Mining transcriptomic data for gestational diabetes mellitus: What public datasets reveal

Table 2 Overview of RNA sequencing and expression profiling platforms used in gestational diabetes mellitus transcriptomic studies

Platform	Read configuration/probe architecture	Data output capacity	Advantages	Disadvantages	Frequency	Category
NovaSeq 6000	2 × 50 ~ 2 × 250 bp (2 × 150 bp common)	Ultra-high	High-throughput, good cost/data ratio	Expensive, best for large projects	11	NGS, short-read (Illumina)
HiSeq 4000	2 × 50 ~ 2 × 150 bp	High	Mainstream, reliable	Being replaced by NovaSeq	10	NGS, short-read (Illumina)
HiSeq 2000	2 × 100 bp	Moderate	Stable, classical platform	Older, limited throughput	4	NGS, short-read (Illumina)
HiSeq 2500	2 × 50 ~ 2 × 125 bp (rapid)	Moderate	Flexible (rapid/high modes)	Phasing out	6	NGS, short-read (Illumina)
NextSeq 500	2 × 75 ~ 2 × 150 bp	Middle	Fast run time, flexible	Limited throughput, costlier	4	NGS, short-read (Illumina)
NextSeq 2000	2 × 50 ~ 2 × 150 bp	Middle-high	Improved chemistry, higher quality	Still relatively costly	1	NGS, short-read (Illumina)
Illumina BeadChip	48 k/24 k fixed probes	Ultra-high	Mature, low cost	Lower sensitivity, cannot detect novel transcripts	5	DNA microarray
Affymetrix	3’-biased or whole-transcript probes	High	Mature database support	Lower resolution, narrow dynamic range	4	DNA microarray
Agilent	8 × 60 k format, 20638 genes	High	Cost-effective, widely used	Limited depth of analysis	4	DNA microarray

NGS: Next-generation sequencing.