Data

Tools

Indexes

Applications

Experiments

Awesome

An open API service indexing awesome lists of open source software.

https://github.com/zavolanlab/tin-score-calculation

Given a set of BAM files and a gene annotation BED file, calculates the Transcript Integrity Number (TIN) for each transcript.
https://github.com/zavolanlab/tin-score-calculation

bioinformatics high-throughput-sequencing quality-control rna-seq

Last synced: 5 months ago
JSON representation

Given a set of BAM files and a gene annotation BED file, calculates the Transcript Integrity Number (TIN) for each transcript.

Awesome Lists containing this project

README 

          
[![ci](https://github.com/zavolanlab/tin-score-calculation/workflows/ci/badge.svg?branch=dev)](https://github.com/zavolanlab/tin-score-calculation/actions?query=workflow%3Aci)

[![CodeFactor](https://www.codefactor.io/repository/github/zavolanlab/tin-score-calculation/badge)](https://www.codefactor.io/repository/github/zavolanlab/tin-score-calculation)

[![GitHub issues](https://img.shields.io/github/issues/zavolanlab/tin-score-calculation)](https://github.com/zavolanlab/tin-score-calculation/issues)

[![GitHub license](https://img.shields.io/github/license/zavolanlab/tin-score-calculation)](https://github.com/zavolanlab/tin-score-calculation/blob/dev/LICENSE)



# TIN score calculation



Given a set of BAM files and a gene annotation BED file, calculates the

Transcript Integrity Number (TIN) for each transcript.



## Main usage



```sh

python calculate-tin.py [-h] [options]

```



### Parameters



```console

  --version             show program's version number and exit

  -h, --help            show this help message and exit

  -i INPUT_FILES, --input=INPUT_FILES

                        Input BAM file(s). "-i" takes these input: 1) a single

                        BAM file. 2) "," separated BAM files (no spaces

                        allowed). 3) directory containing one or more bam

                        files. 4) plain text file containing the path of one

                        or more bam files (Each row is a BAM file path). All

                        BAM files should be sorted and indexed using samtools.

                        [required]

  -r REF_GENE_MODEL, --refgene=REF_GENE_MODEL

                        Reference gene model in BED format. Must be strandard

                        12-column BED file. [required]

  -c MINIMUM_COVERAGE, --minCov=MINIMUM_COVERAGE

                        Minimum number of read mapped to a transcript.

                        default=10

  -n SAMPLE_SIZE, --sample-size=SAMPLE_SIZE

                        Number of equal-spaced nucleotide positions picked

                        from mRNA. Note: if this number is larger than the

                        length of mRNA (L), it will be halved until it's

                        smaller than L. default=100

  --names=SAMPLE_NAMES  sample names, comma separated (no spaces allowed);

                        number must match the number of provided bam_files

  -s, --subtract-background

                        Subtract background noise (estimated from intronic

                        reads). Only use this option if there are substantial

                        intronic reads.

  -p NRPROCESSES, --processes=NRPROCESSES

                        Number of child processes for the parallelization.

                        Default: 1

```



### File formats



- [BAM](https://samtools.github.io/hts-specs/SAMv1.pdf)

- [BED](https://www.ensembl.org/info/website/upload/bed.html)



Sample output ([TSV](https://en.wikipedia.org/wiki/Tab-separated_values)):



```console

transcript         sample_name

ENST00000303113    80.6328743265

ENST00000427445    0

ENST00000430792    59.7324017312

ENST00000647504    84.8860204563

ENST00000398647    64.4764470574

ENST00000400202    69.6331415873

ENST00000455813    85.3605191157

ENST00000397854    92.3965306733

ENST00000630077    72.8829044591

```



### Information



The tool was forked off the script `tin.py` (v2.6.4) of the

[`RSeQC`](http://rseqc.sourceforge.net/) package to achieve some speed-up.



This program calculates transcript integrity number (TIN) for each transcript

(or gene) in BED file. TIN is conceptually similar to RIN (RNA integrity number)

but provides transcript level measurement of RNA quality and is more sensitive

to measure low quality RNA samples:



1. TIN score of a transcript is used to measure the RNA integrity of the

transcript.

2. Median TIN score across all transcripts can be used to measure RNA integrity

of that "RNA sample".

3. TIN ranges from 0 (the worst) to 100 (the best). TIN = 60 means: 60% of the

transcript has been covered if the reads coverage were uniform.

4. TIN will be assigned to 0 if the transcript has no coverage or covered reads

is fewer than cutoff.



## Extended usage



Additionaly, this repository has been updated with three simple Python scripts.



