genes table has 1332 genes.## After fold change filter, the up genes table has 1061 genes.## After fold change filter, the down genes table has 815 genes.## Writing excel data for wt_undef_vs_mt_st: 39/60.## After (adj)p filter, the up genes table has 1392 genes.## After (adj)p filter, the down genes table has 1238 genes.## After fold change filter, the up genes table has 831 genes.## After fold change filter, the down genes table has 790 genes.## Writing excel data for wt_ex_vs_mt_undef: 40/60.## After (adj)p filter, the up genes table has 971 genes.## After (adj)p filter, the down genes table has 1034 genes.## After fold change filter, the up genes table has 523 genes.## After fold change filter, the down genes table has 584 genes.## Writing excel data for wt_st_vs_mt_undef: 41/60.## After (adj)p filter, the up genes table has 1854 genes.## After (adj)p filter, the down genes table has 1855 genes.## After fold change filter, the up genes table has 1443 genes.## After fold change filter, the down genes table has 1294 genes.## Writing excel data for wt_undef_vs_mt_undef: 42/60.## After (adj)p filter, the up genes table has 748 genes.## After (adj)p filter, the down genes table has 550 genes.## After fold change filter, the up genes table has 296 genes.## After fold change filter, the down genes table has 270 genes.## Writing excel data for wt_st_vs_wt_ex: 43/60.## After (adj)p filter, the up genes table has 1743 genes.## After (adj)p filter, the down genes table has 1710 genes.## After fold change filter, the up genes table has 1389 genes.## After fold change filter, the down genes table has 1138 genes.## Writing excel data for wt_undef_vs_wt_ex: 44/60.## After (adj)p filter, the up genes table has 825 genes.## After (adj)p filter, the down genes table has 669 genes.## After fold change filter, the up genes table has 433 genes.## After fold change filter, the down genes table has 384 genes.## Writing excel data for wt_undef_vs_wt_st: 45/60.## After (adj)p filter, the up genes table has 1954 genes.## After (adj)p filter, the down genes table has 1906 genes.## After fold change filter, the up genes table has 1372 genes.## After fold change filter, the down genes table has 1520 genes.## Printing significant genes to the file: excel/pa_nobatch_significant-v20171019.xlsx## 1/15: Creating significant table up_1deseq_mt_st_vs_mt_ex## 2/15: Creating significant table up_2deseq_mt_undef_vs_mt_ex## 3/15: Creating significant table up_3deseq_wt_ex_vs_mt_ex## 4/15: Creating significant table up_4deseq_wt_st_vs_mt_ex## 5/15: Creating significant table up_5deseq_wt_undef_vs_mt_ex## 6/15: Creating significant table up_6deseq_mt_undef_vs_mt_st## 7/15: Creating significant table up_7deseq_wt_ex_vs_mt_st## 8/15: Creating significant table up_8deseq_wt_st_vs_mt_st## 9/15: Creating significant table up_9deseq_wt_undef_vs_mt_st## 10/15: Creating significant table up_10deseq_wt_ex_vs_mt_undef## 11/15: Creating significant table up_11deseq_wt_st_vs_mt_undef## 12/15: Creating significant table up_12deseq_wt_undef_vs_mt_undef## The sheet name was too long for Excel, truncating it by removing vowels.## 13/15: Creating significant table up_13deseq_wt_st_vs_wt_ex## 14/15: Creating significant table up_14deseq_wt_undef_vs_wt_ex## 15/15: Creating significant table up_15deseq_wt_undef_vs_wt_st## Writing excel data for mt_st_vs_mt_ex: 46/60.## After (adj)p filter, the up genes table has 311 genes.## After (adj)p filter, the down genes table has 504 genes.## After fold change filter, the up genes table has 228 genes.## After fold change filter, the down genes table has 225 genes.## Writing excel data for mt_undef_vs_mt_ex: 47/60.## After (adj)p filter, the up genes table has 113 genes.## After (adj)p filter, the down genes table has 193 genes.## After fold change filter, the up genes table has 69 genes.## After fold change filter, the down genes table has 151 genes.## Writing excel data for wt_ex_vs_mt_ex: 48/60.## After (adj)p filter, the up genes table has 56 genes.## After (adj)p filter, the down genes table has 49 genes.## After fold change filter, the up genes table has 40 genes.