Aditi, I am sorry for the late reply. I was fixing my PC.. Below is the code for stringtie and ballgown. Here is the code for stringtie: stringtie -e -B -p 8 -G ./stringtie_merged.gtf -o ${BALLGOWNDIR}/SRR${A}/SRR${A}.gtf ${HISAT2DIR}/SRR${A}.bam

Here is the code for ballgown

#Read phenotype sample data
pheno_data = read.csv("data/frda_phenodata.csv", header = TRUE, colClasses = rep("character", 4))
pheno_data = pheno_data[order(pheno_data$ids), ]


# Read in expression data
ballgown_obj = ballgown(dataDir = "data/ballgown", samplePattern = "SRR", pData = pheno_data)

#Pre-Filtering out genes that are expressed at low levels prior to differential expression analysis reduces the severity of the multiple-testing correction and may improve the power of detection.\
#Pre-filtering to keep only rows that have at least 10 reads total (across samples). 
ballgown_obj1 = subset(ballgown_obj, "rowSums(texpr(ballgown_obj)) >= 10", genomesubset=TRUE)

#Filter low-abundance genes. Here we remove all transcripts with a variance across the samples of less than one:
ballgown_obj2 = subset(ballgown_obj, "rowVars(texpr(ballgown_obj)) > 1", genomesubset=TRUE)

#DE by transcript
differ_transcripts1 = stattest(ballgown_obj1, feature = "transcript", covariate = "genotype", getFC = TRUE,  meas = "FPKM")

#DE by gene
differ_genes1 = stattest(ballgown_obj1, feature = "gene", covariate = "genotype", getFC = TRUE, meas = "FPKM")