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* added troubleshooting section to readme

* updated readme

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@jacksonjacobs1
jacksonjacobs1 authored Jan 9, 2024
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# HistoQC
---


HistoQC is an open-source quality control tool for digital pathology slides

![screenshot](https://user-images.githubusercontent.com/9681868/40330248-a39603a2-5d4c-11e8-9d16-cc13fd9e21d4.png)

# Requirements
---

Tested with Python 3.7 and 3.8
Note: the DockerFile installs Python 3.8, so if your goal is reproducibility you may want to take this into account
Expand Down Expand Up @@ -36,12 +35,27 @@ Openslide binaries will have to be installed separately as per individual o/s in

The most basic docker image can be created with the included (7-line) Dockerfile.


# Installation

You can install HistoQC into your system by using

```bash
git clone https://github.com/choosehappy/HistoQC.git
cd HistoQC
python -m pip install --upgrade pip # (optional) upgrade pip to newest version
pip install -r requirements.txt # (required) install pinned versions of packages
pip install . # (recommended) install HistoQC as a package
```
Note that `pip install .` will install HistoQC as a python package in your environment. If you do not want to install HistoQC as a package, you will only be able to run HistoQC from the `HistoQC` directory.

# Basic Usage
---

## histoqc CLI

Running the pipeline is now done via a python module:

```
```
C:\Research\code\HistoQC>python -m histoqc --help
usage: __main__.py [-h] [-o OUTDIR] [-p BASEPATH] [-c CONFIG] [-f] [-b BATCH]
[-n NPROCESSES] [--symlink TARGET_DIR]
Expand Down Expand Up @@ -70,27 +84,18 @@ optional arguments:
```

HistoQC now has a httpd server which allows for improved result viewing, it can be accessed like so:
Installed or simply git-cloned, a typical command line for running the tool thus looks like:

```bash
python -m histoqc -c v2.1 -n 3 "*.svs"
```
C:\Research\code\HistoQC>python -m histoqc.ui --help
usage: __main__.py [-h] [--bind ADDRESS] [--port PORT] [--deploy OUT_DIR]
[data_directory]
positional arguments:
data_directory Specify the data directory [default:current directory]

optional arguments:
-h, --help show this help message and exit
--bind ADDRESS, -b ADDRESS
Specify alternate bind address [default: all
interfaces]
--port PORT Specify alternate port [default: 8000]
--deploy OUT_DIR Write UI to OUT_DIR
which will use 3 process to operate on all svs files using the named configuration file config_v2.1.ini from the config directory.

```
In case of errors, HistoQC can be run with the same output directory and will begin where it left off, identifying completed images by the presence of an existing directory.

Lastly, supplied configuration files can be viewed and modified like so:
## histoqc.config CLI
Supplied configuration files can be viewed and modified like so:

```
Expand All @@ -108,36 +113,46 @@ optional arguments:
```


If you would like, you can install HistoQC into your system by using

```
git clone https://github.com/choosehappy/HistoQC.git
cd HistoQC
python -m pip install --upgrade pip # (optional) upgrade pip to newest version
pip install -r requirements.txt # install pinned versions of packages
pip install .
Alternatively one can specify their own modified config file using an absolute or relative filename:

```bash
python -m histoqc.config --show light > mylight.ini
python -m histoqc -c ./mylight.ini -n 3 "*.svs"
```

Installed or simply git-cloned, a typical command line for running the tool thus looks like:
## histoqc.ui CLI

HistoQC now has a httpd server which allows for improved result viewing, it can be accessed like so:

```
python -m histoqc -c v2.1 -n 3 "*.svs"
```
C:\Research\code\HistoQC>python -m histoqc.ui --help
usage: __main__.py [-h] [--bind ADDRESS] [--port PORT] [--deploy OUT_DIR]
[data_directory]
which will use 3 process to operate on all svs files using the named configuration file config_v2.1.ini from the config directory.
positional arguments:
data_directory Specify the data directory [default:current directory]
Alternatively one can specify their own modified config file using an absolute or relative filename:
optional arguments:
-h, --help show this help message and exit
--bind ADDRESS, -b ADDRESS
Specify alternate bind address [default: all
interfaces]
--port PORT Specify alternate port [default: 8000]
--deploy OUT_DIR Write UI to OUT_DIR
```
python -m histoqc.config --show light > mylight.ini
python -m histoqc -c ./mylight.ini -n 3 "*.svs"
```


Afterward completion of slide processing you can view the results in your web-browser simply by following the directions after typing:
After completion of slide processing, view results in your web-browser simply by running the following command *from within the output directory* (saved in the **histoqc_output_YYMMDD-hhmmss** format by default. See histoqc CLI -o option)

```bash
cd histoqc_output_YYMMDD-hhmmss
python -m histoqc.ui
```
python -m histoqc.ui

... OR set data_directory to the output directory explicitly:
```bash
python -m histoqc.ui ./histoqc_output_YYMMDD-hhmmss
```

Which will likely say something like:
Expand All @@ -147,32 +162,30 @@ Serving HistoQC UI on 0.0.0.0 port 8000 (http://0.0.0.0:8000/) ...
```

Allowing you to browse to http://localhost:8000/ to select your results.tsv file.

In case of errors, HistoQC can be run with the same output directory and will begin where it left off, identifying completed images by the presence of an existing directory.

This can also be done remotely, but is a bit more complex, see advanced usage.

# Configuration modifications
---


HistoQC's performance is significantly improved if you select an appropriate configuration file as a starting point and modify it to suit your specific use case.

If you would like to see a list of provided config files to start you off, you can type

```
```bash
python -m histoqc.config --list
```

and then you can select one and write it to file like so for your modification and tuning:

```
```bash
python -m histoqc.config --show ihc > myconfig_ihc.ini
````
```



# Advanced Usage
---



See [wiki](https://github.com/choosehappy/HistoQC/wiki)
Expand All @@ -184,10 +197,12 @@ Information from HistoQC users appears below:

1. the new Pannoramic 1000 scanner, objective-magnification is given as 20, when a 20x objective lense and a 2x aperture boost is used, i.e. image magnification is actually 40x. While their own CaseViewer somehow determines that a boost exists and ends up with 40x when objective-magnification in Slidedat.ini is at 20, openslide and bioformats give 20x.

1.1. When converted to svs by CaseViewer, the MPP entry in ImageDescription meta-parameter give the average of the x and y mpp. Both values are slightly different for the new P1000 and can be found in meta-parameters of svs as tiff.XResolution and YResolution (inverse values, so have to be converted, also respecting ResolutionUnit as centimeter or inch
1.1. When converted to svs by CaseViewer, the MPP entry in ImageDescription meta-parameter give the average of the x and y mpp. Both values are slightly different for the new P1000 and can be found in meta-parameters of svs as tiff.XResolution and YResolution inverse values, so have to be converted, also respecting ResolutionUnit as centimeter or inch



# Citation
---

If you find this software useful, please drop me a line and/or consider citing it:

"HistoQC: An Open-Source Quality Control Tool for Digital Pathology Slides", Janowczyk A., Zuo R., Gilmore H., Feldman M., Madabhushi A., JCO Clinical Cancer Informatics, 2019
Expand Down

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