I put an additional bam and bai in the index hacking google drive:

https://drive.google.com/open?id=1Y9krI6VX3vBzTKEcneGy1McnMJEK739m

human_2009_inOrder_evenNumberChromosomesAndXHaveLessData.bam
This file is from the smoketesting dataset for the 2009 human genome. I went through and chopped out some amount of data on every even numbered chromosome and the X chromosome. I kept the order of the chromosomes as they appear below. Note that the chromosomes are for the most part in order from largest to smallest. However, chr20, chr22, and chrX are out of order in terms of their size.

Order and sizes of chromosomes in bam/bai file
@SQ SN:chr1 LN:249250621
@SQ SN:chr2 LN:243199373
@SQ SN:chr3 LN:198022430
@SQ SN:chr4 LN:191154276
@SQ SN:chr5 LN:180915260
@SQ SN:chr6 LN:171115067
@SQ SN:chr7 LN:159138663
@SQ SN:chr8 LN:146364022
@SQ SN:chr9 LN:141213431
@SQ SN:chr10 LN:135534747
@SQ SN:chr11 LN:135006516
@SQ SN:chr12 LN:133851895
@SQ SN:chr13 LN:115169878
@SQ SN:chr14 LN:107349540
@SQ SN:chr15 LN:102531392
@SQ SN:chr16 LN:90354753
@SQ SN:chr17 LN:81195210
@SQ SN:chr18 LN:78077248
@SQ SN:chr19 LN:59128983
@SQ SN:chr20 LN:63025520
@SQ SN:chr21 LN:48129895
@SQ SN:chr22 LN:51304566
@SQ SN:chrM LN:16571
@SQ SN:chrX LN:155270560

I made a new altered file where the chromosomes are out of order from IGB. I tested the bai file in IGB, and it does appear to load the data in the wrong order. Even numbered and X chromosome have reduced data.

In the google drive: https://drive.google.com/open?id=1Y9krI6VX3vBzTKEcneGy1McnMJEK739m

Order of chromosomes in bam/bai
@SQ SN:chr11 LN:135006516
@SQ SN:chr12 LN:133851895
@SQ SN:chr13 LN:115169878
@SQ SN:chr14 LN:107349540
@SQ SN:chr15 LN:102531392
@SQ SN:chr16 LN:90354753
@SQ SN:chr17 LN:81195210
@SQ SN:chr18 LN:78077248
@SQ SN:chr19 LN:59128983
@SQ SN:chr20 LN:63025520
@SQ SN:chr21 LN:48129895
@SQ SN:chr22 LN:51304566
@SQ SN:chrM LN:16571
@SQ SN:chrX LN:155270560
@SQ SN:chr1 LN:249250621
@SQ SN:chr2 LN:243199373
@SQ SN:chr3 LN:198022430
@SQ SN:chr4 LN:191154276
@SQ SN:chr5 LN:180915260
@SQ SN:chr6 LN:171115067
@SQ SN:chr7 LN:159138663
@SQ SN:chr8 LN:146364022
@SQ SN:chr9 LN:141213431
@SQ SN:chr10 LN:135534747

I added some additional files to the Google Drive.

human_2009_outOfOrder (bam/bai) is out of order (starts with chromosome 11, see previous post), but includes all of the data (it is NOT truncated).

human_2009_inOrder_evenNumberChromosomesAndXHaveLessData.txt is the JVARkit output that gives an example of what the index contains. It looks like it does have bins up until the very end of the chromosome even when the data is truncated, but it may be misleading as the offsets become zero, which is odd. JVARkit does use the bam file header (which is why you can see the chromosome names) and may be adding in bins until the end of the chromosome length. May need to investigate further based on what Pawan has observed in IGB.

Additional test files

ftp://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/AshkenazimTrio/HG004_NA24143_mother/NIST_Illumina_2x250bps/novoalign_bams/

This task was mainly focused on the BAI files that had the out of order indexing of the BAM file
I was working on the matching the chromosomes with the bin sizes for that I carried out the following ways:

1. I got the maximum bin size from the bin list of each chromosome of the BAI file. After I tried matching it with the chromosome list from the GenLoadUtils. If the bin sizes of the indexed data are not complete the matching of the chromosomes.
For eg. If the indexed chromosome has the data with maximum binsize 100,000. Each chromosome has a unique length. So considering there are two chromosomes that are near to this value of indexed chromosome, chromosome A with 102,000 and chromosome B 112,000. So here we can easily guess that the indexed chromosome is A, but if the indexed chromosome is derived from chromosome B with no data after 100,000 we can never reach a correct conclusion for the same.
Hence we need to have a lookup of the order of indexing of the chromosomes ( It is present in the header of the BAM file).

2.We also referred to the method of using offsets instead of bin sizes for the chromosome length matching.
https://github.com/jorainer/biovizBase/blob/master/R/coverage.R
It also uses a similar approach of getting the sequences information of the chromosomes.

Unfortunately it does not seem possible to accurately compare the chromosome and bin sizes given the limitations of the bai index.

Closing this issue for now.