In the main directory you will find bash
scripts named from 1 to 4. They should be run in that order (see Requirements).
It will download the raw reads directly from SRA with fasterq-dump
using the accession numbers stored in metadata-7938743-processed-ok.tsv
and rename them. Next step is to filter and trim reads with trimmomatic
.
Generates genome indices for star
based on files stored in references.
Maps reads using star
and generates BAM files as well as their indices.
Counts reads for parent species alignments using featureCounts
and for hybrid data and allele-specific expression it uses CompMap
. It will also generate tables with raw counts for each sample.
This directory includes bash
and r
scripts running RNA-seq data simulations for allele-specific expression using the package polyester
.
All the raw count tables are included here.
This contains two subdirectories scripts and tables.
scripts
has further subdirectories with r
scripts to generate summary tables from differential expression (and other) analyses.
tables
has all the raw summary tables used for this work.
Running some of the r
scripts will overwrite the files already in that directory. So do it carefully!
briggsae.nigoni.1-to-1.orto.dnds_final.csv
--> Includes dN, dS estimates for each orthologc_briggsae_genes_conv_to_wormbase.csv
--> CSV tables with equivalent gene names for the current C. briggsae WormBase release (PRJNA10731)orthologs.txt
--> A list with C. briggsae and C. nigoni orthologssamples.txt
--> List of sample names used for renaming files
samtools
CompMap
GNU-parallel
star
BWA
trimmomatic
sratools
featureCounts
polyester
glimma
edgeR
DESeq2
MASS
RColorBrewer
cowplot
dplyr
edgeR
ggVennDiagram
ggforce
ggplot2
ggplotify
ggpointdensity
ggrepel
ggridges
ggstance
ggtext
grid
gridExtra
gtable
lemon
parallel
scales
tibble
tidyr
venneuler
viridis