Methods and reproducibility outputs¶
This page describes the reproducibility outputs generated by MTD Explorer.
These files are designed to help users audit, reproduce, and report an analysis run.
The main folder is:
Main reproducibility table¶
The most important reproducibility file is:
Example table:
Download example run parameters CSV
This table records the run configuration in a structured format.
The columns are usually:
Each row describes one setting, file path, software version, output pattern, or analysis choice used during the run.
Run metadata¶
The Run metadata rows record when and how the pipeline was launched.
Typical parameters include:
The original_command row is especially important because it stores the exact
command line used to start the analysis.
This can include input paths, output paths, host taxon settings, custom databases, read extraction options, and analysis parameters.
Input and output paths¶
The Input and output rows record the main files and folders used by the run.
Typical parameters include:
These rows help users trace the analysis back to the original samplesheet, FASTQ directory, output directory, and optional metadata file.
Study design¶
The Study design rows record settings that affect biological interpretation.
Typical parameters include:
These values help identify the host annotation used for downstream host analysis and the association metric used by HAllA.
Read preparation¶
The Read preparation rows record preprocessing settings.
Typical parameters include:
These rows document whether fastp trimming was used, the minimum read length, and the downstream FASTQ naming pattern.
Host filtering¶
The Host filtering rows record the Kraken2 settings used to split
host and non-host reads.
Typical parameters include:
host_kraken_db
host_kraken_db_mode
host_kraken_db_from_hostid
confidence
minimum_hit_groups
classified_out
unclassified_out
These rows are important because the host filtering step affects which reads are passed to downstream microbiome and functional analyses.
Microbiome classification¶
The Microbiome classification rows record the Kraken2 database and
classification settings used for the non-host read fraction.
Typical parameters include:
microbiome_kraken_db
microbiome_kraken_db_mode
microbiome_kraken_db_default
confidence
minimum_hit_groups
raw_report_pattern
final_report_pattern
These values should be reported when comparing taxonomic profiles across runs.
Contaminant removal¶
The Contaminant removal rows record whether a contaminant taxid list was
available to KrakenTools.
Typical parameters include:
If contaminant removal is enabled or available, users should check whether the raw and final global composition outputs differ.
Abundance estimation¶
The Abundance estimation rows record Bracken parameters.
Typical parameters include:
bracken_read_length
bracken_threshold
bracken_distribution_file
bracken_distribution_file_status
taxonomic_levels
These rows are useful for reproducing microbiome abundance estimation.
The read length and distribution file must match the intended Bracken database configuration.
Detected microbiome read extraction¶
The Detected microbiome read extraction rows record whether reads assigned to
detected microbiome taxa were extracted.
Typical parameters include:
These settings affect downstream per-taxon read extraction and any analyses based on extracted microbiome reads.
Host downstream analysis¶
The Host downstream analysis rows record host alignment, counting, and
ssGSEA-related settings.
Typical programs and tools include Magic-BLAST, HISAT2, featureCounts, and ssGSEA.
Typical parameters include:
host_alignment_mode
blast_database
hisat2_database
gtf_file
output
gmt_file
gmt_mode
protein_fasta
annotation_gff
These rows are important for reproducing host expression and gene-set activity results.
Functional profiling¶
The Functional profiling rows record HUMAnN settings.
Typical parameters include:
These rows help document how non-host reads were passed into functional profiling and how HUMAnN outputs were normalized.
Association analysis¶
The Association analysis rows record HAllA settings.
Typical parameters include:
These values help interpret the integration outputs and clarify whether extra diagnostic or alternative association analyses were enabled.
Key outputs¶
The Key outputs rows record major result files generated by the run.
Typical parameters include:
These paths help users locate the main taxonomic composition table, final species abundance table, and matrix used by HAllA.
Software paths and versions¶
The Software path and Software version rows record executable paths and
best-effort version captures.
Typical programs include:
These rows support reproducibility, but they should be interpreted carefully.
A value such as not_found or command not found means that the version
capture step did not find that executable in the environment where the capture
was attempted.
It does not necessarily mean the whole analysis failed.
Some tools may have been called from another environment, wrapper, module, or step-specific context.
Recommended inspection order¶
For reproducibility, inspect files in this order:
methods/mtd_methods_run_parameters.csv
methods/
host_counts.txt
Nonhost_DEG/
Host_DEG/
hmn_genefamily_abundance_files/
ssGSEA/
halla/
Start with methods/mtd_methods_run_parameters.csv.
Then inspect the output folders relevant to the result you want to reproduce.
What this page can support¶
The methods outputs can help answer questions such as:
What not to conclude¶
Do not assume two runs are comparable unless their databases, software versions, read preprocessing settings, taxonomic thresholds, normalization choices, and analysis modes are comparable.
Do not treat a visual output as reproducible without checking the corresponding run-parameter table.
Do not ignore not_found values in the software section; check whether they are
expected for that environment or indicate a missing executable.