sfrenk / seq_utilities

Useful scripts to be used in combination with NGS analysis pipelines

Useful scripts to be used in combination with NGS analysis pipelines

DESeq2.R

Basic script for differential gene expression analysis with DESeq2

bed_count.sh

Takes a directory of bam files and for each file counts reads mapping to regions in a specified bed file. If a total_mapped_reads.txt file exists, this can be used to calculate normalized read counts

bed_counts_merge.py

Dependency for bed_count.sh

collapse_reads.sh

Used to collapse identical reads (often used in sRNA data to counteract the effect of "jackpotting"). Contains an option to uncollapsed a collapsed file.

fastqc.sh

Run fastqc on a directory of samples

go_terms.R

Get GO terms from DESeq2 output file.

make_bg.sh

Makes bedgraph file showing coverage for a group of bam files at specified loci

make_normalized_bw.sh

Makes normalized BigWig files from a directory of bam files. Tracks are normalized to the mean total mapped reads per library.

merge_counts.py

Merges read count files made from individual bam files into a single file that can be loaded straight into DESeq

rnaseq.R

Contains some basic processing steps for RNA-seq data that don't involve DESeq (eg. normalizing to total mapped reads)

run_picard_markdup.sh

Run the picard duplicate removal utility on a batch of bam files

srna_filter

Converts between fasta/fastq/raw file types. Optionally filters for reads based on sequence features (eg. 22 nucleotides long, beginning with a "G") and allows for 3' trimming (eg. to get rid of A-tails).

sra_download.sh

Download SRR files from sample IDs (eg. GSM IDs from GEO) and extract fastq files

trim.sh

Basic script for trimming reads with bbduk