fix

Author: valentinwust

docs/tutorials/integration_fixed-spectra/index.md

@@ -2,7 +2,7 @@
 
 In this tutorial, we demonstrate how to standardise data while using only measured dye spectra.
 
-First, we use [rainbow beads to calibrate the flow cytometer](integration_fixed-spectra-rainbow.ipynb), and apply this to the spectra and raw samples. Afterwards, we [fit a marker normalization using reference samples](integration_fixed-spectra-ref.ipynb) to normalize the unmixed marker intensities. While we strongly encourage the use of rainbow beads, the marker normalization can also be used independently from the cytometer standardization, and will be the dominant source of batch effects in many setups.
+First, we use [rainbow beads to calibrate the flow cytometer](integration_fixed-spectra-rainbow), and apply this to the spectra and raw samples. Afterwards, we [fit a marker normalization using reference samples](integration_fixed-spectra-ref) to normalize the unmixed marker intensities. While we strongly encourage the use of rainbow beads, the marker normalization can also be used independently from the cytometer standardization, and will be the dominant source of batch effects in many setups.
 
 ```{toctree}
 :hidden:

docs/tutorials/integration_variable-spectra/index.md

@@ -2,7 +2,7 @@
 
 In this tutorial, we showcase our full pipeline, including inferring appropriate dye spectra for every batch.
 
-As in the simpler case, we start with the [rainbow bead calibration](integration_variable-spectra-rainbow.ipynb) and apply it to the samples and single stain measurements. Afterwards, we [model the dye spectra variability](integration_variable-spectra-dye.ipynb) to compress the full spectral matrix into a smaller embedding. This then allows us to [fit a full standardisation from overlapping samples](integration_variable-spectra-model.ipynb), including both marker normalization factors and inferred dye spectra for every batch.
+As in the simpler case, we start with the [rainbow bead calibration](integration_variable-spectra-rainbow) and apply it to the samples and single stain measurements. Afterwards, we [model the dye spectra variability](integration_variable-spectra-dye) to compress the full spectral matrix into a smaller embedding. This then allows us to [fit a full standardisation from overlapping samples](integration_variable-spectra-model), including both marker normalization factors and inferred dye spectra for every batch.
 
 ```{toctree}
 :hidden: