Differential-transcript-expression
unawaz1996
2023-03-26
Last updated: 2023-05-10
Checks: 6 1
Knit directory: NMD-analysis/
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Things to do:
- QC plots and normalization
- Transcript level QC - DONE
- PCA - DONE
- BCV and other edgeR associated plots - DONE
- bigPint plot interpretations
- DET analysis - all data
- MA plots for all analyses - DONE
- Log fold change distribution - DONE
- Ratio of up/down
- Pvalue histograms - DONE
- NIF enrichment
- How many transcripts that are DE have multiple NIF features - DONE
- Is NIF enrichment in a given analysis significant - DONE
- Number of individual NIF in DET analysis - DONE
- Distribution of NIFs in DETs - DONE
- How many genes have multiple DETs, and how many of those have NIFs?
- Overlap of transcripts between UPF3B and UPPF3A and NIF distribution of those alignments? - DONE
- Overlap of UPF3B sig only transcripts with UPF3B and NIF distribution - DONE
- Overlap of UPF3A sig only transcripts with UPF3A and NIF distribution - DONE
- Overlap of UPF3B KD and UPF3A OE in UPF3B KD and NIF distribution? –> What is the logFC of overlapping transcripts?
- Overlap of UPF3B KD sig only transcripts in UPF3A OE in UPF3B KD and vice versa
Introduction
Set-up
Transcript-level counts were retrieved using the
catchSalmon() function from the edgeR package. Once
retrieved, the counts underwent rigourous QC.
Removal of outlier sample
According to the quality control analysis, it was revealed that one of the samples was not clustering with its condition group. Investigation into GC content, transcript length and library size revealed no contribution of these factors. To ensure we are getting results that are not skewed we will remove the sample from the transcript level analysis.
Principal component analysis of transcript level data. PCA was performed on log2 transformed CPM after filtering lowly expressed genes. The PCA shows that samples are clustering close to their conditions based on PC1, however one of the samples of the UPF3A OE in UPF3B KD cell line (sample 223), seems to deviate from its condition group and the rest of the data, so needs to be further investigated
Analysis
[1] 0.01177187
Biological coeficcient of variation plot against the average abundance of each transcript. The plot shows the square-root estimates of the common, trended and tagwise NB dispersions.
Quasi-likelihood dispersion aganist gene abundance. Estimates are shown for raw, tended and squeezed dispersions
Min. 1st Qu. Median Mean 3rd Qu. Max.
14.32 14.32 14.32 14.32 14.32 14.32 Checking normalization and QC
$Control_UPF3BKD
$Control_UPF3AOE
Distribution of results
Fold change distributions
DET statistics
Distribution of NIFs
Are DET shared between UPF3B KD and UPF3A KD?
sign.lfc
-1 1
1328 1860 sign.lfc
-1 1
816 1504 
What is the distribution between transcripts in UPF3B KD and UPF3A OE?
R version 4.2.2 Patched (2022-11-10 r83330)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.2 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
locale:
[1] LC_CTYPE=en_AU.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_AU.UTF-8 LC_COLLATE=en_AU.UTF-8
[5] LC_MONETARY=en_AU.UTF-8 LC_MESSAGES=en_AU.UTF-8
[7] LC_PAPER=en_AU.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] grid stats4 tools stats graphics grDevices utils
[8] datasets methods base
other attached packages:
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[3] glmpca_0.2.0 broom_1.0.4
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