## After fold change filter, the down genes table has 39 genes.## Writing excel data for wt_st_vs_mt_ex: 49/60.## After (adj)p filter, the up genes table has 1302 genes.## After (adj)p filter, the down genes table has 1866 genes.## After fold change filter, the up genes table has 1050 genes.## After fold change filter, the down genes table has 1349 genes.## Writing excel data for wt_undef_vs_mt_ex: 50/60.## After (adj)p filter, the up genes table has 358 genes.## After (adj)p filter, the down genes table has 411 genes.## After fold change filter, the up genes table has 221 genes.## After fold change filter, the down genes table has 266 genes.## Writing excel data for mt_undef_vs_mt_st: 51/60.## After (adj)p filter, the up genes table has 875 genes.## After (adj)p filter, the down genes table has 808 genes.## After fold change filter, the up genes table has 586 genes.## After fold change filter, the down genes table has 610 genes.## Writing excel data for wt_ex_vs_mt_st: 52/60.## After (adj)p filter, the up genes table has 289 genes.## After (adj)p filter, the down genes table has 197 genes.## After fold change filter, the up genes table has 197 genes.## After fold change filter, the down genes table has 164 genes.## Writing excel data for wt_st_vs_mt_st: 53/60.## After (adj)p filter, the up genes table has 1186 genes.## After (adj)p filter, the down genes table has 1330 genes.## After fold change filter, the up genes table has 855 genes.## After fold change filter, the down genes table has 855 genes.## Writing excel data for wt_undef_vs_mt_st: 54/60.## After (adj)p filter, the up genes table has 872 genes.## After (adj)p filter, the down genes table has 748 genes.## After fold change filter, the up genes table has 567 genes.## After fold change filter, the down genes table has 504 genes.## Writing excel data for wt_ex_vs_mt_undef: 55/60.## After (adj)p filter, the up genes table has 159 genes.## After (adj)p filter, the down genes table has 89 genes.## After fold change filter, the up genes table has 125 genes.## After fold change filter, the down genes table has 61 genes.## Writing excel data for wt_st_vs_mt_undef: 56/60.## After (adj)p filter, the up genes table has 1545 genes.## After (adj)p filter, the down genes table has 1874 genes.## After fold change filter, the up genes table has 1239 genes.## After fold change filter, the down genes table has 1467 genes.## Writing excel data for wt_undef_vs_mt_undef: 57/60.## After (adj)p filter, the up genes table has 2 genes.## After (adj)p filter, the down genes table has 10 genes.## After fold change filter, the up genes table has 2 genes.## After fold change filter, the down genes table has 9 genes.## Writing excel data for wt_st_vs_wt_ex: 58/60.## After (adj)p filter, the up genes table has 1092 genes.## After (adj)p filter, the down genes table has 1542 genes.## After fold change filter, the up genes table has 927 genes.## After fold change filter, the down genes table has 1204 genes.## Writing excel data for wt_undef_vs_wt_ex: 59/60.## After (adj)p filter, the up genes table has 8 genes.## After (adj)p filter, the down genes table has 7 genes.## After fold change filter, the up genes table has 7 genes.## After fold change filter, the down genes table has 5 genes.## Writing excel data for wt_undef_vs_wt_st: 60/60.## After (adj)p filter, the up genes table has 1823 genes.## After (adj)p filter, the down genes table has 1510 genes.## After fold change filter, the up genes table has 1336 genes.## After fold change filter, the down genes table has 1181 genes.## Printing significant genes to the file: excel/pa_nobatch_significant-v20171019.xlsx## 1/15: Creating significant table up_1basic_mt_st_vs_mt_ex## 2/15: Creating significant table up_2basic_mt_undef_vs_mt_ex## 3/15: Creating significant table up_3basic_wt_ex_vs_mt_ex## 4/15: Creating significant table up_4basic_wt_st_vs_mt_ex## 5/15: Creating significant table up_5basic_wt_undef_vs_mt_ex## 6/15: Creating significant table up_6basic_mt_undef_vs_mt_st## 7/15: Creating significant table up_7basic_wt_ex_vs_mt_st## 8/15: Creating significant table up_8basic_wt_st_vs_mt_st## 9/15: Creating significant table up_9basic_wt_undef_vs_mt_st## 10/15: Creating significant table up_10basic_wt_ex_vs_mt_undef## 11/15: Creating significant table up_11basic_wt_st_vs_mt_undef## 12/15: Creating significant table up_12basic_wt_undef_vs_mt_undef## The sheet name was too long for Excel, truncating it by removing vowels.## 13/15: Creating significant table up_13basic_wt_st_vs_wt_ex## 14/15: Creating significant table up_14basic_wt_undef_vs_wt_ex## 15/15: Creating significant table up_15basic_wt_undef_vs_wt_st## Adding significance bar plots.pander::pander(sessionInfo())R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
locale: LC_CTYPE=en_US.utf8, LC_NUMERIC=C, LC_TIME=en_US.utf8, LC_COLLATE=en_US.utf8, LC_MONETARY=en_US.utf8, LC_MESSAGES=en_US.utf8, LC_PAPER=en_US.utf8, LC_NAME=C, LC_ADDRESS=C, LC_TELEPHONE=C, LC_MEASUREMENT=en_US.utf8 and LC_IDENTIFICATION=C
attached base packages: stats, graphics, grDevices, utils, datasets, methods and base
other attached packages: foreach(v.1.4.4), Vennerable(v.3.1.0.9000) and hpgltools(v.2018.03)
loaded via a namespace (and not attached): colorspace(v.1.3-2), rprojroot(v.1.3-2), htmlTable(v.1.12), corpcor(v.1.6.9), XVector(v.0.20.0), GenomicRanges(v.1.32.4), base64enc(v.0.1-3), rstudioapi(v.0.7), roxygen2(v.6.0.1), ggrepel(v.0.8.0), bit64(v.0.9-7), AnnotationDbi(v.1.42.1), xml2(v.1.2.0), codetools(v.0.2-15), splines(v.3.5.1), doParallel(v.1.0.11), robustbase(v.0.93-1.1), geneplotter(v.1.58.0), knitr(v.1.20), Formula(v.1.2-3), Rsamtools(v.1.32.2), annotate(v.1.58.0), cluster(v.2.0.7-1), graph(v.1.58.0), compiler(v.3.5.1), httr(v.1.3.1), backports(v.1.1.2), assertthat(v.0.2.0), Matrix(v.1.2-14), lazyeval(v.0.2.1), limma(v.3.36.2), acepack(v.1.4.1), htmltools(v.0.3.6), prettyunits(v.1.0.2), tools(v.3.5.1), bindrcpp(v.0.2.2), gtable(v.0.2.0), glue(v.1.3.0), GenomeInfoDbData(v.1.1.0), reshape2(v.1.4.3), dplyr(v.0.7.6), Rcpp(v.0.12.17), Biobase(v.2.40.0), Biostrings(v.2.48.0), preprocessCore(v.1.42.0), rtracklayer(v.1.40.3), iterators(v.1.0.10), stringr(v.1.3.1), openxlsx(v.4.1.0), gtools(v.3.8.1), devtools(v.1.13.6), XML(v.3.98-1.12), edgeR(v.3.22.3), DEoptimR(v.1.0-8), directlabels(v.2018.05.22), zlibbioc(v.1.26.0), MASS(v.7.3-50), scales(v.0.5.0), doSNOW(v.1.0.16), hms(v.0.4.2), RBGL(v.1.56.0), parallel(v.3.5.1), SummarizedExperiment(v.1.10.1), RColorBrewer(v.1.1-2), yaml(v.2.1.19), memoise(v.1.1.0), gridExtra(v.2.3), pander(v.0.6.2), ggplot2(v.3.0.0), biomaRt(v.2.36.1), rpart(v.4.1-13), latticeExtra(v.0.6-28), stringi(v.1.2.3), RSQLite(v.2.1.1), genefilter(v.1.62.0), S4Vectors(v.0.18.3), checkmate(v.1.8.5), GenomicFeatures(v.1.32.0), BiocGenerics(v.0.26.0), zip(v.1.0.0), BiocParallel(v.1.14.2), GenomeInfoDb(v.1.16.0), rlang(v.0.2.1), pkgconfig(v.2.0.1), commonmark(v.1.5), matrixStats(v.0.53.1), bitops(v.1.0-6), evaluate(v.0.11), lattice(v.0.20-35), purrr(v.0.2.5), bindr(v.0.1.1), labeling(v.0.3), GenomicAlignments(v.1.16.0), htmlwidgets(v.1.2), bit(v.1.1-14), tidyselect(v.0.2.4), plyr(v.1.8.4), magrittr(v.1.5), DESeq2(v.1.20.0), R6(v.2.2.2), snow(v.0.4-2), IRanges(v.2.14.10), Hmisc(v.4.1-1), DelayedArray(v.0.6.1), DBI(v.1.0.0), pillar(v.1.3.0), foreign(v.0.8-70), withr(v.2.1.2), survival(v.2.42-6), RCurl(v.1.95-4.11), nnet(v.7.3-12), tibble(v.1.4.2), crayon(v.1.3.4), rmarkdown(v.1.10), progress(v.1.2.0), locfit(v.1.5-9.1), grid(v.3.5.1), data.table(v.1.11.4), blob(v.1.1.1), digest(v.0.6.15), xtable(v.1.8-2), stats4(v.3.5.1), munsell(v.0.5.0) and quadprog(v.1.5-5)
message(paste0("This is hpgltools commit: ", get_git_commit()))## If you wish to reproduce this exact build of hpgltools, invoke the following:## > git clone http://github.com/abelew/hpgltools.git## > git reset c730ef178f8e57bbf3819e21cf5e6cfe879e6328## R> packrat::restore()## This is hpgltools commit: Fri Jul 13 17:21:39 2018 -0400: c730ef178f8e57bbf3819e21cf5e6cfe879e6328this_save <- paste0(gsub(pattern="\\.Rmd", replace="", x=rmd_file), "-v", ver, ".rda.xz")
message(paste0("Saving to ", this_save))## Saving to 03_differential_expression_all-v20171019.rda.xztmp <- sm(saveme(filename=this_save))