SMLG (Statistical Machine Learning Group) Discussion Forum

FASTQC Reports for Trimmomatic Data

Multi QC

Feature Count Data Plus Graphs ( Multi QC)
Taabular Count Data

Data for BANJO

Sheet one contains participant ID in the first column, I ( for intervention in the second column) with B= Baseline and F= Fasted, the rest of the columns are the genes ( There are 350 gene columns total).

Sheet two contains the data in an easier way to input it into BNLEARN. The 350 genes come first and then the intervention data is in the last column.

Gene discretization key:
low = low expression; z<-1
none = no signficant gene expression; (-1 ≤ z ≤ 1)
high = high expression; z >1

Gene Expression Data

Data normalized by z score (see d-scale)

R script is posted in github

https://github.com/smlgfiuedu/BNLEARN-G ... ta-anlysis

Network scores generated :
> score(Bn4, Intervention, type = "bde" )
[1] -7082.487
> score(Bn4, Intervention, type = "loglik")
[1] -2544.214
> score(Bn5, Intervention, type = "bde" )
[1] -7095.455
> score(Bn5, Intervention, type = "loglik")
[1] -2592.736
> score(Bn6, Intervention, type = "bde" )
[1] -7101.518
> score(Bn6, Intervention, type = "loglik")
[1] -2555.251
> score(Bn7, Intervention, type = "bde" )
[1] -7095.455
> score(Bn7, Intervention, type = "loglik")
[1] -2592.736
> score(Bn8, Intervention, type = "bde" )
[1] -7095.455
> score(Bn8, Intervention, type = "loglik")
[1] -2592.736
>

CounT data

First column is Gene ID prior to annotation

DESSEQ2 Count Normalization ( See script posted in github)
https://github.com/smlgfiuedu/DESEQ-2-d ... ptDeseq2.R

DESEQ2 Count Normalization Method:
1) Determine Estimates Size Factor
2) Create Normalized Object
3) Undergo Variance Stablization Transformation

https://www.bioconductor.org/packages/d ... sformation
https://hbctraining.github.io/DGE_works ... ation.html

rpazo001 wrote:CounT data

First column is Gene ID prior to annotation

Can you post a count data with gene names annotated?