Make consistent tense (present)

jupyter-book/introduction/scrna_seq.md

@@ -248,7 +248,7 @@ Limitations:
 
 #### Nanopore single-cell transcriptome sequencing
 
-Long-read single-cell sequencing approaches rarely used UMI {cite}`Singh2019` or did not perform UMI correction {cite}`Gupta2018` and therefore assigned novel UMI reads to novel UMIs. Due to the higher sequencing error rate of long-read sequencers this causes serious issues {cite}`Lebrigand2020`. Lebrigand et al. introduced ScNaUmi-seq (Single-cell Nanopore sequencing with UMIs) which combines Nanopore sequencing with cell barcode and UMI assignment. The barcode assignment is guided with Illumina data by comparing the cell bar code sequences found in the Nanopore reads with those recovered from the Illumina reads for the same region or gene {cite}`Lebrigand2020`. However, this effectively requires two single-cell libraries. scCOLOR-seq computationally identifies barcodes without errors using nucleotide pair complementary across the full length of the barcode. These barcodes are then used as guides to correct the remaining erroneous barcodes {cite}`Philpott2021`. A modified UMI-tools directional network based method corrects for UMI sequence duplication.
+Long-read single-cell sequencing approaches rarely use UMI {cite}`Singh2019` or do not perform UMI correction {cite}`Gupta2018` and therefore misassign some reads to novel UMIs. Due to the higher sequencing error rate of long-read sequencers this causes serious issues {cite}`Lebrigand2020`. Lebrigand et al. introduced ScNaUmi-seq (Single-cell Nanopore sequencing with UMIs) which combines Nanopore sequencing with cell barcode and UMI assignment. The barcode assignment is guided with Illumina data by comparing the cell bar code sequences found in the Nanopore reads with those recovered from the Illumina reads for the same region or gene {cite}`Lebrigand2020`. However, this effectively requires two single-cell libraries. scCOLOR-seq computationally identifies barcodes without errors using nucleotide pair complementary across the full length of the barcode. These barcodes are then used as guides to correct the remaining erroneous barcodes {cite}`Philpott2021`. A modified UMI-tools directional network based method corrects for UMI sequence duplication.
 
 Strengths:
 
@@ -270,6 +270,8 @@ For an extensive comparison of all single-cell sequencing protocols, we recommen
 
 So far we have only been discussing single-cell assays, but it is also possible to only sequence the nuclei of the cells.
 Single-cell profiling does not always provide an unbiased view on cell types for specific tissues or organs, such as, for example, the brain. During the tissue dissociation process, some cell types are more vulnerable and therefore difficult to capture. For example, fast-spiking parvalbumin-positive interneurons and subcortically projecting glutamatergic neurons were observed in lower proportions than expected in mouse neocortex{cite}`Tasic2018`. On the contrary, non-neuronal cells survive dissociation better than neurons and are overrepresented in single-cell suspensions in the adult human neocortex{cite}`darmanis2015`. Moreover, single-cell sequencing highly relies on fresh tissue, making it difficult to make use of tissue biobanks.
+
+
 On the other hand, the nuclei are more resistant to mechanical force, and can be safely isolated from frozen tissue without the use of tissue dissociation enzymes{cite}`Krishnaswami2016`. Both options have varying applicability across tissues and sample types, and the resulting biases and uncertainties are still not fully uncovered. It has been shown already that nuclei accurately reflect all transcriptional patterns of cells{cite}`Ding2020`.
 The choice of single-cell versus single-nuclei in the experimental design is mostly driven by the type of tissue sample. Data analysis however should be aware of the fact that dissociation ability will have a strong effect on the potentially observable cell types. Therefore, we strongly encourage discussions between wet lab and dry lab scientists concerning the experimental design.