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Updated DGE on chr19 list
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@royfrancis
royfrancis committed Jan 6, 2025
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68 changes: 34 additions & 34 deletions topics/rnaseq/lab_rnaseq.qmd
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Expand Up @@ -1141,40 +1141,40 @@ For every file you open a number of panels are opened that visualise the data in
To see actual reads you have to zoom in until the reads are drawn on screen. If you have a gene of interest you can also use the search box to directly go to that gene.
Here is the list of top 30 differentially expressed genes on Chr19 ordered by absolute fold change. The adjusted p value is shown as padj, the average expression of the gene is shown as baseMean.
```
ensembl_gene_id external_gene_name baseMean log2FoldChange padj gene_biotype
1 ENSMUSG00000117896 AA387883 59.94083 -2.7846887 1.943690e-17 lncRNA
2 ENSMUSG00000024799 Tm7sf2 947.63388 -2.0385744 1.677171e-44 protein_coding
3 ENSMUSG00000025172 Ankrd2 59.28633 1.7519899 1.261004e-08 protein_coding
4 ENSMUSG00000049134 Nrap 220.59983 1.6993887 1.067822e-08 protein_coding
5 ENSMUSG00000024935 Slc1a1 63.82987 1.6821634 1.652208e-09 protein_coding
6 ENSMUSG00000037071 Scd1 6678.59981 -1.4473717 2.961722e-14 protein_coding
7 ENSMUSG00000024665 Fads2 3269.79425 -1.4152150 3.134559e-29 protein_coding
8 ENSMUSG00000024747 Aldh1a7 65.81205 -1.3544431 1.002599e-06 protein_coding
9 ENSMUSG00000025216 Lbx1 26.03640 1.3356124 1.328372e-04 protein_coding
10 ENSMUSG00000056290 Ms4a4b 23.27050 1.3299845 5.015617e-05 protein_coding
11 ENSMUSG00000025221 Kcnip2 34.13675 -1.3165310 1.463369e-04 protein_coding
12 ENSMUSG00000032648 Pygm 1129.47092 1.2452572 2.736196e-04 protein_coding
13 ENSMUSG00000043639 Rbm20 51.36261 1.1816554 7.774718e-04 protein_coding
14 ENSMUSG00000118032 Gm50147 39.53043 -1.1797580 3.794393e-04 lncRNA
15 ENSMUSG00000036278 Macrod1 244.02353 1.0824415 4.984802e-07 protein_coding
16 ENSMUSG00000025203 Scd2 44054.03491 -1.0504733 1.874759e-11 protein_coding
17 ENSMUSG00000010663 Fads1 4074.38868 -1.0503935 1.470460e-18 protein_coding
18 ENSMUSG00000060675 Plaat3 5284.36470 -1.0462725 2.114719e-13 protein_coding
19 ENSMUSG00000016496 Cd274 35.91671 1.0175443 5.632932e-03 protein_coding
20 ENSMUSG00000024673 Ms4a1 25.80723 1.0130356 6.294275e-03 protein_coding
21 ENSMUSG00000032773 Chrm1 76.11444 0.9262597 7.665519e-04 protein_coding
22 ENSMUSG00000067279 Ppp1r3c 162.14777 0.9018589 3.672613e-04 protein_coding
23 ENSMUSG00000025013 Tll2 108.20333 -0.9012959 1.249858e-03 protein_coding
24 ENSMUSG00000006457 Actn3 1322.01659 0.8988003 1.352229e-02 protein_coding
25 ENSMUSG00000075289 Carns1 1003.91026 -0.8819988 4.982949e-10 protein_coding
26 ENSMUSG00000075010 AW112010 56.94897 0.8128744 4.027595e-02 lncRNA
27 ENSMUSG00000025227 Mfsd13a 107.55434 -0.8126676 1.107050e-03 protein_coding
28 ENSMUSG00000067242 Lgi1 506.42577 -0.7842945 2.570293e-06 protein_coding
29 ENSMUSG00000024812 Tjp2 1478.96029 -0.7627251 9.004722e-07 protein_coding
30 ENSMUSG00000047368 Abhd17b 1562.07350 -0.7625545 5.750875e-07 protein_coding
Here is the list of top 20 differentially expressed genes on Chr19 ordered by absolute fold change. The adjusted p value is shown as padj, the average expression of the gene is shown as baseMean.
```{r}
#| eval: false
#| echo: false
readRDS("dge_r#| esults_full.rds") %>%
filter(chromosome_name == 19, padj < 0.05) %>%
arrange(-abs(log2FoldChange)) %>%
head(20) %>%
select(external_gene_name, baseMean, log2FoldChange, lfcSE, stat, pvalue, padj)
```
```
external_gene_name baseMean log2FoldChange lfcSE stat pvalue padj
1 AA387883 59.94083 -2.784689 0.2706306 -9.076824 1.117894e-19 1.943690e-17
2 Tm7sf2 947.63388 -2.038574 0.1399445 -14.539498 6.809003e-48 1.677171e-44
3 Ankrd2 59.28633 1.751990 0.2747018 6.323854 2.551188e-10 1.261004e-08
4 Nrap 220.59983 1.699389 0.2680529 6.352080 2.124228e-10 1.067822e-08
5 Slc1a1 63.82987 1.682163 0.2501657 6.651224 2.906652e-11 1.652208e-09
6 Scd1 6678.59981 -1.447372 0.1767165 -8.190325 2.605209e-16 2.961722e-14
7 Fads2 3269.79425 -1.415215 0.1201146 -11.779700 4.966970e-32 3.134559e-29
8 Aldh1a7 65.81205 -1.354443 0.2413361 -5.548387 2.883175e-08 1.002599e-06
9 Lbx1 26.03640 1.335612 0.2954499 4.503693 6.678261e-06 1.328372e-04
10 Ms4a4b 23.27050 1.329984 0.2927615 4.729255 2.253447e-06 5.015617e-05
11 Kcnip2 34.13675 -1.316531 0.2914951 -4.479672 7.475767e-06 1.463369e-04
12 Pygm 1129.47092 1.245257 0.2912826 4.323631 1.534817e-05 2.736196e-04
13 Rbm20 51.36261 1.181655 0.2927293 4.051754 5.083520e-05 7.774718e-04
14 Gm50147 39.53043 -1.179758 0.2754761 -4.239382 2.241359e-05 3.794393e-04
15 Macrod1 244.02353 1.082442 0.1904105 5.681007 1.339039e-08 4.984802e-07
16 Scd2 44054.03491 -1.050473 0.1434332 -7.323814 2.410205e-13 1.874759e-11
17 Fads1 4074.38868 -1.050393 0.1121926 -9.361514 7.860230e-21 1.470460e-18
18 Plaat3 5284.36470 -1.046273 0.1317594 -7.940261 2.017561e-15 2.114719e-13
19 Cd274 35.91671 1.017544 0.2938405 3.474263 5.122580e-04 5.632932e-03
20 Ms4a1 25.80723 1.013036 0.2949268 3.437803 5.864549e-04 6.294275e-03
```
Have a look at few of the interesting genes on Chr19 using the `external_gene_name` identifier. Look into gene **Tm7sf2** or **Ankrd2**. You might have to right-click and change option to **Squished** to see more reads.
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