### TIN score merging



Merge TIN score tables for multiple samples.



```sh

python merge-tin.py [-h] [options]

```



#### Parameters



```console

  -h, --help            show this help message and exit

  -v {DEBUG,INFO,WARN,ERROR,CRITICAL}, --verbosity {DEBUG,INFO,WARN,ERROR,CRITICAL}

                        Verbosity/Log level. Defaults to ERROR

  -l LOGFILE, --logfile LOGFILE

                        Store log to this file.

  --input-files INFILES

                        Space-separated paths to the input tables.

  --output-file OUTFILE

                        Path for the outfile with merged TIN scores

```



Output file is formatted in a TSV table as well.



### TIN score plotting



Create per-sample [boxplots](https://en.wikipedia.org/wiki/Box_plot) of TIN scores.



```sh

python plot-tin.py [-h] [options]

```



#### Parameters



```console

  -h, --help            show this help message and exit

  -v {DEBUG,INFO,WARN,ERROR,CRITICAL}, --verbosity {DEBUG,INFO,WARN,ERROR,CRITICAL}

                        Verbosity/Log level. Defaults to ERROR

  -l LOGFILE, --logfile LOGFILE

                        Store log to this file.

  --input-file INFILE   Path to the table with merged TIN scores

  --output-file-prefix OUTFILE_PREFIX

                        Prefix for the path to the TIN boxplots.

```



The boxplots are generated in [PDF](https://en.wikipedia.org/wiki/PDF) and

[PNG](https://en.wikipedia.org/wiki/Portable_Network_Graphics) formats under

`output-file-prefix`+`.pdf` and `output-file-prefix`+`.png`.



### TIN score summary



Calculate simple summary statistics for the per-sample TIN scores.



```sh

python summarize-tin.py [-h] [options]

```



#### Parameters



```console

  -h, --help            show this help message and exit

  -v {DEBUG,INFO,WARN,ERROR,CRITICAL}, --verbosity {DEBUG,INFO,WARN,ERROR,CRITICAL}

                        Verbosity/Log level. Defaults to ERROR

  -l LOGFILE, --logfile LOGFILE

                        Store log to this file.

  --input-file INFILE   Path to the table with merged TIN scores

  --output-file OUTFILE

                        Path for the output table with TIN statistics.

```



Output file is formatted in a TSV table as well.



## Run locally



In order to use the scripts you will need to clone this repository and install

the dependencies:



```sh

git clone https://github.com/zavolanlab/tin-score-calculation

cd tin-score-calculation

pip install .

```



Alternatively you can install it via pypi by:

```sh

pip install tin-score-calculation

```



Alternatively you can install it via conda by:



```sh

conda install -c bioconda -c conda-forge tin-score-calculation

```



> **NOTES:**  

>  

> - You may want to install dependencies inside a virtual environment,

>   e.g., using [`virtualenv`](https://virtualenv.pypa.io/en/latest/). Alternatively, if you use [`conda`](https://docs.conda.io/en/latest/) we provide an environment recipe too - in such case just run `conda env create`.

> - Some of the dependencies require specific system libraries to be installed, this however should be taken care of by the package manager.



You can then find the scripts in directory `scripts/` and run it as described in

the [Main usage](#main-usage) and [Extended usage](#extended-usage) sections.

To run the tool with minimum test files, try:



```sh

calculate-tin.py \

-i .test/calculate-tin/sample.bam \

-r .test/calculate-tin/transcripts.bed \

--names "sample_name" \

1> .test/calculate-tin/test.tsv



merge-tin.py \

--input-files .test/merge-tin/sample_1.tsv .test/merge-tin/sample_2.tsv \

--output-file .test/merge-tin/test.tsv



plot-tin.py \

--input-file .test/plot-tin/merged.tsv \

--output-file-prefix .test/plot-tin/test



summarize-tin.py \

--input-file .test/summarize-tin/merged.tsv \

--output-file .test/summarize-tin/test.tsv

```



## Run inside container



If you have [Docker](https://www.docker.com/) installed, you can also pull the

Docker image:



```sh

docker pull quay.io/biocontainers/tin-score-calculation:0.6--pyh5e36f6f_0

```



You can execute the scripts as following:



```sh

docker run -it quay.io/biocontainers/tin-score-calculation:0.6--pyh5e36f6f_0 calculate-tin.py --help

docker run -it quay.io/biocontainers/tin-score-calculation:0.6--pyh5e36f6f_0 merge-tin.py --help

docker run -it quay.io/biocontainers/tin-score-calculation:0.6--pyh5e36f6f_0 plot-tin.py --help

docker run -it quay.io/biocontainers/tin-score-calculation:0.6--pyh5e36f6f_0 summarize-tin.py --help

```



> **NOTE:** To run the tool on your own data in that manner, you will probably

> need to [mount a volume](https://docs.docker.com/storage/volumes/) to allow

> the container read input files and write persistent output from/to the host

> file system.



## Version



0.6.3



## Contact



Please see the [list of contributors](contributors.md) for contact information.