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Quantify Reads with Kallisto

Description:

Kallisto will individually generate pseudoalignments and quantification for each replicate of each condition. In the Discovery Environment application, the 'Kallisto index' command will first build an index of the transcriptome. Next, that indexed transcriptome will be used to quantify the read data (equivalent to the 'Kallisto quant' command at the command line).

Input Data:

Input Description Example
Transcriptiome A transcriptome for pseudoalignment is required Arabidopsis transcriptome
FastQ files (e.g. SRR9666131.sra.fastq,SRR9666132.sra.fastq...) Sequencing data in FastQ format SRA FastQ Files

Import Transcriptome from Ensembl

  1. Go to the Ensembl homepage for Arabidopsis at https://plants.ensembl.org/Arabidopsis_thaliana/Info/Index.

  2. Under Gene annotation click the FASTA link under 'Download genes, cDNAs, ncRNA, proteins' ; ftp://ftp.ensemblgenomes.org/pub/plants/release-48/fasta/arabidopsis_thaliana.

  3. In the cnda folder, locate the file Arabidopsis_thaliana.TAIR10.cdna.all.fa.gz.

  4. In your web browser, copy the URL for this file (left click, Copy Link Location for most browsers). The URL for release 48 of Ensembl is ftp://ftp.ensemblgenomes.org/pub/plants/release-48/fasta/arabidopsis_thaliana/cdna/Arabidopsis_thaliana.TAIR10.cdna.all.fa.gz.

Tip

Ensure you use the 'cdna.all.fa.gz'; your annotation release must match what is used later in the Sleuth analysis

  1. In the Data view in the Discovery Environment, navigate to your rna-seq-tutorial folder.

  2. Create a new folder called transcriptome and navigate into the newly created folder.

  3. In the Data view, click the Upload button and choose Import from URL; paste in the URL for the Arabidopsis transcriptome. Be sure to avoid any extra spaces or characters at the end of your URL. Click Import to complete this action. You will get a notification when import is complete. You may need to refresh your browser to see the imported file.

  4. Back on the Ensembl page, also copy the URL for the CHECKSUMS file and repeat the import procedure to the same folder.

Tip

You can also apply metadata to the imported transcriptome. See also the for Data Store Guide additional options for apply metadata.

Use Kallisto App to Psuedoalign Reads

  1. Click on the Data icon and navigate to your rna-seq-tutorial tutorial folder and create a folder to store outputs, name the folder kallisto_analyses.

  2. In the Apps view, search for and launch the Kallisto-v.0.43.1 app.

  3. In Analysis Info you can name this analysis and provide any comments (optional). Under Output folder, navigate to the kallisto_analyses folder created earlier. Your outputs will automatically be placed in this folder; click Next.

  4. In Parameters under Input:

    (a) For The transcript fasta file supplied (fasta or gzipped) browse to the transcriptome folder and add the Arabidopsis_thaliana.TAIR10.cdna.all.fa.gz file. (b) For Paired or single end choose single. © Under FASTQ Files (Read1): Click Browse and browse to the fastq_files folder and select 12 files (e.g., SRR9666131.sra.fastq, SRR9666132.sra.fastq...).

    Under Options

    (a) For Number of bootstrap samples enter 25.

    (b) For Estimated average fragment length (required for single end reads) enter 200.

    © For Estimated standard deviation of fragment length (required for single end reads) enter 20.;

Note

Although SRA data usually does not contain fragment length and standard deviation, these are common values. For other options for this application, consult the Kallisto documentation. Bootstrapping is the most computationally intensive option, so higher numbers of bootstrapping operations will cause the analysis to take longer to complete.

Click Next.

  1. Click Next again to skip Advanced Settings (optional); under Review and Launch click Launch Analysis.
  2. Click on Analyses view to see the current status of the job; you can also click on the Analyses icon to navigate to this section. When the job is complete, you can click on the folder icon next to the analyses name to browse the results. You may need to Refresh to see the current job status. This job is estimated to take about 60-70 minutes.
  3. When the job has status Completed to navigate to the expected output. The expected output will be a folder Kallisto_quant_output containing 12 folders (labeled with the accession name).

Output/Results

Output Description Example
Kallisto quantification results (abundances.h5, abundances.tsv, run_info.json for each FastQ file analyzed ) See detailed description below Kallisto outputs

Description of output and results

Kallisto will generate a set of results for each FastQ file (or pairs of FastQ files if our data were paired-end sequenced). Inside each folder will be:

  • abundances.h5: HDF5 binary file containing run info, abundance estimates, bootstrap estimates, and transcript length information length. This file can be read in by Sleuth.

  • abundances.tsv: plaintext file of the abundance estimates. It does not contain bootstrap estimates. When plaintext mode is selected; output plaintext abundance estimates. Alternatively, Kallisto h5dump will output an HDF5 file to plaintext. The first line contains a header for each column, including estimated counts, TPM, effective length.

  • run_info.json: a json file containing information about the run.

Note

We did not select the BAM file creation option when launching the app. Although a BAM file will be created, it is empty and can be ignored.

Last update: 2022-11-28