RNA-seq pipelines

• HISAT2 + StringTie2 pipeline
• STAR, Cufflinks, RSEM
• Kallisto

Setup

1. In raw run ./fetch_data.sh and then ./create_index.sh.
2. In src run ./fetch_binaries.sh (requires macOS or Linux), ./setup_samtools.sh, and ./setup_rsem.sh (requires various libraries for compiling).
3. HISAT2 and StringTie2 can be run from hisat_stringtie by running ./map.sh and then ./quant.sh.
4. STAR and RSEM can be run from star_rsem by running ./run.sh.
5. Kallisto can be run from kallisto by running ./quant.sh.

Test data

The data used to compare the workflows is from Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie, and Ballgown. Each FASTQ file is named using the SRA RUN IDs.

ERR188044
ERR188104
ERR188234
ERR188245
ERR188257
ERR188273
ERR188337
ERR188383
ERR188401
ERR188428
ERR188454
ERR204916

You can get more information on the run using Entrez Direct. (The run info obtained by running the command below is provided in the metadata folder.)

esearch -db sra -query ERR188044 | efetch -format runinfo
Run,ReleaseDate,LoadDate,spots,bases,spots_with_mates,avgLength,size_MB,AssemblyName,download_path,Experiment,LibraryName,LibraryStrategy,LibrarySelection,LibrarySource,LibraryLayout,InsertSize,InsertDev,Platform,Model,SRAStudy,BioProject,Study_Pubmed_id,ProjectID,Sample,BioSample,SampleType,TaxID,ScientificName,SampleName,g1k_pop_code,source,g1k_analysis_group,Subject_ID,Sex,Disease,Tumor,Affection_Status,Analyte_Type,Histological_Type,Body_Site,CenterName,Submission,dbgap_study_accession,Consent,RunHash,ReadHash
ERR188044,2012-11-07 04:42:08,2012-11-07 04:41:56,36349964,5525194528,36349964,152,3596,,https://sra-downloadb.st-va.ncbi.nlm.nih.gov/sos2/sra-pub-run-3/ERR188044/ERR188044.1,ERX162864,NA18498.2.M_120131_1 extract,RNA-Seq,cDNA,TRANSCRIPTOMIC,PAIRED,280,0,ILLUMINA,Illumina HiSeq 2000,ERP001942,PRJEB3366,,204869,ERS185292,SAMEA1573216,simple,9606,Homo sapiens,SAMEA1573216,,,,,,,no,,,,,CRG,ERA169774,,public,3DDC6C2865E755D74EBB7702A5BAC58E,D5681D67D5A545BF09827BA3E3C2706D

From the metadata we can see the that this run ID belongs to the SRA Study ERP001942, which is the "RNA-sequencing of 465 lymphoblastoid cell lines from the 1000 Genomes".

Comparing quantifications

The R Markdown document compare_quant.Rmd in analysis compares the quantification results.

Papers

Papers to read when deciding choice of tool, gene mdoels, and gene quantification method for RNA-seq experiments.

• A survey of best practices for RNA-seq data analysis
• Alignment and mapping methodology influence transcript abundance estimation
• A comprehensive evaluation of ensembl, RefSeq, and UCSC annotations in the context of RNA-seq read mapping and gene quantification
• A benchmark for RNA-seq quantification pipelines

Also checkout this list of benchmarks.