De novo assembly

In the next step, De novo assemblies need to be performed as per the computational infrastructure available. We provide an example commandline used by us

Differential expression analysis - edgeR

Differential expression analysis across the 2x10 libraries is performed using the Bioconductor packages edge

Compare mapping assemblies - Mapping 1

The quality of the mapping assemblies obtained after the consensus step is be evaluated

Simulate raw sequencing data - Step 2

The 2b_gnrCounts.R script generates per gene and per library expression levels for 2x10 libraries with differential expression among them. These read count files are used along with the fastq files simulated in previous step by 2c_drawreads.pl to create 2x10 libraries with differential expression among them

ZebraFinchData

Zebra finch CDS downloaded from Biomart (Ensembl Version 61) with 100 bp 5' UTR and 400 bp 3' UTR per gene

Distributions

Simuated read distributions per expression category

Simulate raw sequencing data - Step 1

In the second step, the reference genome is used along with expression profiles (exponential or uniform) to create fastq files using the program dwgsim version 0.1.2

Mapping assembly

The mapping assembly first requires mapping the reads onto the reference using stampy read mapper. The sam/bam file obtained after the mapping step is sorted and used to call the consensus sequence. Example commandline used by us can be modified suitably

Metadata by individual

Metadata for each crow sampled in this study: including population of origin, GPS coordinates, dates of feather plucking, dates of sampling, times of day of sampling, weight at sampling, approximate age at sampling, and number of days of feather regrowth until sampling

Differential expression analysis - baySeq

Differential expression analysis across the 2x10 libraries is performed using the Bioconductor package baySeq